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This study focuses on the improvement of the tracking performance of space observation radar systems. Coherent radar systems usually provide an observation vector including four observables (range, range rate, azimuth, elevation) measured at a given epoch. Moreover, for some coherent radars, such as the TIRA system, it is possible to determine an additional parameter, the range rate, which is extracted from the collected complex amplitude. The tracking performance can be improved by increasing the observation parameter accuracy. The influence of each parameter on the overall tracking performance can be assessed by conducting a sensitivity analysis. The investigation shows that the best way to increase the accuracy of the state vector is by improving the angle estimates. The TIRA system is equipped with a tracking radar and an imaging radar. A powerful solution to improve the tracking performance is the realization of a multi-sensor data fusion between the two radars of the system. [ABSTRACT FROM AUTHOR]

In this paper, we present the results of a special experimental study of quiet-time behavior of the mid-latitude ionosphere over Eastern Europe by synchronously operation of different ground-based facilities. For the first time we used data obtained from Kharkiv incoherent scatter (IS) radar, ionosonde and coherent Doppler HF sounding system to detect and investigate traveling ionospheric disturbances (TIDs). The periods close to winter solstice and autumn equinox in 2018 were analyzed. The dominant periods and horizontal phase velocities of registered TIDs were 45–80 min and 230–460 m s−1, respectively. The strongest signatures were observed in the solstice measurement and represented by large amplitudes. Based on results obtained by all three methods, we found the LS TIDs with the same interval of time and altitude of propagation and similar characteristics (the period of about 50 min, estimated vertical 80 m/s and horizontal 460 m/s velocity and horizontal spatial scale size about 1360 km) for winter measurement. Such observational findings confirm the reliability of these TID detection techniques. Possible sources of TIDs generation were considered including solar terminator. [ABSTRACT FROM AUTHOR]

• Middle atmosphere dynamics and coupling using three decades of Indian MST radar and complimentary observations. • Highlighted recent results on waves, tides, planetary waves, tropopause, STE processes and low-latitude mesospheric dynamics. • Gap areas and scope for future study using other complementary techniques are mentioned. The genesis for Indian Mesosphere-Stratosphere-Troposphere (MST) radar came from the Indian Middle Atmospheric Programme (IMAP) to study the middle atmospheric dynamics and its underlying processes. During the early 1990s VHF radar operating at 53 MHz has been set up at Gadanki (13.5°N, 79.2°E), India, which started operating initially in the stratospheric and tropospheric (ST) mode. It is upgraded to MST mode in 1993. Since then, it has served various scientific experiments not only from India but under international collaboration. Numerous focused campaigns that have national and international importance were conducted. Using this unique data in the last 30 years along with complementary measurements, several stimulating results has been reported covering a wide range of topics that includes gravity wave characteristics, tides, planetary waves, oscillations, tropopause dynamics and stratosphere-troposphere exchange processes, monsoon dynamics and circulations, mesospheric structure and dynamics, vertical and lateral coupling and long-term trends. The present communication will highlight the unique results obtained using long-term observations of Indian MST radar and complementary techniques covering the complete middle atmosphere. Unique results include quantification of the momentum carried by the high-frequency waves generated in the troposphere up to the mesosphere, demarcating the complete tropical tropopause layer using MST radar observations alone, indication for the strengthening of the tropical easterly jet in the recent decade, unusual behavior of the Hadley circulation during drought and El Nino years, the revelation of the mechanisms for the occurrence of mesospheric echoes at the tropical latitudes, quantification of the turbulence, evidence for the role of anthropogenic changes on the dynamics of the mesosphere and generation of the empirical model by combing multi-instrument data sets. These data set also served in validating numerous ground-based and space-borne measurements including several re-analysis products over a tropical latitude. Issues remained unresolved and ways to tackle in future experiments are highlighted. [ABSTRACT FROM AUTHOR]

This review article provides an overview of various aspects of lunar exploration, including missions to the Moon, collection and analysis of lunar sample data in laboratories, and the processing and analysis of remote sensing data, particularly using radar techniques. Both remote sensing and in-situ methods are critical for advancing our understanding of the lunar surface and its properties. This review article focuses on the identification and quantification of water–ice deposits located in areas such as Permanently shadowed areas (PSRs) and the lunar poles (section " Lunar Poles and PSRs: A Special Environment "). These volatile resources have the potential to serve as valuable sources of fuel for future missions, making it crucial for the lunar community to determine their abundance and distribution. After thoroughly examining lunar samples using high-precision laboratory techniques, many preconceptions were dispelled which is highlighted in the section " Laboratory Investigation of Lunar samples ". But as in-situ observations are difficult to acquire, especially terrestrial bodies samples, remote sensing techniques allow the global understanding of the surface. The article specifically highlights the importance of understanding the electrical characteristics of the lunar surface and how radar inversion can provide valuable information in this regard. The " Conclusion " section of this review article serves as a key takeaway for readers, underscoring the critical role that both in-situ and remote sensing techniques play in advancing our understanding of the Moon. [ABSTRACT FROM AUTHOR]

• A frequency-domain retracker with interface to In-Flight Point-Target-Response. • Assessment of the impact of In-Flight Point-Target-Response for Sentinel-6 MF. • The range walk correction applied via a Chirp-Zeta-Transform algorithm. • Assessment of the impact of the range-walk correction for Sentinel-6 MF. • A full Cal/Val of the first year of Sentinel-6 MF altimetry science data. Poseidon-4 is a dual-frequency redundant radar altimeter on board the European Commission Copernicus Programme Sentinel-6 Michael Freilich satellite, that represents a significant breakthrough with respect to its predecessors Jason-class altimeters due to its digital architecture and to its innovative measurements and calibration modes. In the framework of the Sentinel-6 Michael Freilich commissioning preparatory activities, CNES has contracted CLS for the development of a Sentinel-6 Processing Prototype (S6PP) application. S6PP is a multi-chain processing suite able to process Sentinel-6 Level-1A and Level-1B data products up to Level-2. The novel algorithms developed in the CNES/CLS research and development activities are implemented within S6PP and validated to support the different thematic applications (in particular inland water and ocean) and in view of promoting them for possible implementation in the operational ground segment. The present work covers in particular the main results over open ocean for the main altimetric geophysical variables over the sea surface (sea surface height anomaly, significant wave-height, sigma-nought and wind speed) derived by the Low-Resolution Mode (LRM) and High-Resolution Mode (HRM) chains of S6PP in terms of precision, accuracy, spectral content and measurement stability. Given the reported variation of the payload in-orbit temperatures along with the reported instrumental ageing, and given the tight requirement to measure the GMSL (Global Mean Sea Level) in seamless continuity with Jason-3, the clear goal for S6PP was to process the S6-MF data with the minimum possible level of approximations along the processing pipeline but still maintaining a very efficient prototype from the computational point of view. For this scope, a novel and computationally efficient numerical retracking scheme with interface to the in-flight PTR (Point Target Response) provided by the instrument calibration chain has been put in place within S6PP for both the Low-Resolution and High-Resolution modes whereas the Delay-Doppler beam-forming is carried out by applying the range walk correction based on a computationally efficient algorithm (Chirp Zeta-Transform). The impact of the range walk correction and of the in-flight PTR interface is assessed for HRM and LRM, respectively. The paper shows that the proposed processing baseline ensures a dataset robust from the currently known instrumental degradation or ageing issues, both in LRM and HRM mode and, once this is done, that Sentinel-6 Michael Freilich global mean sea level measurement is in line with the one measured by Jason-3. [ABSTRACT FROM AUTHOR]

Calibrating the relative positional posture of the roadside sensor with respect to the road is crucial for target tracking and sensor fusion. However, most previous studies rely on prior information or require additional manual measurements, which increases calibration error and labor costs. This paper proposes an automatic extrinsic parameters calibration method for roadside integrated radar camera fusion sensors for the first time. In particular, we leverage the radar camera fusion framework to automatically reconstruct the road plane. Specifically, to integrate sensing abilities, a stable bidirectional selection association method is adopted to match radar and camera trajectories. Based on the association results, the Extended Kalman Filter (EKF) is adopted to fuse pixel positions and three-dimensional (3D) velocities of vehicles, and then a series of 3D positions of vehicle bottoms are obtained to reconstruct the road plane. Experimental results show that our proposed method achieves automatic and accurate calibration of extrinsic parameters. • An automatic extrinsic parameters calibration method. • Calibration method for roadside radar camera fusion sensors for the first time. • Use radar to provide scale factors, thus eliminating the need for prior information. • The method is tested in real-world scenarios and achieves promising performance. • Experiments verify that the proposed method is robust to data association results. [ABSTRACT FROM AUTHOR]

During deorbiting, be it natural orbital decay or otherwise (e.g. self-disposal or active debris removal), precise knowledge of the condition of the target is of critical importance. The Tracking and Imaging Radar (TIRA) is an instrument that possesses the ability to accurately determine satellite and space debris orbits while also generating detailed radar images of them. We present recent results from the characterization of deorbiting satellites and space debris employing TIRA. Drawing examples from orbital decay events (Tiangong-1, Soyuz 2.1v R/B), deorbiting (Tiangong-2) and self-disposal operations (Carbonite-1, MicroSCOPE), we demonstrate the potential of TIRA. Furthermore, we focus on the emerging field of active debris removal (ADR), where reliable information of the on-orbit status and attitude motion of potential targets can "make or break" an ADR mission. In this context, the on-orbit status of a JAXA R/B (43682) and a VESPA adapter (39162) are investigated. We employ inverse synthetic aperture radar (ISAR) imaging and 3D modelling of ISAR images, obtained with TIRA, to characterize the status and attitude motion of satellites and space debris. When certain conditions render direct imaging unsuitable, the more powerful L-band tracking radar of TIRA is used to obtain and analyze the temporal evolution of their radar cross-section (RCS). In this work, we employ for the first time, a wavelet time–frequency analysis of such RCS signatures, specifically of NABEO-1 (43692) in LEO and an Ariane 5 rocket body (28904) in geostationary transfer orbit (GTO), to characterize their on-orbit status. The wavelet analysis delivers results in good agreement with more traditional tools, with added information on time localization of periodicities. We are thus able to confirm the tumbling motion of NABEO-1 and constrain the rotational velocity of Ariane 5 upper stage (28904). [ABSTRACT FROM AUTHOR]

This work outlines and assesses several methods for the detection of manoeuvres in Low Earth Orbit (LEO) from surveillance radar data. To be able to detect manoeuvres, the main starting assumption is that the object under analysis has an orbit known with a sufficient degree of precision. Based on the precise (a posteriori) orbit and radar data, several manoeuvre detection methods are presented; one is based on unscented Kalman filtering, whereas two others algorithms are based on reachability analysis of the state, which correlates its prediction set with the next track from the radar. The filtering algorithm can be extended for several radar tracks, whereas the reachability-based methods are more precise in detecting manoeuvres. Then, to inherit the best properties of both classes of algorithms, a manoeuvre detection filter that combines both concepts is finally presented. Manoeuvre detection results are analysed first for simulated scenarios—for validation and calibration purposes—and later for real data. Radar information comes from the Spanish Space Surveillance Radar (S3TSR), with real manoeuvre information and high-quality ephemerides. The results show promise, taking into account that a single surveillance radar is the only source of data, obtaining manoeuvre detection rates of more than 50% and false positive rates of less than 10%. [ABSTRACT FROM AUTHOR]

Curved periacetabular osteotomy (CPO) is indicated for patients with developmental dysplasia of hip (DDH) to prevent progressive osteoarthritis. Patients with DDH have not only lateral acetabulum dysplasia but also anterior and posterior dysplasia. The full circumference acetabular coverage angle (ACA) of the femoral head should be evaluated preoperatively. This study aimed to determine the full circumference ACA in the patients with DDH before and after CPO compared with the coverage in normal patients. Twenty-three patients (a total of 24 hips) with DDH undergoing CPO between February 2006 and March 2014 were included in this study. The normal group was defined as the normal side in patients with unilateral osteonecrosis of the femoral head (ONFH) and the non-collapsed femoral head side in patients with bilateral ONFH. Pre- and postoperative hip functions were evaluated using the Japanese Orthopedic Association (JOA) hip score. ACA was measured using pre- and postoperative three-dimensional computed tomography (3DCT) and described as a clock using a radar chart. The ACA of the normal group was evaluated in the same manner as that for patients who underwent CPO. The ACA before CPO was compared with the ACA after CPO, the ACA before CPO was compared with that of the normal group and the ACA after CPO was compared with that of the normal group at each location. The mean JOA hip scores improved significantly from 69 preoperatively to 88 postoperatively. The superior, posterior, and anterior ACA after CPO significantly increased and the inferior ACA decreased compared with ACA before CPO. The superior, posterior, and anterior ACA before CPO were significantly smaller than ACA in the normal group. The ACA after CPO were similar to the normal group. CPO improved the anterosuperior coverage of the femoral head but reduced its inferior coverage. The radar chart could visualize acetabulum full circumference and was useful for three-dimensional pre-postoperative evaluation. [ABSTRACT FROM AUTHOR]

Ground-based radar systems are critical for physical and dynamical characterization of near-Earth objects (NEOs) and space debris. The operational aspect and applications of radar for planetary defense and space situational/domain awareness (SSA/SDA) are similar, but there are some factors that should be taken into account for an instrument to support both areas: planetary defense is focused on asteroids and comets in heliocentric orbit with perihelion distance <1.3 au. Special attention is given to potentially hazardous objects (PHOs), which are NEOs larger than 140 m that can come within 0.05 au (∼20 lunar distances) of Earth. Radar can quickly and accurately determine NEOs' future trajectory, therefore, the sooner an object can be observed, the safer it is to assess any possible threat. Radar is also useful to help obtaining information about the objects' properties to plan for an impact mitigation mission if needed. For SSA, the focus is artificial objects orbiting Earth. This document presents the radar capabilities of the legacy Arecibo telescope, and explores synergistic future concepts for planetary defense and SSA. • The Arecibo Observatory had the most powerful planetary radar system in the world. • Arecibo supported planetary defense that focuses on near-Earth asteroids and comets. • Ground-based radars are critical for characterization of near-Earth objects. • Space Situational Awareness uses ground-based radar for space debris studies. • Synergistic use of radar system for planetary defense and debris should be explored. [ABSTRACT FROM AUTHOR]

• Evolving the Radar System Simulator into the Sensor Network Simulator. • Newly implemented Optical Performance Model was verified and validated with real data. • The SNS tool suite can be used to analyze sensor networks and their performance. The number of human-made objects orbiting the Earth is growing steadily. This trend is further accelerating during recent years due to increasing commercialization in the field of satellite operations and an increasing launch rate. Concerning the area of space surveillance and tracking (SST), this leads to higher demands with respect to object observation capabilities. In order to ensure the safe usability of the different Earth orbits for all spacecraft operators, it is of great importance to continuously observe and catalog as many of the human-made objects as possible. This is especially true for inactive and uncontrollable objects, i.e. space debris. Only by maintaining accurate catalogs of the space debris environment, involuntary collisions can be avoided and risks of losing a spacecraft kept low. While the number of space debris objects can only be expected to further increase, it is not trivial to increase the number of observation sites, such as telescopes and radars, or their capabilities to counter this. One way to increase the observation capabilities without constructing new observation sites is to search for possibilities to improve the efficiency with which the existing sensors observe objects. With the goal to study and analyze single sensors, sensor networks, and how they can be used in the most efficient way, a sensor network simulator tool suite has been developed at the Institute of Space Systems of the Technical University of Braunschweig. Originally, the tool suite was developed as a radar system simulator concentrating on the different radar system configurations, such as reflector antennas or phased arrays that are used in a mono- or bistatic mode. Additionally, the corresponding radar performance model is able to simulate a tracking as well as a scanning mode. Building upon this tool suite, it is now extended to include an optical performance model and the possibility to simulate not only ground-based but also space-based sensors. Within this work, the preliminary results obtained with the newly implemented optical performance model are shown. Using the enhanced version of this sensor network simulator tool suite, thorough analyses can now be made using the radar and optical performance models. Sensor networks consisting of radars and telescopes being both ground- or space-based can be studied in different configurations. Thereby, different aspects, such as observation strategies, sensor tasking, or choosing the right location and sensor to reach a certain goal can be investigated. [ABSTRACT FROM AUTHOR]

It has been shown that bistatic radars using radio telescopes as receivers can be used to increase the sensitivity of orbital debris measurements over traditional terrestrial monostatic radar. A method to calculate the lateral surface area of a bistatic radar is needed to evaluate the efficacy of a proposed bistatic radar configuration for orbital debris measurements. For over three decades, models of the orbital debris (OD) environment in low Earth orbit (LEO) have been developed to assess the risk posed by OD to spacecraft. While terrestrial radar measures debris 3 mm and larger and in situ measurements provide data for debris smaller than 1 mm, no good data sources exist for debris between 1 mm and 3 mm in size. This results in large variations between competing OD models. It also happens to be the size regime which poses the highest mission-ending risk to spacecraft. It is, therefore, of interest to investigate potential new data sources for this under-sampled size regime. There are many radars and radio telescopes that could be combined to create sensitive bistatic radars that could potentially bridge the size gap. In addition to sensitivity, it is necessary to predict the expected count rate of a candidate sensor to evaluate its performance. NASA's Orbital Debris Engineering Model (ORDEM) can be used to predict the flux of debris passing through the line of sight of a radar or telescope. This flux is related to a count rate through the calculation of the lateral surface area of the sensor. While this can be done easily for monostatic radars, a method for calculating the lateral surface area of a bistatic radar is needed. This new method of calculation has been developed and is described. The new method maps the radar beam overlap in 3D space, calculating the area of the complex surface formed by the gain product of the two antennas. Comparisons of the monostatic and new bistatic lateral surface area calculation methods for the monostatic case are presented. Results of a sample lateral surface area calculation for a bistatic radar observation configuration currently employed by NASA are shown. Finally, a guide for total error as a function of baseline and target altitude is established. [ABSTRACT FROM AUTHOR]

The construction of the distribution of the flux density of meteor bodies over the celestial sphere is necessary for solving problems of meteor astronomy and others. To construct such distributions, experimental data on the coordinates of meteor radiants are needed. Meteor radars provide determination of the coordinates of the radiant in the presence of one transmitter and three spaced receivers. In this research, we are talking about ground-based meteor observations of the number of meteors using single-station meteor back-skatter radars as simpler than measurements of meteor radiants. In the 1950–80s in Kharkiv (Ukraine), active meteor radar research was carried out, both simple single-station and complex with remote points. The authors in the 1980s were participants in the meteor international program GLOBMET (Kashcheev, 1982; Roper, 1990). At that time, they modified an algorithm for calculating the flux density of meteor bodies over the heliocentric celestial sphere by number, range and velocity for radar observations with using single-station meteor backscatter. An algorithm was developed for dividing the celestial sphere into regions with a combination of "celestial" and "antenna" regions with a binding of a meteor to the antenna region in radar observations with a narrowly directed antenna without goniometr. This algorithm was applied to specific equipment for measuring the number of meteors by the Kharkiv Meteor Automated Radar System (MARS), 31.1 MHz. The correctness of the algorithm was confirmed by constructing the density distribution of the incident flux over the celestial sphere based on measurements in October-December 1989. The distributions are constructed using two methods for approximating the amplitude-time characteristics of signals. The results represent the experience of past years, which may be of interest as a scientific and technical solution. [ABSTRACT FROM AUTHOR]

This paper proposes a new dual-band difference (DBD) method to retrieve total electron content (TEC) in Martian ionosphere with the dual-band echoes of the Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS). It establishes the relationship between the group delay difference of two-band echoes and the plasmas frequency. Then the Martian ionospheric parameters are solved with this equation. Then the TEC is calculated by integrating the vertical distribution model of Mars electron density. This method is used to calculate the TEC of the typical ionosphere in the southern hemisphere of Mars, and the comparison with previous results validates this method. The experiments prove that this method can not only calculate the TEC of dayside and nightside in different periods, but also effectively eliminate the influence of ionospheric dispersion on radar echoes. Moreover, the time variation characteristics of the ionosphere are analyzed. According to the characteristics of this algorithm, the error sources are analyzed. By calculating the influence of different parameters on the results, it is proved that the maximum error of the algorithm is less than 0.1 TECU. [ABSTRACT FROM AUTHOR]

• Ratios of E-CHAIM model-to-RISR radar measured electron density are close to one at heights near F2 peak. • On average, E-CHAIM underestimates electron density at ionospheric topside and bottomside by ∼ 20 % • E-CHAIM underestimations are strongest in summer and equinoctial nighttime at bottomside and in autumn nighttime at topside. In this study, predictions of the E-CHAIM ionospheric model are compared with measurements by the incoherent scatter radars RISR at Resolute Bay, Canada, in the northern polar cap. Reasonable coverage was available for all seasons except winter for which no conclusions were drawn. It is shown that ratios of the model-to measured electron densities are close to unity in the central part of the F layer, around its peak. This is particularly evident for summer daytime. Distributions of the ratios are wider for other seasons indicating larger number of cases when the model underestimates or overestimates. E-CHAIM underestimates the electron density at ionospheric topside and bottomside by ∼ 10–20 %. At the bottomside, the underestimations are strongest in summer and equinoctial nighttime. At the topside, the underestimations are strongest in autumn nighttime. Model overestimations are noticeable in the middle part of the F layer during dawn hours in autumn. Overall, the model tends to not predict highest-observed peak electron densities and the largest-observed heights of the peak. [ABSTRACT FROM AUTHOR]

This paper presents an approach to ensuring the safety of a landing module on a threat during its splashdown in the World Ocean. We propose mathematical methods and software to predict the main hydrophysical disturbances from underwater vehicles, which are necessary to estimate artificial anomalies on the sea surface. • Detection of underwater objects ensures safety of the spacecraft splashdown. • Underwater object creates identifiable hydrophysical anomalies. • Computer technologies can predict hydrophysical anomalies. • Analysis of radar images of anomalies allows to detect an underwater object. [ABSTRACT FROM AUTHOR]

• Finds all efficient routes of an UAV considering distance and threat objectives. • The UAV can move to any point in the continuous space. • Characterizes efficient trajectories between target pairs by a fitted curve. • Outperforms discretized case in solution quality and computational effort. We consider the route planning problem of an unmanned air vehicle (UAV) in a continuous space that is monitored by radars. The UAV visits multiple targets and returns to the base. The routes are constructed considering the total distance traveled and the total radar detection threat objectives. The UAV is capable of moving to any point in the terrain. This leads to infinitely many efficient trajectories between target pairs and infinitely many efficient routes to visit all targets. We use a two stage approach in solving the complex problem of finding all efficient routes. In the first stage, we structure the nondominated frontiers of the efficient trajectories between all target pairs. For this, we first identify properties shared by efficient trajectories between target pairs that are protected by a radar. This helps to structure the nondominated frontier between any target pair by identifying at most four specific efficient trajectories. We develop a search-based algorithm that finds these efficient trajectories effectively. For the second stage, we develop a mixed integer nonlinear program that exploits the structured nondominated frontiers between target pairs to construct the efficient routes. We compare the nondominated front we generate in the continuous space with its counterpart in a terrain discretized with three different grid fidelities. The continuous space representation outperforms all discrete representations in terms of solution quality and computational times. [ABSTRACT FROM AUTHOR]

• A review of track detection algorithms across different research fields. • Technical description of the initiation, maintenance and termination of a radar track in the BIRALES radar. • Presentation of a new track detection strategy that is used for the detection of orbital debris using a bi-static continuous-wave radar. • Performance evaluation of this new track detection method on synthetic data. The world's economy has become heavily dependent on the services provided by satellites. With the exponential increase in satellite launches, the population of defunct or inactive hardware in space has grown substantially. This is especially true in sensitive orbits such as the Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) regimes. These objects, collectively known as orbital debris, can reach speeds of up to 28 000km h−1 in LEO. At these orbital speeds, even the smallest of objects can pose a considerable threat to operational satellites or astronauts. This makes the monitoring, and detection, of these objects of the utmost importance. This work describes the latest detection strategy used in one of Europe's largest Space Situational Awareness (SSA) installation; the BIstatic RAdar for LEo Survey (BIRALES) space debris radar. We present a novel bottom-up approach that makes use of single-linkage clustering to identify faint radar streaks in spectrogram data. Tests on synthetic data have shown that the detection strategy presented in this study obtains a higher detection rate when it is compared against existing methods. Unlike other approaches, this detection strategy, using the Multi-beam streak detection strategy (MSDS) algorithm, was still able to recall 90% of the track information at an Signal-to-Noise Ratio (SNR) of 2dB. [ABSTRACT FROM AUTHOR]

We describe the use of radar beam-park experiments to characterize the space debris resulting from a recent fragmentation event, the deliberate demolition of the defunct Kosmos-1408 satellite. We identify the Kosmos-1408 fragments and present distribution of measurement parameters as well as proxy orbit parameters. We present and apply a novel technique to estimate the size of objects by matching the signal to noise ratio of the detection to the radiation pattern of the radar. With this method we estimate the size distribution of the debris cloud. We also demonstrate how a pair of beam-park observations can be used to perform a crude, yet seemingly reliable, initial orbit determination. Finally, we present followup observations ∼ 5 months after the fragmentation that show a still compact cloud of debris. • The deliberate destruction of the Kosmos-1408 satellite has generated an appreciable cloud of space debris. • Ground-based radars in beam-park mode can be used to observe and characterize the debris cloud. • We have used these observations to estimate size distributions of the debris cloud. • Orbit information for objects can, in some cases, be obtained or updated using these kinds of observations. [ABSTRACT FROM AUTHOR]

For the physical model testing of wave energy converters (WECs) in the wave basin, it is necessary to test the models in a small number of sea states. Previously, the H – T binning method was widely used to determine the sea states that are representative of an ocean area. However, it omitted much useful information such as the wave directionality. In this paper, a novel method, the K -means clustering technique is used in combination with High Frequency (HF) radar measured data from Wave Hub, UK. The results show that K -means clustering method better preserves the characteristics of the ocean area than the binning method. Furthermore, the impact of different regrouping methods on assessing the annual energy output of the model is investigated, by applying the K -means clustering method to a 1:25 two-body hinged raft WEC. It is found that although non-linear performance can be clearly observed in the model both physically and numerically. Due to the fact that most sea states from Wave Hub are out of the non-linearity range of the model, the non-linear effect on the overall performance of the WEC model in this ocean area is limited. It allows the annual energy output to be accurately predicted by using only a small number of representative sea states (defined as K) ≤15, based on K -means clustering method. • K -means method selected representative sea states tested on a physical WEC model. • K -means method is effective in selecting the sea states for WEC model testing. • Representative sea states can obtain accurate annual energy output estimation. • Non-linearity of WEC tested had limited influence on annual energy output estimation. [ABSTRACT FROM AUTHOR]

This study presents the analysis of planetary waves (PWs) using daily mean wind velocities for four years (August 2013 to July 2017) of continuous measurements using MF radar over the low latitude Indian region Kolhapur (16.8° N; 74.2° E). The MF radar at Kolhapur was upgraded in 2013. These are the first results of PWs after the upgradation of MF radar. The seasonal and intra-seasonal variabilities of East-West (EW) traveling PWs in the MLT region have been studied. In the present work, the data was analyzed to study the waves with various periodicities (e.g. 3–4, 5–8, 15–17, and 30–60 days). The 3.5 day [Ultra-Fast Kelvin (UFK)] wave shows semiannual variability with burst like wave activity observed during the summer months and December solstice. In addition, it is observed to be stronger in the spring equinoctial period. A strong semiannual oscillation (SAO) has been observed in a 6.5-day wave with peaks near the equinoxes. Similar to SAO over the low latitude MLT region, the wave activity is stronger in April/May than in September/October. The 6.5-day waves are observed to be stronger when the background mean wind is westward. From the analysis, it has been seen that the period before and after the equinoctial period is favorable for the 6.5-day wave propagation. The 16-day wave has no significant seasonal dependence; instead, the waves spread to almost all seasons. The Madden-Julian Oscillations (MJOs) have been observed to be propagating with an average wind speed of ∼ 5 m/s when the background mean wind is eastward. The occurrence of MJO is observed during the summer and winter months. These results are the first of their kind in two aspects: first, they show the PWs with enhanced altitude coverage covering up to 110 km, and second, they show the PWs not contaminated due to equatorial electro jet influence. [ABSTRACT FROM AUTHOR]

Ground-based radar interferometry offers significant capabilities for the observation of engineering structures and natural objects displacements. The quality of the recorded displacement is significantly influenced by the intensity of the reflected radar signal. In order to determine the actual accuracy of measurement performed in the field, two comparative experiments were carried out. In both cases, referential values were specified using precise instruments: a laser interferometer and a precise total station. This way, the error value equal to 0.1–0.2 mm declared by the manufacturer was confirmed in the field conditions. Furthermore, the relationship between SNR (signal-to-noise ratio) parameter and the actual measurement accuracy was analysed based on the acquired results. Due to the different ways of expressing the parameter, i.e. thermal and estimated SNR values, specific for the applied radar system, both of them were analysed. Finally, the model which allows determining the actual accuracy of displacement measurement in the field was proposed. It includes the SNR value and the distance to the object, so the accuracy can be reliably estimated upon these basic parameters without the need for additional measurement techniques. [ABSTRACT FROM AUTHOR]

Insects are the most diverse group of animals on Earth, but their small size and high diversity have always made them challenging to study. Recent technological advances have the potential to revolutionise insect ecology and monitoring. We describe the state of the art of four technologies (computer vision, acoustic monitoring, radar, and molecular methods), and assess their advantages, current limitations, and future potential. We discuss how these technologies can adhere to modern standards of data curation and transparency, their implications for citizen science, and their potential for integration among different monitoring programmes and technologies. We argue that they provide unprecedented possibilities for insect ecology and monitoring, but it will be important to foster international standards via collaboration. Technological developments are opening new possibilities for biodiversity monitoring, but – especially for insects – they come with their own unique set of limitations. Due to the vast diversity of insects, of which at least 80% remain undescribed, traditional monitoring is unable to provide even basic knowledge of the state of most insect species in most places. We appraise four emerging tools and technologies (computer vision, acoustic monitoring, radar, and molecular methods) that provide unprecedented opportunities for insect ecology. These technologies can enhance spatial, temporal, and taxonomic coverage of monitoring, but none can monitor all insects at all scales, and each comes with a set of limitations. Technological integration, open data, and international standards are needed to harness the full potential of novel technologies for insect monitoring. [ABSTRACT FROM AUTHOR]

This study evaluated feasibility and patient outcomes for targeted axillary lymph node (LN) dissection (TAD) with SAVI SCOUT® ultrasound-guided radar reflector localization (RRL). In this IRB-approved retrospective study, 800 consecutive patients who underwent ultrasound-guided RRL between November 2017 and June 2020 were reviewed. Of these patients, those with axillary LN RRL were included in this study. Reports in the electronic medical record were reviewed to determine RRL placement, retrieval, and surgical outcomes. A total of 147 patients met inclusion criteria. Of these, axillary RRL was performed for biopsy-proven metastatic disease in 134 and inconclusive or benign biopsy in 13. RRL was successful in 146/151 lymph nodes (97%). Two patients had placement >10 mm from target and 3 had no post-placement signal. In all 5, the targets were successfully retrieved at surgery. Specimen radiographs were performed in 135 cases and confirmed the intended target in all 135 (100%). In 109 patients who underwent TAD + sentinel lymph node biopsy (SLNB), the RRL LN and the SLN(s) were different in 18 (17%). In 3 of these, the RRL LN was the only malignant LN (3%). In the 105 patients who underwent neoadjuvant chemotherapy, 43% (45/105) achieved nodal pCR and 85% (89/105) had <3 metastatic lymph nodes at surgery. Ultrasound-guided RRL of axillary LNs is a feasible approach to facilitate TAD with high placement and retrieval success rates. This enables TAD as an alternative to complete axillary LN dissection (cALND), sparing some patients with low nodal tumor burden from cALND. • US-guided SAVI SCOUT® radar reflector localization of axillary lymph nodes is highly successful (97% initial placement success rate, 100% surgery retrieval success rate) • This facilitates targeted axillary dissection + sentinel lymph node biopsy in patients with high likelihood of achieving low nodal burden • For ER/PR+ patients with only 1 suspicious lymph node on initial imaging, 95% had low nodal burden after neoadjuvant chemotherapy Precis • US-guided SAVI SCOUT® radar reflector localization of axillary lymph nodes is highly successful and facilitates targeted axillary dissection in patients with a likelihood of low axillary nodal burden [ABSTRACT FROM AUTHOR]

Based on a variety of observation instruments, we have comprehensively analysed the rare topside fossil plumes after sunrise during the recovery phase of the 27–29 May 2017 magnetic storm over Sanya. The results showed that the irregularities leading to these topside plumes on Sanya Very High Frequency (VHF) radar maps were not freshly generated after sunrise, but were able to survive at even ∼02:30UT (∼09:48LT). Different from the fresh equatorial plasma bubbles (EPBs) near sunrise, the | V d | of these plumes was very small and the zonal drift was also unnoticeable. Although a plasma depletion could be observed by Swarm A satellite near Sanya, it was too small and no ionospheric scintillation or TEC fast fluctuation was caused by it. Since the simultaneous disturbances were found under the F peak over Sanya and the corresponding plumes at Fuke appeared later than those at Sanya by ∼40 min, it was inferred that the irregularities leading to these topside plumes were generated somewhere to the south of Sanya, and then grew and reached higher altitudes and extended to higher latitudes along the geomagnetic field lines. Combining the theory of disturbance electric field during storm, it was inferred that the eastward overshielding penetration electric field as well as the uplift of F layer supported the formation and sustainment of the irregularities leading to the topside plumes. [ABSTRACT FROM AUTHOR]

• This work attempts to make an overview of the RA schemes for target tracking. • The modeling methods and solution techniques for RA in RSN are reviewed. • The challenges and promising research directions on RA are discussed. Traditional networked radar fusion technology adopts an open-loop signal processing manner, in which multiple nodes independently detect or track target first, and then send their raw data or processed measurements to the fusion center for target state estimation. In such a working manner, each radar sensor operates within predetermined rules, adopts fixed transmit and receiving mode for changeable target tracking environment, and thus will definitely cause an insufficient use of its limited resource. Resource allocation (RA) has emerged as a promising technology to exploit the limited radar resource in a more efficient way by allocating the available resource parameters w.r.t. multiple nodes collaboratively in view of the fused target tracking performance. The goal of this paper is to provide a brief overview of the RA methods for fused target tracking in radar sensor network. We mainly investigate the existing RA works and divide them into two types, namely tracking quality constrained RA type and performance driven RA type. Solution techniques for both types appeared in the literatures are also summarized. Finally, some potential future research directions in this field are discussed. [ABSTRACT FROM AUTHOR]

A recent paper (Mhaskar (2020)) introduces a straightforward and simple kernel based approximation for manifold learning that does not require the knowledge of anything about the manifold, except for its dimension. In this paper, we examine how the pointwise error in approximation using least squares optimization based on similarly localized kernels depends upon the data characteristics and deteriorates as one goes away from the training data. The theory is presented with an abstract localized kernel, which can utilize any prior knowledge about the data being located on an unknown sub-manifold of a known manifold. We demonstrate the performance of our approach using a publicly available micro-Doppler data set, and investigate the use of different preprocessing measures, kernels, and manifold dimensions. Specifically, it is shown that the localized kernel introduced in the above mentioned paper when used with PCA components leads to a near-competitive performance to deep neural networks, and offers significant improvements in training speed and memory requirements. To demonstrate the fact that our methods are agnostic to the domain knowledge, we examine the classification problem in a simple video data set. • We examine the pointwise error in approximation using least squares optimization based on the kernel presented in Mhaskar (2020). • The approximation error depends upon the data characteristics and deteriorates as one goes away from the training data. • The theory is presented with an abstract localized kernel, which can utilize any prior knowledge about the data being located on an unknown sub-manifold of a known manifold. • We demonstrate the performance of this kernel using a publicly available micro-Doppler data set, investigating the use of different preprocessing measures, kernels, and manifold dimension. • It is shown that the proposed method offers nearcompetitive performance to deep neural networks and significant improvements to speed and accuracy. [ABSTRACT FROM AUTHOR]

In this work, wave measurements from a Radac wave radar installed on the TetraSpar Demonstrator floating wind turbine are analysed and compared to measurements from an adjacent Fugro Midi wave buoy and MET Norway model forecasts. The wave radar is found to agree well with the wave buoy and model forecasts in most cases, giving confidence to use the data for engineering calculations and design. Some discrepancy in the measured spreading is observed, but analysis of raw wave data indicates that the wave radar measures similar spreading values to the pitch, roll and heave wave buoy. Wave diffraction by the local structure is found to have a small impact on the high-frequency tail of the measured spectra, but has minimal impact on the measured bulk wave parameters. Measurements of spurious large wave crest events appear to be associated with sea-spray from the centre column for a particular wave direction. Quality control procedures implemented in the wave radar software remove these spurious large crest events. • Wave radar measurements agree well with Midi buoy measurements and model forecasts. • Wave radar directional spreading measurements are similar to those from a Midi buoy. • The effect of diffraction by the floater structure is small but measurable. • Spurious crest measurements are observed and are likely associated with sea spray. • The wave radar should be positioned carefully to avoid the effect of sea spray. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of mainlobe deceptive jammer suppression via joint transmit–receive design in a multiple-input multiple-output (MIMO) radar. At the design stage, a discrete element-pulse coding (DEPC) phase is implemented in both the slow-time pulses and transmit array antennas. After decoding and compensation of the delayed pulses, the true and false targets can be identified in the joint transmit–receive (JTR) spatial frequency domain. Furthermore, to eliminate the false targets, a data-dependent beamforming technique is adopted, where an optimization problem is constructed to maximize the output signal-to-interference-plus-noise ratio (SINR) by optimizing the DEPC coefficients and the weight vector of the receive filter in an alternating way. Specifically, two methods, including the Single Jammer Suppression (SJS)-Alternating Direction Method of Multipliers (ADMM) and Multiple Jammers Suppression (MJS)-Gradient Descent (GD) methods are developed for the cases of a single jammer and multiple jammers, respectively. A series of numerical results are utilized to verify the effectiveness of the proposed methods for mainlobe deceptive jammer suppression. • The DEPC-MIMO scheme is proposed by discretizing element pulse coding coefficients. • The true and false targets are distinguished in the transmit–receive spatial domain. • The false targets are suppressed by optimizing DEPC coefficients and weight vector. [ABSTRACT FROM AUTHOR]

This paper focuses on the design of a frequency modulated continuous wave (FMCW) dual-functional radar-communication (DFRC) system with low-loss radar detection performance, aiming at achieving a balance among communication rate, symbol error rate (SER), and out-of-band leakage. For what the communication functionality concerns, the constrained frequency hopping (C–FH) sequence mapping and up/down chirp are used to embed data, limiting the out-of-band leakage. We provide explicit rules for traversal-FH sequence to adjust the number of configurable frequency points within each chip, and limit the SER at the receiver. For the radar signal processing, after coherent processing and sampling, we proceed time-domain extension and range-bin phase compensation (TE-RBPC) according to the FH value, achieving the same range profile as an unmodulated (FMCW) without any influence from the FH sequences. The simulation results show that the proposed C–FH-chirp waveform reduces the out-of-band power leakage by 10 dB if compared with a phase shift keying scheme, and provides a 5 dB improvement in the signal noise ratio under the same SER if compared with an unconstrained FH-chirp scheme. Moreover, by comparing it with a scheme without compensation, the sidelobe amplitude of radar range profile in TE-RBPC scheme is reduced by about 39 dB. [ABSTRACT FROM AUTHOR]

Herein, we developed a convenient and versatile dual-mode electrochemiluminescence (ECL) and photoelectrochemistry (PEC) sensing radar for the detection of Prostate-specific antigen (PSA), which has important implications for detection of low-abundance disease-associated proteins. Cerium-based metal-organic framework (Ce-MOFs) were firstly modified on the electrode, showing well ECL and PEC property. In particular, a unique multifunctional Au@CdS quantum dots (QDs) probe loaded numerous QDs and antibody was fabricated, not only displaying strong ECL and PEC signals, but also having specific recognition to PSA. After the signal probe was linked to the electrode by immune reaction, much amplified signals of ECL and PEC were generated for double-mode detection of PSA. Therefore, this work proposed a multifunctional Au@CdS QDs signal probe with excellent ECL and PEC performance, and developed an ultrasensitive photoelectric biosensing platform for dual-mode detection, which provides an effective method for health monitoring of cancer patients. A convenient and versatile dual-mode electrochemiluminescence and photoelectrochemistry sensing radar was developed for the detection of Prostate-specific antigen, which has important implications for detection of low-abundance disease-associated proteins. [Display omitted] • A versatile ECL and PEC sensor based on CdS QDs-sensitized Ce-MOF was designed for dual detection of PSA. • This work opened a novel multifunctional CdS QDs-Ce MOF material with unique optical-electrical characteristics. • A large number of CdS QDs loaded to Au NPs generated amplified signals for sensitive detection of PSA. • This unique double-mode sensing strategy can improve detection precision and solve false positive problem. [ABSTRACT FROM AUTHOR]

The performance of constant false alarm rate (CFAR) detectors is often severely degraded in clutter edge and under multiple target interference. CFAR detection in the above environments often uses generalised likelihood ratio method or mean ratio method to find out the clutter edge demarcation line and suppress the sharp increase of false alarm rate, or remove the interference and modify the threshold factor to suppress the interference and improve the detection performance, but this sacrifices the detection gain from the number of clutter samples. In this paper, the feature information is fused to construct feature vectors, and the edge location is judged by the modulus of the cross product of the feature vector pair (MCPFVP), this edge demarcation line detection method fusing with features can be implemented without the need of clutter statistical distribution information. In addition, this paper reconstructs the sea clutter masked by multiple target interference by fusing the sea clutter amplitude correlation information, and these reconstructed sea clutter samples are used for power estimation together with the unmasked sea clutter without changing the threshold factor. This method can not only suppress the target masking effect of multiple target interference as the censoring type CFAR detector, but also maintain the detection gain from the number of clutter samples, which is not possible with the traditional censoring type CFAR detector. In addition, the relative weighted ratio summation (RWRS) is proposed to detect the multiple target interference, which takes into account the asymmetry of the shape of the statistical distribution. Both simulated and real sea clutter data are used to validate the above methods. The measured data are obtained from radar data collected at Yantai Yangma Island, China, Darmouth, Canada and Grimsby, Canada. (The latter two datasets are collected by the IPIX radar - Ice Multiparameter Imaging X-Band Radar). [ABSTRACT FROM AUTHOR]

The rapid development of detection technology, the technology with radar infrared compatible stealth function has become one of the important ways to improve the survivability of weapons and equipment. However, the two stealth mechanisms of radar stealth and infrared stealth are mutually exclusive. In this work, a multilayer radar-infrared compatible stealth metamaterial is presented based on SiO 2 fiber reinforced aerogels skeleton (SFRAS). The prepared samples with bird 's nest microstructure showed good compressive strength (1.73–2.52 MPa) and low density (0.22–0.27 g/cm3), achieving lightweight. Moreover, the metamaterial exhibits excellent electromagnetic absorption performance, effective absorbing broadband (13 GHz), and ultra-wideband absorption of electromagnetic waves is achieved. Nanoporous structure and low thermal conductivity (0.03426–0.05011 W/ (m K)) successfully reduce the surface thermal radiation, indicating that it is a potential material for achieving infrared stealth. The new technology provides a new approach to the research of the radar-infrared compatible stealth structure. • A multilayer radar-infrared compatible stealth metamaterial is synthesized based on the traditional papermaking process. • The effect of fiber contents on both mechanical and thermal conductivity was studied. • The absorbing properties of metamaterial are studied, and the relative bandwidth reaches139.8 %. • The structure was observed to have a unique three-dimensional bird's nest-like structure by using SEM. [ABSTRACT FROM AUTHOR]

This study presents low phase angle 0 ° – 5 ° measurements of polarimetric properties of icy planetary regolith analog materials acquired using the custom-built Multi-Axis- Goniometer-Instrument (MAGI). We present same sense (S C) , and opposite sense (O C) backscatter circular polarization coefficients, circular polarization ratio (C P R) , and degree linear polarization (D L P) of spherical latex (non-dye) beads of varying sizes and volume concentrations (v/v) in aqueous solutions (λ = 0. 8 μ m) in water. We also present measurements of alumina powder in air at λ = 1. 064 μ m. Measurements showed that at a low incidence angle (i = 0 °) , backscatter is dominated by surface specular single-bounce scattering, that hides other scattering processes. At high (i = 15 °) incidence angle, surface single-bounce surface scattering becomes negligible, allowing for the detection of diffuse, dihedral (multiple bounces) scattering. We find that classical Mie alumina particles (2. 1 μ m , 4. 0 μ m) enhance subsurface scattering due to a larger void space relative to larger Mie particles (30 μ m) , that cause the radar signal to scatter forward off small imperfections, maintaining the polarization properties of the signal and generating high > 1 C P R. Latex beads, representing impurities, demonstrate the impact of isotropic and anisotropic scattering on radar signatures. This study also found that the scattering medium's anisotropy correlates to the size of the beads, while the void space of the medium inversely correlates with the bead size and the volume concentration (v/v) of the beads. Rayleigh beads, due to isotropic scattering from the reduced scattering cross-section and higher transparency relative to larger impurities, generate subsurface single bounce scattering from the sample platform, producing O C ≫ S C and a low (< 0. 5) C P R across all v/v. Rayleigh impurities in transparent water-ice simulate single bounce scattering from underlying layers. Conversely, classical and large Mie beads generate anisotropic scattering that intensifies scattering in the forward direction with high C P R , inversely proportional to the volume concentration. This study aids in interpreting radar observations of icy bodies in the solar system, providing insights into the interplay between radar waves and icy regolith compositions. • Multi-Axis-Goniometer-Instrument for measuring polarization at low phase angles. • Polarization properties of latex beads in aqueous solution and alumina powder in air. • Alumina particles of different sizes affect subsurface scattering due to void space. • Latex beads affect polarization through isotropic, and anisotropic scattering. • The study provides insights for interpreting radar observations of icy bodies. [ABSTRACT FROM AUTHOR]

The assessment of morphological mapping capacity of X-band radars is performed by comparing radar-derived shoreline estimates with in-situ data measured from DGPS-RTK surveys in Cala Millor beach (October 22–24, 2018). Radar estimates are obtained by applying an automatic method based on digital image processing, threshold segmentation and first-order derivative filters on X-Band radar variance images. The study site is covered by the endemic Posidonia oceanica seagrass meadow at the seabed. It represents a challenge on the estimation of local shoreline. Results reveal that X-band radar estimate the shoreline location with a mean bias of 4.66 m, a relative error of 2.95% and a RMSE of 14.07 m. Also, the beach morphology is assessed by the identification of surrounding rocky outcrops and a submerged sandbar. Since the obtained radar estimation errors are comparable with the reported by previous studies but using video-cameras, results reveal a potential complementary use of both marine radars and optical cameras to provide higher-resolution and more accurate shoreline measurements in a broader area. • An automated shoreline detection method for nearshore areas using X-Band marine radar is proposed. • We combine threshold segmentation, edge detection, digital processing and statistical properties of the surrounding. • Shoreline location is detected with a mean bias of 4.66 m, a relative error of 2.95% and a RMSE of 14.07 m. • We suggest the complementary use of marine radars and optical camera for shoreline measurements. [ABSTRACT FROM AUTHOR]

A composite hybrid structure reinforced by cobalt oxide (Co3O4), copper-copper oxide (Cu–Cu2O), and barium hexaferrite (BaFe12O19) was investigated. Chemical reduction and sol-gel were used for synthesizing reinforcement materials. Polyester resin was used as a matrix material. Synthesized powders were analyzed and characterized by using various characterization techniques such as differential thermal analysis, X-ray diffractions (XRD), vibrating sample magnetometer (VSM), scanning electron microscopy (SEM), and particle size analysis. Three-Layer RAM structures were prepared layer by layer, and the concentration of the filler powders was the same in each layer. RAM structures were investigated using a vector network analyzer (VNA). Based on the radar absorbing analysis, the most effective absorption is possessed by sample RA5 50 wt%, which consists of two layers of cobalt oxide and one layer of copper-copper oxide. The maximum value of the reflection loss was- 45 dB at a frequency of 10.25 GHz. • A composite hybrid structure reinforced with Co3O4, Cu–Cu2O and BaFe12O19 was produced by and sol-gel and chemical reduction. • Three-layer RAM structures were prepared with different additives. • Radar absorbing structures were investigated using a vector network analyzer (VNA). • Most effective absorption achieved by sample consisting of two layers of cobalt oxide and one layer of copper-copper oxide. • The maximum value of reflection loss was - 45 dB at a frequency of 10.25 GHz. [ABSTRACT FROM AUTHOR]

In this study, a novel RAM utilizing Fe 3 O 4 , ZnO, polyaniline (PANI), and reduced graphene oxide (rGO) in the form of nanohybrid is invented, namely Fe 3 O 4 /ZnO/PANI/rGO nanohybrid. In this study, the effects of the rGO fraction in Fe 3 O 4 /ZnO/PANI/rGO composition on the radar absorbing performance were investigated. Meanwhile, exploring the quality of the nanohybrid sample, such as the crystal structure, functional groups, morphology, magnetic properties, and reflection loss was also examined carefully. It shows that two crystalline phases of Fe 3 O 4 and ZnO, as well as amorphous structures of PANI and rGO are formed independently, indicating successful nanohybrid formation. In this case, PANI functioned as a binder for Fe 3 O 4 and ZnO, and thus, it could infiltrate the pores of rGO. Fe 3 O 4 /ZnO/PANI/rGO nanohybrid possesses superparamagnetic properties with decreasing saturation magnetization as rGO composition increases. Nevertheless, rGO enhanced the radar absorption performance with a maximum reflection loss of −8.57 dB at 11.10 GHz. In this present research, the synergy of combination between the magnetic and dielectric losses in the Fe 3 O 4 /ZnO/PANI/rGO nanohybrid is discussed together with plausible strategies to obtain highly efficient RAM. • The radar technology is one of important aspect in stealth technology. • One of the most popular magnetic materials applied as radar technology is Fe 3 O 4. • A novel Fe 3 O 4 /ZnO/PANI/rGO nanohybrid for radar absorbing application was successfully synthesized using the regular mixing method. • Radar absorbing material (RAM) must have several features, including high permittivity and permeability with high magnetic saturation. • rGO enhanced the radar absorption performance with a maximum reflection loss of −8.57 dB at 11.10 GHz. [ABSTRACT FROM AUTHOR]

This paper describes a ultra-wideband (UWB) three-stage cascaded high gain amplifier with low group delay variation for phased-array radar system. The shunt inductor at the input not only provides an electrostatic discharge (ESD) path to ground, but also introduces a new notch for S 11 , thus extending the matching bandwidth. Staggered tuning of load impedance peaks at each stage facilitates a balance between flat gain and low group delay variation. The output stage further enhances the overall gain while reinforcing bandwidth and stability through resistive feedback, and employs an adaptive bias circuit for linearity improvement. Implemented in SMIC 40-nm CMOS technology, the proposed amplifier achieves good input impedance matching, flat gain and low group delay variation of ±73.5 ps over 4.7–16 GHz. The whole power consumption is 198.3 mW and the output 1 dB compression point (OP 1dB) is greater than 9 dBm. After careful design, the chip size is 0.64 mm2. [ABSTRACT FROM AUTHOR]

Airspace surveillance is a significant issue for many countries to control and manage their airspace. The number of radars used and their coverage rate are the main issues to consider in this case. Therefore, this paper addresses the problem of finding the best radar locations to obtain the highest coverage rate with the least possible number of radars in a certain region. The radar placement problem is considered as a multi-objective optimization problem with two objectives: the number of radars and the coverage rate. To perfectly solve this optimization problem, a set of multi-objective meta-heuristic approaches based on simulated annealing, memory-based steady-state genetic algorithm, a decomposition-based multi-objective algorithm with differential evolution, and non-dominated sorting genetic algorithm (NSGA-II) are utilized. Algorithms are tested on a dataset created using DTED-1 map elevation data for two different selected regions. Based on the results, the NSGA-II algorithm achieves the best results and the highest coverage ratios among the tested algorithms. Two improved versions of the NSGA-II algorithm are also proposed to enhance its performance and make it more suitable for solving this optimization problem. The experimental results show that a coverage rate of 98% could be achieved with a small number of radars, and by increasing the number of radars, it exceeds 99%. • This paper solves the radar placement problem using a set of metaheuristic approaches. • The problem is considered as a multi-objective optimization problem. • Two adaptive and enhanced versions of the NSGA-II algorithm are proposed. • The results show that a coverage rate of 98% can be achieved with just a few radars. [ABSTRACT FROM AUTHOR]

The current study utilizes the operational data assimilation system of Deutscher Wetterdienst (DWD) to investigate the impacts of improved radar forward operator. First of all, it is shown that for experiments in which both conventional and radar data are assimilated and the latent heat nudging (LHN) is applied, the one with improved operator (i.e., with improved Mie-scattering scheme and accounting for beam broadening effect and etc.) exhibits neutral impacts on short-term forecasts. However, in subsequent experiments, in which conventional data are not assimilated and the LHN is switched off, the one with improved operator not just reduces representation error during data assimilation cycles but also enhances the short-term forecast skills. In addition, it is found that the subsequent experiments result in much shorter observation error correlation length scales for radar reflectivity data, indicating that the application of the LHN or assimilation of conventional data may increase the length scales. • Improved radar forward operator configurations reduce representation error but exhibit neutral impact on short-term forecasts • However, in the pure radar data assimilation experiment, improved operator configurations enhance forecast skills • The observation error statistics estimated by the Desroziers method exhibit clear dependency on the data assimilation [ABSTRACT FROM AUTHOR]

Recent studies have shown that radar temporal coherence over tropical and boreal forests undergoes a diurnal cycle as a result of a combined effect of the wind-induced motion of scatterers and of the change and displacement of water within the plant in response to the transpiration process. Within this context, the objective of this paper is to investigate, for the first time, the diurnal cycle of temporal coherence over wheat crops in relation to its development and physiological functioning throughout the agricultural season. A ground-based experiment was installed in Morocco, targeting a wheat field during the 2020 agricultural season. The radar system, essentially based on a Vector Network Analyzer (VNA) connected to 6C-band antennas installed at the top of a 20 m tower, has enabled quad-polarimetric acquisitions every 15 min. In parallel, evapotranspiration, soil moisture and meteorological variables are automatically measured in addition to above-ground biomass and vegetation water content collected during field campaigns. The results show that the temporal coherence with a 15 min baseline follows a marked diurnal cycle characterized by variable amplitude according to the phenological stage, with high values during the night, a significant morning drop to reach the lowest values in the late afternoon followed by an increase to recover the high nighttime values. The rate of the drop at dawn is shown to be related to the increase of evapotranspiration (r = 0.80 at VV polarization) when the wheat is covering the soil and the transpiration dominate the evapotranspiration process. This supports the assumption of a physiological effect related to water movement entailing a decorrelation. By contrast, the daily minimum of temporal coherence occurring in the late afternoon correlates well to the daily maximum of wind (r = 0.7). Interestingly enough, the amplitude of the diurnal cycle exhibit a marked seasonal evolution characterized by an increase of 85% from tillering to maturity in relation to the wheat development. At the early start of the season when the soil is almost bare, irrigation events impact slightly the diurnal cycle of temporal coherence. Likewise, it is shown that the presence of dew in the early morning has led to a decrease of the decorrelation rate. Temporal coherence dynamic has also been investigated for longer baselines up to 22 days. Results indicate a stronger decorrelation than what has been observed on tropical and boreal forests by previous studies with values below 0.4 for baselines above 2 days. Taken together, the results of this work demonstrate the unique potential of sub-daily C-band data for monitoring crop water status by future geostationary radar missions such as Hydroterra. • Diurnal cycles of 15-min C-band temporal coherence over wheat crops are analyzed. • The morning drop of the temporal coherence is related to the transpiration process. • Temporal coherence exhibits a marked seasonal dynamic according to phenological stages. • Irrigation events and morning dew have an impact on sub-daily temporal coherence. • Early morning hours showed potential for monitoring the vegetation physiological functioning. [ABSTRACT FROM AUTHOR]

Spatiotemporal prediction is a challenging topic because of uncertainty. Existing works attempt to design complicated systems to learn short-term and long-term dynamics. However, these models suffer from heavy computational burden on spatiotemporal data, especially for high-resolution frames. To reduce resource dependence, we propose FastNet, a novel and light encoder–decoder for predictive learning. We stack four ConvLSTM (Convolutional Long Short-Term Memory) based layers to construct a hierarchical framework. Based on this architecture, the feature aggregation module first aligns the temporal context, then decouples different frequency information, next gathers multi-level features and last synthesizes new feature maps alternately. We aggregate various and hierarchical features into predictions bringing two benefits: rich multi-level features and low resource usage. As for the unit blocks, depth-wise separable convolution is used to improve model efficiency and compress model size. Besides, we adopt perceptual loss as the cost function between ground truths and predictions, which helps our model to get higher similarity with true frames. In experiments, we evaluate the performances of FastNet on the MovingMNIST (Mixed National Institute of Standards and Technology) and Radar Echo datasets to verify its effectiveness. The quantitative metrics on the Radar Echo dataset show that FastNet reaches a slight increase in accuracy but up to 84% decline in computation compared with PredRNN-V2. Therefore, our FastNet achieves competitive results with lower resource usage and fewer parameters than the state-of-the-art model. [ABSTRACT FROM AUTHOR]

We present the results from investigation of spectra of polar mesospheric summer echoes (PMSE) observed with EISCAT VHF 224 MHz radar during energetic particle precipitation events in the summer of 2019. We used the sudden enhancements in electron densities derived from the VHF observations above 90 km as indicators of particle precipitation. We find that the altitude extent of the PMSE increased along with an enhancement of the strength of the pre-existing PMSE. On some occasions, PMSE suddenly appeared during particle precipitation events. After the particle precipitation subsided, the PMSE intensities continued to be stronger for a few minutes and then decreased. At the altitudes where the maximum enhancement in PMSE backscatter occurred, there is no corresponding broadening in the spectral widths. Interestingly, the most intense PMSE echoes almost always coincided with the lower values of spectral widths both during particle precipitations and other times. In some cases, the spectral widths show well separated regimes between the upper and lower parts of the PMSE layers and this also happened irrespective of particle precipitation. The frequency Doppler shifts showed alternating upward and downward motions without much difference before and after the particle precipitation. Based on these observations, we conclude that the sudden enhancement in the electron densities during particle precipitation intensifies PMSE structures that match the Bragg scale of the incident radio wave thereby enabling an enhancement in the backscatter strength. Similarly, PMSE backscattering may get initiated in the altitudes in which the structures were already present but where electron density was not sufficient before the onset of precipitation. Spectral widths and Doppler velocities does not show sudden variations with particle precipitation because they depend on the neutral dynamics. [ABSTRACT FROM AUTHOR]

Globally the land subsidence is a significant problem of the rapidly growing urban area. The factor responsible for the land subsidence caused by over-exploitation of the underground fluid such as water, petroleum, and gas respectively. In present study we present the result of detail investigation of active ground subsidance in New Delhi, National Capital Region (NCR). This area indicates a high rate of urban growth during the past decades. To analyze the land subsidence, we used multiple SAR sensor data and exploited the PS-InSAR technique. The data used for this study are Cosmo-skymed acquired between 08/06/2011 to 15/11/2017, Sentinel-1A-B (18-12-2014 to 27-11-2018), and ALOS PALSAR acquired between 19/01/2007 and 20/01/2011. These radar sensors operate in X, C, and L-band, which covers over ten years, from 2007 to 2018. The PSI results of Cosmo-skymed reveals that the Delhi NCR region has undergone an average deformation ± 15 mm/y, a maximum surface deformation observed from ALOS-PALSAR is 10 to 18 mm/y and the ground displacement observed from the SENTINAL-1A data is −2 to 16 mm/y. Groundwater level data also collected for the same period and a ground water level depletion compared with the subsidence. Monitoring land subsidence with ground-based conventional technology is time-consuming and can be carried out in a limited area due to the financial implication. PS-InSAR is an established method to detect the surface movement using the SAR sensor's time-series data. The result shows that a twenty centimeter of land subsidence is visible in some areas, validated with the collected ground evidence. The affected area is also showing resemblance to the groundwater depleting condition in those areas. This study also establish that multiple sensor data can be used to monitor the long term land subsidence. [ABSTRACT FROM AUTHOR]

Traditional clustering algorithms can be applied for the pre-sorting step of radar signal sorting. It can effectively dilute the pulse stream and prevent the dense pulse stream from interfering pulse repetition interval (PRI) extraction. However, the pre-sorting deviation will cause interference and missing pulses during the main sorting process. To solve this problem, we deploy the unmanned aerial vehicle (UAV) swarm to monitor reconnaissance areas and put forward a novel deep transfer learning based signal sorting method. The UAV swarm can collect the pulses from different time and spatial domains, and interference and missing pulses in main sorting processing can be relieved dramatically. In our model, we pre-train our model with the data collected from multiple source areas, which corresponds to different areas detected by different parts of UAV swarms. Then we fine-tune our model with the data of the target area. The experimental results prove that the signal sorting accuracy of methods based on deep transfer learning, i.e., YOLO-MobileNet, F-RCNN and cascade RCNN, are higher than that of the baseline methods. In addition, the signal sorting accuracy of traditional methods based on deep learning can be greatly improved with the help of transfer learning. • The reconnaissance architecture is constructed by UAV swarms. • Deep transfer learning is used to improve the sorting accuracy. • Experiment results verify the effectiveness of this method. [ABSTRACT FROM AUTHOR]

Continental earthquakes, especially shallow earthquakes, can cause disasters in populated areas. On 20 May 2016, a moderate magnitude earthquake (Mw 6.0) ruptured on Northern Territory of Australia. With the aim of seismic hazard assessment, coseismic and postsesmic deformation of the Petermann earthquake has been determined using ALOS-2 ascending and Sentinel-1A descending images. The coseismic deformation field suggests that the earthquake ruptured in the NNW direction with a length of about 20 km, a rake angle of 57.1° and a moment magnitude of Mw 6.06. The maximum slip of 1.31 m can be observed at the depth of 1.25 km. The small baseline subset (SBAS) InSAR was utilized to obtain the postseismic deformation from 69 Sentinel-1A images in a descending orbit. The spatiotemporal evolution of the postseismic deformation presents a gradually decaying trend, with a maximum displacement of 5.4 cm within 858 days after the mainshock. Our afterslip model suggests that the maximum slip of 0.28 m occurred at the depth of 0.25 km with a slight shift to the northwest compared to the coseismic slip. The static Coulomb failure stress (CFS) changes at various depths were calculated, indicating the consistency between high loaded stress zones and aftershock distribution. [ABSTRACT FROM AUTHOR]

The identification of individuals based on their walking patterns, also known as gait recognition, has garnered considerable interest as a biometric trait. The use of gait patterns for gender classification has emerged as a significant research domain with diverse applications across multiple fields. The present investigation centers on the classification of gender based on gait utilizing data from Ultra-wide band radar. A total of 181 participants were included in the study, and data was gathered using Ultra-wide band radar technology. This study investigates various preprocessing techniques, feature extraction methods, and dimensionality reduction approaches to efficiently process Ultra-wide band radar data. The data quality is improved through the utilization of a two-pulse canceller and discrete wavelet transform. The hybrid feature dataset is generated through the creation of gray-level co-occurrence matrices and subsequent extraction of statistical features. Principal Component Analysis is utilized for dimensionality reduction, and prediction probabilities are incorporated as features for classification optimization. The present study employs k-fold cross-validation to train and assess machine learning classifiers, Decision Tree, Random Forest, Support Vector Machine, Logistic Regression, Multi-Layer Perceptron, K-Nearest Neighbors, and Extra Tree Classifier. The Multilayer Perceptron exhibits superior performance, achieving an accuracy of 0.936. The Support Vector Machine and k-Nearest Neighbors classifiers closely trail behind, both achieving an accuracy of 0.934. This research is of the utmost importance due to its capacity to offer solutions to crucial problems in multiple domains. The findings indicate that the utilization of UWB radar data for gait-based gender classification holds promise in diverse domains, including biometrics, surveillance, and healthcare. The present study makes a valuable contribution to the progress of gender classification systems that rely on gait patterns. [ABSTRACT FROM AUTHOR]

Shallow convective systems occasionally cause heavy precipitation through active warm-rain processes, although the mechanism is not well understood. In this study, a shallow line-shaped precipitation (SLSP) system, which produced heavy rainfall in the Kanto Region, Japan, was investigated using Ka-band and X-band radars, in addition to a numerical weather prediction model. The SLSP system exhibited features similar to squall lines (SLs), such as rapid movement perpendicular to the line, but the echo-top height remained below the 0 °C level, despite the rainfall intensity reaching approximately 78 mm h−1. Therefore, the SLSP system was considered to be dominated by a shallow convective system that contained cloud droplets, raindrops and drizzle rather than a deep convective system that included ice particles. The Ka-band radar observed a low-level cloud deck spreading to the front side of the convective system, and low-level cloud subsequently entered the SLSP system. In addition, large amounts of water vapor were transported by a super typhoon came from the southwest of the Kanto Region. Cloud water supplied from the cloud deck and that condensed from the water vapor supplied by the typhoon were considered to play an important role in the heavy precipitation associated with the SLSP system through the accretion of raindrops. This study provides insights into the microphysical structure of SLSP systems as well as the precipitation processes. • A shallow line-shaped precipitation system was observed by cloud radar. • Abundant water vapor and low-level stratocumulus clouds were transported by typhoon. • Active accretion process was responsible for driving production of heavy rainfall. [ABSTRACT FROM AUTHOR]

Over the last two decades, there has been a notable increase in the use of bistatic radar configurations for remote sensing, particularly employing Signals-of-Opportunity (SoOp), such as Global Navigation Satellite System - Reflectometry (GNSS-R). Unlike the more common monostatic backward radar configuration, GNSS-R forward scattering is dominated by different mechanisms. The forward scattering measurement provides valuable insights into regions where the backscatter is minimal or dominated by the double bounce effect caused by the vegetation. The Soil Moisture Active Passive (SMAP) mission carries an L-band radiometer and a radar. However, following a radar malfunction during its commissioning, the radar was repurposed to measure GPS L2C signals. This repurposing provides a unique opportunity to compare data from both the SMAP radar and GNSS-R (SMAP-R) collected by the same platform, using the same antenna, same incident angle, and similar frequencies. The study conducted offers a comprehensive analysis, both qualitative and quantitative, of the relationship between forward scattering at full polarization, and backward scattering at three polarizations (3-polarization: HH, VV and HV). Additionally, the study includes comparisons with ancillary geophysical measurements across three distinct areas with varying environmental characteristics, including dense forests and deserts. • There is a strong correlation between polarimetric GNSS-R and L-band radar. • Polarimetric GNSS-R provides complementary sensitivity over densely vegetated regions. • The relationship between forward and backward scattering is proportional but inverse. • Radar and reflectometry measurements complement each other over distinct areas. [ABSTRACT FROM AUTHOR]