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With the increasing of on-orbit satellites, target dynamic monitoring becomes more and more important in space situation awareness applications. Currently, there are some exploratory methods monitoring attitude-stabilized targets using various high-resolution remote sensing technologies. However, it is still a big challenge to achieve dynamic estimation of spin satellite with single sensor. Inspired by the existing matching based works, this article presents a dynamic estimation method of spin satellite using single-station inverse synthetic aperture radar (ISAR) images. When the angle accumulation is set to be a constant in each ISAR imaging period, the projection change of target structures in the long-term observation sequence is described with the hidden Markov model to build the mathematic expression of target on-orbit state. In this condition, target sequential attitude can be solved with Viterbi decoding algorithm even the azimuth scaling of each image is difficulty due to target spin motion. Then, combined with the radar observation geometry, target sequential attitude parameters are substituted into a spin parameter optimization, which is solved by particle swarm optimization algorithm. In the end, target instantaneous attitude vectors and spin speed are used to express its dynamic during the observation period. Simulation experiments of a typical spin spacecraft, Tiangong-I, confirm the feasibility of the proposed algorithm, and its superiority is also investigated by comparison with the existing work. [ABSTRACT FROM AUTHOR]

Radar sounders (RSs) are gaining importance in planetary missions thanks to their unique capability of providing direct measurements of subsurface (SS) structures. To support their design and data interpretation, several electromagnetic (e.m.) simulation techniques have been developed with enhanced capabilities for emulating the RS acquisition process. However, the raw simulated radargrams obtained from e.m. simulators are difficult to interpret and analyze without a focusing operation, which results in an underestimation of the RS detection performance. While frequency methods for range and azimuth compression of real RS data are well-established, their use on simulated data is not addressed in the literature and requires major modifications. This article presents a novel method that implements azimuth compression using unfocused and focused processing on simulated raw data. The proposed method is based on an adaptation of the range-Doppler algorithm to the case of raw data generated by a coherent RS simulator. The method is demonstrated in three case studies to show the similarity between simulated and real data processing: 1) simple geometries; 2) a simulated SHAllow RADar (SHARAD) radargram compared with the real data product; and 3) a real application scenario for supporting the design of a new RS instrument. The results indicate higher fidelity of the focused simulated data with the real data product and the target structure, confirming the usefulness of the proposed approach in obtaining realistic processing of simulated radargrams. [ABSTRACT FROM AUTHOR]

Multiple radar systems represent an attractive option for target tracking because they can significantly enlarge the area coverage and improve both the probability of trajectory detection and the localization accuracy. The presence of multiple extended targets or weak targets is a challenge for multiple radar systems. Moreover, their performance may be severely deteriorated by regions characterized by a high clutter density. In this article, an algorithm for detection and tracking of multiple targets, extended or weak, based on measurements provided by multiple radars in an environment with heavily cluttered regions, is proposed. The proposed method features three stages. In the first stage, past measurements are exploited to build a spatiotemporal clutter map in each radar; a weight is then assigned to each measurement to assess its significance. In the second stage, a track-before-detect algorithm, based on a weighted 3-D Hough transform, is applied to obtain target tracklets. In the third stage, a low-complexity tracklet association method, exploiting a lion reproduction model, is applied to associate tracklets of the same target. Three experiments are presented to illustrate the effectiveness of the proposed approach. The first experiment is based on synthetic data, the second one is based on actual data from a radar network with two homogeneous air surveillance radars, and the third one is based on actual data from a radar network with four different marine surveillance radars. The results reveal that the proposed method can outperform competing approaches. [ABSTRACT FROM AUTHOR]

Spatiotemporal distribution of soil moisture is important for hydrometeorological and agricultural applications. There is growing interest in monitoring soil moisture in relation to soil- and land-based natural flood management (NFM), to understand the soil’s ability, via land-use and management changes, and to delay the arrival of flood peaks in nearby watercourses. This article monitors relative surface soil moisture (rSSM) across the Thames Valley, U.K., using Sentinel-1 data, and the Vienna University of Technology (TU-Wien) Change Detection Algorithm, with a novel exploration of monthly and annual normalization factors and spatial averaging. Two pairs of normalization factors are introduced to remove impacts from varying local incidence angles through direct and multiple regression slopes. The spatiotemporal distribution of rSSM values at various spatial resolutions (1000, 500, 250, and 100 m) is assessed. Comparisons with in situ soil moisture data from the COSMOS-UK network show that, while general temporal trends agree, the difference in effective depth of measurements, coupled with vegetation impacts during the growing season, makes comparison with soil moisture observations difficult. Temporal rSSM trends can be retrieved at spatial resolutions down to 100 m, and the rSSM RMSE was found to decrease as the spatial resolution increases. The vegetation effects upon the rSSM are further explored by comparing the two dominant land cover types: Arable and Horticulture, and Improved Grassland. It was found that, while the rSSM retrieval for these land covers was possible, and the general soil moisture trend is clear, overlying vegetation during the summer artificially increased the rSSM values. [ABSTRACT FROM AUTHOR]

Registration for multisensor or multimodal image pairs with a large degree of distortions is a fundamental task for many remote sensing applications. To achieve accurate and low-cost remote sensing image registration, we propose a multiscale framework with unsupervised learning, named MU-Net. Without costly ground truth labels, MU-Net directly learns the end-to-end mapping from the image pairs to their transformation parameters. MU-Net stacks several deep neural network (DNN) models on multiple scales to generate a coarse-to-fine registration pipeline, which prevents the backpropagation from falling into a local extremum and resists significant image distortions. We design a novel loss function paradigm based on structural similarity, which makes MU-Net suitable for various types of multimodal images. MU-Net is compared with traditional feature-based and area-based methods, as well as supervised and other unsupervised learning methods on the optical-optical, optical-infrared, optical-synthetic aperture radar (SAR), and optical-map datasets. Experimental results show that MU-Net achieves more comprehensive and accurate registration performance between these image pairs with geometric and radiometric distortions. We share the code implemented by Pytorch at https://github.com/yeyuanxin110/MU-Net. [ABSTRACT FROM AUTHOR]

Carrier modulation, a variant of intermodulation distortion, is described and exploited for the remote detection of radio-frequency (RF) electronics. To generate carrier modulation, a single frequency illuminates an electronic device, which is actively transmitting, and mixing of the applied probe tone with the device's emission produces intermodulation distortion. Theory predicts that carrier modulation is detectable from an emitter at a greater distance away from a radar than the traditional intermodulation distortion. Benchtop measurements taken using commercial RF electronic devices confirm this theory. The experiments demonstrate that carrier modulation may be stimulated remotely from a variety of RF electronics. The spectrum of the distortion may be used to pinpoint an emitter's frequency-of-operation. [ABSTRACT FROM AUTHOR]

A quantum-state-based technique for change detection and analysis is presented. The method establishes a framework for change detection based on quantum states’ entanglement concept. The approach is applicable to quantum sensing (QS) (i.e., low field intensity, photon pairs) but is contingent to feasibility of quantum implementations and measurements. The main objective in this work is to develop a new change detection technique for classical radar/synthetic aperture radar (SAR) remote sensing that is inspired by quantum illumination (QI) and exploits the underlying characteristics and mathematical analogy between quantum-states and radar scatter-field-states. The described application of QI concept to develop a quantum signal processing (QSP) algorithm for classical radar/SAR data exploitations introduces a new change detection approach for SAR multi-pol exploitations. [ABSTRACT FROM AUTHOR]

This article presents the pioneering results of successful target detection using a fully operational and cooperative 5G cellular network as a source of illumination in a passive radar system. The electromagnetic wave generated by the real-life base station allowed for remote sensing of a moving car in bistatic geometry, which shows the feasibility of passive radar in which new generation radio networks serve as an illuminator of opportunity. This article describes passive radar principles, the theoretical fundamentals of the 5G signal structure, and the proposed processing for 5G network-based passive radar. Also, the 5G passive radar demonstrator is described, and the trial results show the possibilities and limitations of using new radio standards in the context of passive radars. [ABSTRACT FROM AUTHOR]

Radar imaging of typical planet landforms can be used for planetary exploration such as landform recognition and geometry measurement. This communication realizes high-resolution imaging simulations of typical planetary landforms, such as craters, hills, and volcanoes, by using parametric scattering center (SC) models. Based on the geometric models of these typical landforms, parametric SC models are constructed from scattered solutions of the physical optics (POs) method. Because the SC models take geometric parameters as model parameters, these models can simulate the scattered waves of landforms of different sizes. These SC models are validated by the PO results. In addition, the landform types can be recognized and their geometrical parameters are further extracted by SC model matching. The extracted geometric parameters show good agreement with real landforms, demonstrating that the SC models of typical planetary landforms have potential applications in planetary geomorphologic exploration. [ABSTRACT FROM AUTHOR]

This article reports the yield estimation of vineyards from using a mobile millimeter-wave radar system. The proximal radar sensor is a 122-GHz FM-CW radar mounted on a rover that moves along the furrows between vine plants. The proposed yield estimation is based on the classification of radar echoes measured for various grape varieties, for different meteorological conditions, and at different stages of grape development. As yield estimation errors are found to be lower than 10%, the proposed radar technique is suitable for precision viticulture applications. [ABSTRACT FROM AUTHOR]

Thermal modeling of different transmission lines (TLs) based on resonant scatterers is presented. The coplanar strip (CPS) and microstrip (MS) TLs are used to model resonators and to introduce the thermal dependence. A reflectometry approach is employed to validate the model by detecting the scatterers’ resonance frequency and comparing it with analytical expressions. The observable shift in the resonance frequency of the scatterers with temperature variations is due to the thermal expansion of metals and temperature dependence of the substrate permittivity. Since all the measurements are done remotely with no direct line of sight, it is shown how such a reflectometry approach can be used for remote temperature sensing using a passive label composed of resonators. Unlike previous works in this domain where the thermal dependence is considered empirically, the introduced model is used to take into account all thermal effects affecting the resonant scatterers allowing to link rigorously the variations of the measured resonance frequency with the temperature without any lookup table. Temperature sensing using very simple TLs based on resonant scatterers was demonstrated in a real environment. A temperature error of less than 3 °C is obtained. Once the temperature has been determined, it is possible to go back to the TL parameters, such as the effective permittivity and the physical length. [ABSTRACT FROM AUTHOR]

There has been significant research devoted to the development of distributed microwave wireless systems in recent years. The progression from large, single-platform wireless systems to collections of smaller, coordinated systems on separate platforms enables significant benefits for radar, remote sensing, communications, and other applications. The ultimate level of coordination between platforms is at the wavelength level, where separate platforms operate as a coherent distributed system. Wireless coherent distributed systems operate in essence as distributed phased arrays, and the signal gains that can be achieved scale proportionally to the number of transmitters squared multiplied by the number of receivers, providing potentially dramatic increases in wireless system capabilities enabled by increasing the number of nodes in the array. Coordinating the operations of nodes in a distributed array requires accurate control of the relative electrical states of the nodes. The basic challenge is the synchronization and stability of the relative phases of the signals transmitted or received. Generally, such control requires wireless frequency synchronization, phase calibration, and time alignment. For radar operations, phase control also requires high-accuracy knowledge of the relative positions of the nodes in the array to support beamforming. Various technologies have been developed in recent years to address the coordination challenges for closed-loop applications, such as distributed communications, and more recently, there has been growing interest in new technologies for open-loop applications, such as radar and remote sensing. This article presents an overview of distributed phased arrays, the principal challenges involved in their coordination, and recent research progress addressing these challenges. [ABSTRACT FROM AUTHOR]

Forward-looking multichannel synthetic aperture radar (FLMC-SAR) is an important tool for modern remote sensing applications, which has the capability to reconstruct the high-resolution image of the front area. However, due to the azimuth-variant characteristics of the motion errors over a long aperture, FLMC-SAR data processing is usually a challenging task, especially when involving the motion compensation (MOCO) coupled with Doppler ambiguity resolving. To accomplish an accurate MOCO for FLMC-SAR, a novel parametric azimuth-variant MOCO approach is proposed in this article. Aiming at the coupling problem of MOCO and Doppler ambiguity resolving over the full aperture, we can decouple them through the subaperture division. As a full synthetic aperture is decomposed into several subapertures, the high-order motion errors of the full aperture can be decomposed into the first-order motion errors of the subaperture. On this basis, the mismatch of the space–time spectrum caused by the motion errors can be solved by spectral estimation, yielding Doppler ambiguity resolving for each subaperture. Meanwhile, the azimuth-variant characteristic of motion errors in FLMC-SAR system is characterized by a parametric angle-dependent quadratic phase error (QPE) model. The motion parameters are estimated by a joint multichannel angle estimation-based signal quadratic decomposition method. Immediately, the MOCO for ambiguous targets with different motion errors can be processed separately to improve the imaging performance. Experimental results based on both simulated and real data demonstrate that the proposed method is suitable for FLMC-SAR system. [ABSTRACT FROM AUTHOR]

The direction-finding high-frequency (HF) radar that employs a crossed-loop/monopole antenna as receiving has been widely applied in sea surface dynamics remote sensing due to its compact footprint and remarkable performance. Nevertheless, the direction-of-arrival (DOA) estimation of this system remains challenging in the case of coherent signals, which imposes a great threat to the radar measurement accuracy but has rarely been concerned in the past. In this article, a novel method combining the covariance matrix reconstruction process and subspace estimation technology is proposed to deal with this problem. By exploiting the purely real property of the array manifold, the rank loss of the covariance matrix due to the coherence of signals is mitigated. Both the theoretical derivation and numerical analysis prove that the proposed method is valid in estimating two coherent signals, and the DOA estimation accuracy is mainly related to the signal-to-noise ratio (SNR) and angle separation of the signals. Finally, field experiment data are also used to validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

We propose a lightweight radar that autonomously measures snow depth over sea ice from an unmanned aerial vehicle (UAV). Development of this snow radar and its integration with an octocopter UAV is presented. Field trials of the UAV-mounted snow radar, conducted in Antarctica during the summer season of 2017/2018, are also described. The radar allows measurements of snow depths on sea ice between 10 and 100 cm. Additional reflections due to internal layers within the snow are evident at a few measurement points. The snow radar is evaluated for various flight parameters: stationary; flying at speeds between 1 and 3 m/s, and at heights from 5 to 15 m. Evaluation of snow-depth results indicates that a depth accuracy of ±3.2 cm is achieved with stationary measurements, and of ±9.1 cm with measurements at the various flight speeds. [ABSTRACT FROM AUTHOR]

In this article, a theoretical study is carried out to seek an approach to remotely measure the thickness of the oil film. It is known that it is difficult to probe the oil thickness using a microwave radar due to the fact the dielectric constant of oil is very small compared with seawater for microwave frequencies. While in the range of terahertz (THz) electromagnetic (EM) wave frequency, the dielectric constants of oil and seawater are comparable, resulting in the THz EM fields scattered from the air–oil interface and those from the oil–water interface can produce constructive and destructive interference with the variation in the oil film thickness. Based on this principle, the sensitivity of the THz EM wave to the oil thickness is investigated in this work. First, the oil–seawater two-layer medium is equivalent to a single-layer medium by an equivalent dielectric constant model. Then, the THz EM scattering from the oil-covered sea surface is simulated using the first-order small slope approximation method (SSA-1) and the obtained equivalent dielectric constant. Meanwhile, the influences caused by the damping effect of the oil film, the reduction for friction velocity, and the change in equivalent permittivity on the normalized radar cross section (NRCS) are analyzed. The numerical results show that the NRCSs of THz frequencies are more sensitive to the change in oil thickness than that of microwave frequencies. This property makes the THz EM wave have the potential to probe the thickness of the oil film. [ABSTRACT FROM AUTHOR]

VIPR (vapor in-cloud profiling radar) is a tunable G-band radar designed for humidity and cloud remote sensing. VIPR uses all-solid-state components and operates in a frequency-modulated continuous-wave (FMCW) radar mode, offering a transmit power of 200–300 mW. Its typical chirp bandwidth of 10 MHz over a center-frequency tuning span of 167–174.8 GHz results in a nominal range resolution of 15 m. The radar’s measured noise figure over the transmit band is between 7.4 and 10.4 dB, depending on its frequency and hardware configuration, and its calculated antenna gain is 58 dB. These parameters mean that with typical 1 ms chirp times, single-pulse cloud reflectivities as low as −26 dBZ are detectable with unity signal-to-noise at 5 km. Experimentally, radar returns from ice clouds above 10 km in height have been observed from the ground. VIPR’s absolute sensitivity was validated using a spherical metal target in the radar antenna’s far-field, and a G-band switch has been implemented in an RF calibration loop for periodic recalibration. The radar achieves high sensitivity with thermal noise limited detection both by virtue of its low-noise RF architecture and by using a quasioptical duplexing method that preserves ultrahigh transmit/receive isolation despite operation in an FMCW mode with a single primary antenna shared by the transmitter and receiver. [ABSTRACT FROM AUTHOR]

Recent developments in electronics have pushed miniaturized satellites to the femto-scale, with masses between 10 and 100 g. Although femtosatellites have been proven as a feasible concept, most designs are limited in mission capacity and lifetime due to the lack of environmental protection and onboard propellant. In this article, a novel concept for femtosatellites for earth remote sensing is proposed. In particular, a swarm of femtosatellites are used as elements of a sparse array in orbit to receive radar echoes. They also feature active orbit control enabled by solar radiation pressure to extend their lifetime. A simple active orbit control algorithm has been demonstrated. A mission concept based on a sun-synchronous circular orbit is proposed to maximize the benefit for both earth remote sensing and active orbit control. A synthetic aperture radar mission has been used to characterize their performance. [ABSTRACT FROM AUTHOR]

For an unmanned aerial vehicle (UAV) carrying out a maritime radar surveillance mission, there is a tradeoff between maximizing information obtained from the search area and minimizing fuel consumption. This article presents an approach for the optimization of a UAV's trajectory for maritime radar wide area persistent surveillance to simultaneously minimize fuel consumption, maximize mean probability of detection, and minimize mean revisit time. Quintic polynomials are used to generate UAV trajectories due to their ability to provide complete and complex solutions while requiring few inputs. Furthermore, the UAV dynamics and surveillance mission requirements are used to ensure that a trajectory is realistic and mission compatible. A wide area search radar model is used within this article in conjunction with a discretized grid in order to determine the search area's mean probability of detection and mean revisit time. The trajectory generation method is then used in conjunction with a multiobjective particle swarm optimization algorithm to obtain a global optimum in terms of path, airspeed (and thus time), and altitude. The performance of the approach is then tested over two common maritime surveillance scenarios and compared to an industry recommended baseline. [ABSTRACT FROM AUTHOR]

In remote sensing, micro-Doppler signatures are widely used in moving target detection and automatic target recognition. However, since Doppler signatures are easily affected by the moving direction of the target, prior information of aspect angle is essential for spectral analysis. Thus, a micro-Doppler-based classifier is considered to be “angle-sensitive.” In this article, we propose an angle-insensitive classifier for the omnidirectional classification problem using the monostatic radar through a proposed new convolutional neural network. We further provide a sensible definition of “angle sensitivity,” and perform experiments on two data sets obtained through simulations and measurements. The results demonstrate that the proposed algorithm outperforms both feature-based and existing deep-learning-based counterparts, and resolve the issue of angle sensitivity in micro-Doppler-based classification. [ABSTRACT FROM AUTHOR]

The first X-band dual polarized phased array weather radar (DP-PAWR), which simultaneously transmits pulses of horizontal and vertical polarized radiation, was developed and installed at Saitama University, Japan, in December 2017. The DP-PAWR uses mechanical and electronic scanning at azimuth and elevation angles, respectively. It provides polarimetric precipitation measurements via 3-D volume scanning with an update rate between 10 and 60 s, for a range of up to 80 km. Here, we describe the initial DP-PAWR observation results. To evaluate the DP-PAWR observation accuracy, we compared the observational data with radar variables derived from Parsivel disdrometer data. In comparison with the disdrometer, the relative observation accuracy for the DP-PAWR radar reflectively factor had a standard deviation of 1.1 dB and mean value of 0.4 dB. We also conducted detailed observations of a developing thunderstorm using a specific differential phase (Kdp) column, focusing on the Kdp core during the storm. The Kdp core movements provided useful information about the convection flow during the storm. [ABSTRACT FROM AUTHOR]

The morning of November 23, 2013, a lava fountain formed from the New South-East Crater (NSEC) of Mt. Etna (Italy), one of the most active volcanoes in Europe. The explosive activity was observed from two ground-based radars, the X-band polarimetric scanning and the L-band Doppler fixed-pointing, as well as from a thermal-infrared camera. Taking advantage of the capability of the microwave radars to probe the volcanic plume and extending the volcanic ash radar retrieval (VARR) methodology, we estimate the mass eruption rate (MER) using three main techniques, namely surface-flux approach (SFA), mass continuity-based approach (MCA), and top-plume approach (TPA), as well as provide a quantitative evaluation of their uncertainty. Estimated exit velocities are between 160 and 230 m/s in the paroxysmal phase. The intercomparison between the SFA, MCA, and TPA methods, in terms of retrieved MER, shows a fairly good consistency with values up to 2.4 × 106 kg/s. The estimated total erupted mass (TEM) is 3.8 × 109, 3.9 × 109, and 4.7 × 109 kg for SFA with L-band, X-band, and thermal-infrared camera, respectively. Estimated TEM is between 1.7 × 109 kg and 4.3 × 109 for TPA methods and 3.9 ×109 kg for the MCA technique. The SFA, MCA, and TPA results for TEM are in fairly good agreement with independent evaluations derived from ground collection of tephra deposit and estimated to be between 1.3 ± 1.1 × 109 and 5.7 × 109 kg. This article shows that complementary strategies of ground-based remote sensing systems can provide an accurate real-time monitoring of a volcanic explosive activity. [ABSTRACT FROM AUTHOR]

This article presents the design and optimization of a deployable 1 m mesh reflector compatible with a 12U-class CubeSat. This antenna is designed for telecommunication and is compatible with NASA’s deep-space network (DSN) at ${X}$ -band (i.e., uplink: 7.145–7.19 GHz; downlink: 8.4–8.45 GHz) and Ka-band frequencies (i.e., uplink: 34.2–34.7 GHz; downlink: 31.8–32.3 GHz). Three right-handed circularly polarized (RHCP) antennas, both transmit and receive, are introduced here: ${X}$ -band only, Ka-band only, and ${X}$ -/Ka-band. For the ${X}$ -band-only antenna, a gain of 36.1 and 36.8 dBic is achieved at uplink and downlink frequency bands, respectively. This translates into an aperture efficiency of 72% and 62%. For the Ka-band-only antenna, a gain of 48.4 and 48.7 dBic is obtained at downlink and uplink frequency bands, which translate into an aperture efficiency of 62% and 72%, respectively. [ABSTRACT FROM AUTHOR]

Compact high-frequency surface wave radar has been widely applied to the measurement of sea surface current, but its accuracy and direction resolution of wave parameter estimation are always limited due to the wide beam of the antenna. In this article, a novel wave-height mapping method based on the second-order harmonic peak (SHP) of radar Doppler spectra is proposed to address this concern. The characteristic of the SHP at the Doppler frequency of $\sqrt {2}$ times the Bragg frequency is studied through the theoretical derivation and numerical simulation. A relationship between the ratio ($R$) of the SHP power to the Bragg peak power and significant wave height ($H_{s}$) is derived. Furthermore, the $R$ – $H_{s}$ model is improved by incorporating influences, such as background noise and antenna beamwidth. With this improved model, a wave-height mapping algorithm based on the direction finding technique is presented. This approach enables the significant wave-height map extraction using a broad-beam radar. Finally, wave-height maps obtained at different sea states are depicted and analyzed, and the wave heights appearing on the maps are compared with buoy data over a one-month experiment to verify the validity and robustness of the algorithm. During this period, the significant wave height varies from about 0.5 to 4.5 m, and the radar measured wave heights at different range/distance bins show an overall root-mean-square error (RMSE) of 0.33–0.77 m and a correlation coefficient (CC) of 0.78–0.94, with respect to the buoy measurements. [ABSTRACT FROM AUTHOR]

We present and discuss an electromagnetic model for the description of the coherent scattering from bare soils illuminated by a radar system under arbitrary bistatic geometries. The scattering problem is solved under the Kirchhoff approximation (KA) accounting for both the sphericity of the wavefront of the incident wave and the radiation pattern of the transmitting and receiving antennas. We propose here a general formulation and solution of the scattering problem applicable to an arbitrary bistatic geometry. We discuss and demonstrate the importance of our extension for the characterization of the coherent scattering generated in bistatic radar systems, both inside and outside the plane of incidence. The model is validated against the numerical solution of the Kirchhoff integral and, in the case of the perfect plane conductor, by comparison with the image theory. The work is intended to provide a simple methodology to characterize the coherent normalized radar cross section (NRCS) of a rough surface to be used within the radar equation for extended targets, similarly to what is done for the incoherent component. It aims at enabling a local characterization of the coherent scattering in realistic conditions (e.g., in the presence of inhomogeneous and mountainous surfaces), a feature that is particularly important for practical applications, such as the modeling and understanding of the bistatic scattering generated by sources of opportunity and specifically for Global Navigation Satellite System Reflectometry (GNSS-R) related applications. [ABSTRACT FROM AUTHOR]

High-frequency (HF) ocean radar has the potential to observe sea ice, but this application has not been thoroughly investigated. In this article, we explore sea ice observation with HF radar (HFR) and develop a corresponding signal processing procedure. We derived sea ice radial velocities from raw HFR data and determined angular positions using the MUltiple SIgnal Classification (MUSIC) algorithm. Sea ice velocities were evaluated by comparison with measurements from moored acoustic Doppler current profilers (ADCPs) and a drifting buoy. The root-mean-square (rms) differences between the sea ice velocities obtained by HFR and the ADCPs decreased with increasing radar signal-to-noise ratio (SNR), implying that a high SNR was associated with accurate measurement of sea ice velocity. These results agree with previous validations of HFR ocean current observations. The sea ice pattern mapped by HFR is consistent with the simultaneous C-band microwave radar observations. In particular, the HFR captured the approach of the sea ice edge toward the coast. Sharp attenuation of the HF signal over high concentration sea ice resulted in missing and/or low-SNR data at ranges beyond the front edge of pack ice, in qualitative agreement with model estimates of attenuation. [ABSTRACT FROM AUTHOR]

The emergence of CubeSats has opened up the possibilities of advanced space missions with lower costs and faster development times. A major factor that limits the functionality of CubeSats is the absence of high-gain antennas (HGAs) that can sustain a high data-rate link for communications or provide the required spatial resolution for remote sensing. In this work, we discuss the development of one of the largest apertures at Ka-band for CubeSats—a 1 m mesh deployable offset reflector antenna, with a stowed volume of 3U ($10\times 10\times 30 \,\,\text {cm}^{3}$)—to enable precipitation radars that can achieve the required spatial resolution while meeting the stringent mechanical constraints posed by the small CubeSat volume. We detail the critical aspects of this antenna design, including RF characterization, antenna fabrication, and measurement. We also describe a novel deployment mechanism that facilitates the packaging of such a large aperture in a small volume. The antenna demonstrated a measured efficiency of 60%, with a half-power beamwidth of 0.60° at 35.75 GHz. The cost reduction afforded by CubeSats makes launching a constellation of such radar based CubeSats practical, allowing higher temporal sampling rates, which is essential for the observation of weather processes with a short-time evolution. [ABSTRACT FROM AUTHOR]

Shore-based coherent microwave radar and high-frequency (HF) surface wave radar are two components of a rapidly emerging set of technologies suitable for ocean wave remote sensing. To investigate their differences, this paper describes and analyzes the relationship between the water particle velocity and the wave height spectrum based on linear wave theory which underpins the algorithms developed for the analysis of data collected by coherent microwave radar. The backscatter mechanism which addresses the interaction of the HF radio waves with the ocean surface waves, as well as the empirical method adopted in our HF radar is also presented. The wave characteristics observed by the shore-based coherent S-band radar [Microwave Ocean Remote SEnsor (MORSE)] are analyzed. A multifrequency HF (MHF) radar based on a circular receiving array, which is capable of sensing waves up to 100-km offshore, is also introduced. An intercomparison of the wave height measurements obtained from the MORSE, MHF radar, and wave buoy is made. The comparison indicates that the wave heights measured by the MORSE and the MHF radar are consistent with the buoy-derived wave heights, with the root-mean-square differences (RMSDs) of 0.27 and 0.37 m, respectively. [ABSTRACT FROM AUTHOR]

A novel procedure based on filtering and interpolation approaches is proposed to estimate the sea state parameters, including significant wave height, peak wave direction, peak period, peak wavenumber, and peak wavelength in shallow waters using the X-band marine radars. The method compensates the distortions introduced by the radar acquisition process and the power decay of the radar signal along the distance applying image-enhancement techniques instead of empirical and semiempirical calibration methods that use signal-to-noise ratio and in situ measurements as external references. To determine the threshold value for the interpolation approach, the influence of the antenna height on shadowing modulation effects is examined through performing an analysis of variance (ANOVA) that uses data from two X-band radars deployed at 10 and 20 m above MSL. ANOVA results reveal that it is possible to explain the increment of intensities affected by shadowing throughout the distance using an adaptive threshold retrieved from a third-order polynomial function of the mean radar cross section (RCS). Finally, an X-band radar is installed at 13 m above MSL to test the proposed technique. During measurements, the wind and wave conditions varied, and the antenna-look direction remained constant. Errors for $H_{s}$ , $\theta _{p}$ , and $T_{p}$ calculated as the difference between estimated and true data show a mean bias and a relative value of 0.05 m (2.72%), 1.52° (5.94%), and 0.15 s (1.67%), respectively. The directional and wave energy spectra derived from radar estimates, acoustic wave and current, ADVs record, as well as JONSWAP formulation are presented to illustrate the improvement resulting from the proposed method over the frequency domain. [ABSTRACT FROM AUTHOR]

Wave–current interaction is a common and important phenomenon in the ocean. As an ocean remote sensing tool, high-frequency (HF) radar can be used to measure currents and wave parameters. In this paper, the possibility of studying wave–current interaction using HF radar is investigated. The first-order spectral power (FSP) of HF radar is used to explore the effect of current on the Bragg wave. By analyzing the FSP change with current (FSP-current distribution), we find that, in deep water, the wave–current interactions mainly belong to 2-D refraction case, while, over a relatively shallow shelf, the interactions are stronger and more complicated. Based on local topography and current field data at Taiwan Strait, the simulation results obtained using the SWAN model confirm the 2-D refraction of the Bragg wave. When the wave–current interaction is stable, we compensate the FSP with radar-measured currents according to the radar extracted FSP-current distribution and achieve a more accurate wind estimation. Comparisons between the original and refined wind fields show the effectiveness and necessity of the current-based compensation. [ABSTRACT FROM AUTHOR]

Microwave backscattering models play key roles in surface scattering modeling and soil moisture inversion in active microwave remote sensing. However, numerous evaluations indicate that significant discrepancies between the model simulations and radar observations remain, and these discrepancies are regarded to be attributed to inaccuracies in the models. What do such discrepancies originate from is unclear and has not been comprehensively analyzed. To this end, this paper presents an uncertainty analysis to explore the intrinsic reason for the discrepancies between the backscattering model simulations and radar observations. The probability distribution function and the corresponding statistical characteristics are introduced to describe the uncertainty in the model outputs. We find that the scale dependence of the key model inputs leads to significant uncertainties in the model inputs, and the uncertainties are transferred into the model outputs. Thus, the discrepancies between the model simulations and radar observations are intrinsically caused by the spatial scaling and related uncertainties of key model inputs. In short, the scale mismatch between the model inputs and remote sensing pixels is an intrinsic factor that causes the discrepancies between the model simulations and radar observations. This finding suggests that the scaling effect of model inputs should be carefully considered when using the backscattering models at the pixel scale, and equivalent inputs matched at the corresponding scales should be developed for remote sensing applications. Thus, this analysis insights into the scale dependence of inputs for backscattering models and suggests to provide scale-matched inputs where the models are applied at different scales. [ABSTRACT FROM AUTHOR]

Simulation of radar sounder (RS) data is important for understanding the radar response of subsurface features to facilitate the interpretation of the real data. Conventional electromagnetic simulators require the definition of complex geoelectrical models of the investigated targets. They also involve time-complex solutions of Maxwell’s equations for computing the received electric field, which leads to very high computation time. Furthermore, the simulated radargrams are often not realistic as it is very difficult to model all the variables involved in the data acquisition. In this paper, we propose a novel simulation approach that exploits the data available from existing RSs in geologically analogous terrains, to produce realistic simulations of the investigated RS target. This simulation strategy is based on minimizing the difference between the analog and the investigated acquisition scenarios. This is done by applying a series of corrections, which depend on the relation between the radargram characteristics and the physical variables describing the acquisition process. The aim is to produce radargrams that resemble the investigated scenario in terms of the echo magnitude, bandwidth, range resolution, and along-track resolution. Experimental results present three case studies for different possibilities of the analog and the investigated scenarios. The validation of the simulated radargrams with actual data demonstrates the effectiveness of the proposed approach. Finally, we also present a real application of this approach for the simulation of Radar for Icy Moon Exploration (RIME) radargrams for a combination of instrument and target parameters, using the SHAllow RADar (SHARAD) radargram acquired over the geological analog of a selected RIME target. [ABSTRACT FROM AUTHOR]

During the past decades, radar sounder (RS) instruments have been effectively used to detect subglacial lakes (SLs). SLs appear as flat, smooth, and bright reflectors in RS radargrams. The visual interpretation has been the main approach to SL detection in radargrams. However, this approach is subjective and inappropriate for processing large amounts of radargrams. While the analysis of RS data for understanding the subglacial hydrology has recently received increased attention, the literature on the development of automatic methods specifically designed for SL detection is still limited. In order to fill this gap, in this paper, we propose a novel automatic technique for SL detection. The technique is made up of two steps: 1) feature extraction and 2) automatic detection. In the first step, we define and extract three families of features for discriminating between the lake and nonlake radar reflections. The features model locally the basal topography, the shape of the basal reflected waveforms, and the statistical properties of the basal signal. In the second step, we provide the features as input to a support vector machine classifier to perform the automatic SL detection. The proposed technique has been applied to radargrams acquired over two large regions in East Antarctica and Siple Coast. The obtained results, which are validated both quantitatively and qualitatively, confirm the robustness of the features and their capabilities to effectively characterize SLs. Moreover, they prove the potentiality of the method to process large amounts of radargrams and update the current SL inventory. [ABSTRACT FROM AUTHOR]

Interference among frequency modulated continues wave automotive radars can either increase the noise floor, which occurs in the most cases, or generate a ghost target in rare situations. To address the increment of noise floor due to interference, we proposed a low calculation cost method using adaptive noise canceller to increase the signal-to-interference ratio. In a quadrature receiver, the interference in the positive half of frequency spectrum is correlated to that in the negative half of frequency spectrum, whereas the beat frequencies from real targets are always present in the positive frequency. Thus, we estimated the power of the negative frequency as an indication of interference, and fed the positive frequency and negative frequency components into the primary and reference channel of an adaptive noise canceller, respectively. The least mean square algorithm was used to solve for the optimum filter solution. As a result, both the simulation and experiment showed a good interference mitigation performance. [ABSTRACT FROM AUTHOR]

The problem considered is that of estimating unambiguously migrating targets observed with a wideband radar. We extend a previously described sparse Bayesian algorithm to the presence of diffuse clutter and off-grid targets. A hybrid-Gibbs sampler is formulated to jointly estimate the sparse target amplitude vector, the grid mismatch, and the (assumed) autoregressive noise. Results on synthetic and fully experimental data show that targets can be actually unambiguously estimated even if located in blind speeds. [ABSTRACT FROM AUTHOR]

In this paper, an ultra-wideband fully integrated imaging radar at sub-terahertz (sub-THz) frequencies is presented, which demonstrates a fine lateral resolution without using any focal lens/mirror. We have achieved a lateral resolution of 2 mm for an object at 23-cm distance as well as a range resolution of 2.7 mm. To achieve the decent range resolution, in a frequency modulation continuous wave radar configuration, a state-of-the-art chirp bandwidth (BW) of 62.4 GHz at a center frequency of 221.1 GHz is generated and efficiently radiated. We have presented a design technique for the optimal design of the passive embedding around the core transistor to maximize the tuning BW of the voltage controlled oscillator. At the receiver side, to maximize the intermediate frequency level, a subharmonic mixer is utilized, which is designed for the lowest conversion loss. Finally, to obtain the fine lateral resolution, we have implemented near-field beamforming algorithm based on the inverse synthetic aperture radar (ISAR) systems. The synthesized beamwidth is less than 0.5°; hence, high-resolution images are reconstructed. The system is fabricated in a 55-nm BiCMOS process. To the best of our knowledge, this is the first imaging radar at THz/sub-THz frequencies, which utilizes ISAR to achieve a high lateral resolution while the radar system is fully integrated. [ABSTRACT FROM AUTHOR]

This paper introduces a new concept of slow-time spatial frequency space, also known as “slow-time $k$ -space,” and redefines the associated cross-range bandwidth, which arises naturally from Doppler radar tomography. The slow-time $k$ -space is the most suitable for narrow-band radar imaging, and can be augmented for higher resolution imaging by appropriate signal processing. The respective relationships with the more traditional concepts of fast-time $k$ -space and signal (or range) bandwidth are explained. We also discuss image resolution limits and demonstrate the concepts with simulated data examples. [ABSTRACT FROM AUTHOR]

Recent studies indicate that the poor antenna sidelobe level of phased-array high-frequency (HF) radars degrades the performance of Bragg ratio estimation for wind direction measurements. To explore this issue, this paper improves the previous model of wind direction estimation for phased-array HF radars, and the effect of unsatisfactory array patterns on Bragg ratio estimation is theoretically analyzed. Moreover, a hybrid beam-forming and direction-finding method, in which wind direction is measured by reducing the influence of unsatisfactory array patterns on Bragg ratio estimation, is proposed for multifrequency HF radars installed along the coast of Zhejiang Province in China. The procedure for implementing this scheme is also presented in detail. Wind directions derived from 8.05-, 10.7-, 16.8-, and 19.2-MHz radar data are compared with measurements collected with anemometers at three sampling locations to verify the proposed method, and the measurements with root-mean-square errors from 19.5° to 26.6° show that this strategy is effective for wind direction measurements. We recommend adopting the proposed method or using similar approaches to estimate wind direction based on HF radars, especially in situations where the array pattern is not sufficiently narrow. [ABSTRACT FROM AUTHOR]

In this paper, monitoring of metal-cased oil wells using the ultrawideband (UWB) radar is proposed. The inspection includes the detection and imaging of perforations and corroded areas in a metal pipe. Detection of small anomalies/ perforations on the surface of a narrow metal pipe is very challenging. Here, we present a method for imaging such small anomalies based on the extra time delay of the reflected pulse due to the effect of perforation in the radar near field. In this paper, the necessary concepts for the use of UWB radar specified for this application are developed and proved based on different measurement and simulation scenarios. We have experimentally demonstrated the effect of the perforations’ size on the time delay of reflected pulses. The distance between the perforation and the radar, for the near-field phenomenon, is critical for an effective detection and imaging. Therefore, we also studied the optimal distance between the radar and the perforation. Perforations with a size range of 1–3 cm are considered for the experiments and simulations. The experiments are done both in air and diesel. Synthetic aperture radar processing is used to reconstruct the images of the perforations and corroded area. Measurement and simulation results demonstrate the potential of UWB radar systems for oil well monitoring applications. [ABSTRACT FROM AUTHOR]

The polar layered deposits (PLDs) provide a wealth of information about the past climate evolution of Mars. Surface mass fluxes and ice flow mainly governed topography and layering of the PLD. China’s Mars probe including an orbiter and a landing rover will be launched by 2020. A new type satellite-borne Mars penetrating radar instrument has been selected to be a part of the payloads on the orbiter. Its main scientific objectives are to map the distribution of water, water–ice and to detect the soil characteristics at global scale on the Martian crust. Compared with Mars Advanced Radar for Subsurface and Ionospheric Sounding and Shallow Radar, the biggest difference is that the antenna system of this Mars penetrating radar consists of two dipole antennas mutually perpendicular. This special configuration enables the investigation of the ice flow of PLD by detecting and analyzing the features of anisotropic crystal-orientation fabric (COF). Thus, relying on the fact that the radio waves are depolarized while passing through an anisotropic COF layer, in this paper, a method for anisotropic COF detection based on this radar system is proposed. The radar echo formulation of anisotropic COF is derived and the ratio of the signals measured by the two perpendicular antennas is used to analyze the anisotropy of COF. We demonstrate that the ratio is an ideal criterion for the detection and analysis of COF, since it contains all parameters about the anisotropy feature of COF and it is independent of the attenuation in the propagation path and the reflection coefficient. In order to verify the validity of the derived analytical expression of the ratio for the detection of COF, finite-different time-domain simulations are carried out based on a simple model of the subsurface of PLD which contains an anisotropic COF layer. The advantages of this method, the potential application scenarios, and the effects of the Martian environment are also discussed. [ABSTRACT FROM AUTHOR]

The global optimal solution (GOS) has proven to be very accurate for deriving water surface velocities from contemporaneous image pairs, but previous studies have used shore-based radars or satellite measurements with resolutions on the order of a kilometer or tens of meters to establish this. In contrast, the objective of this paper is to derive a GOS velocity field from infrared (IR) (3–5 $\mu \text{m}$) images having a 1-m pixel size. Because IR images can frequently exhibit a low signal-to-noise ratio, a newly developed GOS technique with a local similarity metric is used to retrieve velocities from such low-contrast data sets. To demonstrate the utility of this new method, we use airborne data collected in the tidal Potomac River over 11 days and spatially varying flood, ebb, and slack conditions. The resulting GOS-derived velocity estimates are compared against acoustic Doppler current profiler (ADCP) measurements taken simultaneously with the airborne collections. Velocity magnitudes and directions are found to have GOS versus ADCP correlations of 0.93 and 0.99, respectively. This high correlation suggests that the GOS technique may be applicable to a variety of lower contrast imagery that can now be collected by a low-altitude remotely controlled aircraft. [ABSTRACT FROM AUTHOR]

Accurate information about ocean surface currents is of high importance for many purposes. Traditional ways of measuring surface currents using instruments immersed in water are associated with various challenges, as well as high installation and maintenance costs. Algorithms and hardware used to measure surface currents based on marine X-band radar images have been steadily improved during the recent decades. Such systems can now provide the user with current measurements with high accuracy in local areas of interest and with no need for underwater equipment, both from fixed sites and from moving installations, such as vessels. The primary focus of the work presented in this paper is to examine the measurement accuracy of an X-band radar-based system. For this purpose, field trials have been arranged and data acquired from a fixed platform in the North Sea in November 2015 and December 2015 and from a research vessel in the Norwegian Sea and the Barents Sea in November 2016. Data are analyzed, measured time series are compared to reference measurements and tidal current models, and statistical estimates of the measurement accuracy are calculated. Root-mean-square measurement errors of 0.032 m/s and 9.1° for magnitude and direction, respectively, are estimated for the fixed installation. Correlation coefficients are 0.93 and 0.94 for east–west and north–south components, respectively. A pooled standard deviation of 0.059 m/s is estimated for the moving installation. [ABSTRACT FROM AUTHOR]

Remote sensing technology is an essential link in the global monitoring of the ocean surface, and radars are efficient sensors for detecting marine pollution. When used operationally by authorities, a tradeoff must usually be made between the covered area and the quantity of information collected by the radar. To identify the most appropriate imaging mode, a methodology based on receiver operating characteristic curve analysis has been applied to an original data set collected by two airborne systems operating at L-band, both characterized by a very low instrument noise floor. The data set was acquired during controlled releases of mineral and vegetable oil at sea. Various polarization-dependent quantities are investigated, and their ability to detect slick-covered areas is assessed. A relative ordering of the main polarimetric parameters is reported in this paper. When the sensor has a sufficiently low noise floor, HV is recommended because it provides the strongest slick–sea contrast. Otherwise, VV is found to be the most relevant parameter for detecting slicks on the ocean surface. Among all the investigated quad-polarimetric settings, no significant added value compared to single-polarized data was found. More specifically, it is demonstrated, by increasing the instrument noise level, that the studied polarimetric quantities which combine the four polarimetric channels have performances of detection mainly driven by the instrument noise floor, namely, the noise equivalent sigma zero. This result, obtained by progressively adding noise to the raw synthetic aperture radar (SAR) data, indicates that the polarimetric discrimination between clean sea and polluted area results mainly from the differentiated behavior between single-bounce scattering and noise. It is thus demonstrated, using SAR data collected with a low instrument noise floor, that there is no deviation from Bragg scattering for radar scattering from ocean surface covered by mineral and vegetable oil. [ABSTRACT FROM AUTHOR]

The Global Precipitation Measurement (GPM) mission was launched in February 2014; its dual-frequency precipitation radar (DPR) operates at both Ku- and Ka-band s. Attenuation in precipitation is typically not negligible, especially at Ka-band. Hence, attenuation correction is an important part of the GPM DPR retrieval algorithm. The operational algorithm uses a path-integrated attenuation (PIA) obtained by comparing the measured surface return with that expected either from a nearby, nonprecipitating area or from the same area, acquired at a previous, nonprecipitating time. This surface reference technique has worked well in most situations but can result in erroneously low estimates of the path attenuation in situations with nonuniform filling of the radar beam, especially at Ka-band due to its larger attenuation. This paper explores the existence of relationships between the Ka-band PIA and the characteristics of the measured reflectivity profiles. The author finds that PIA is, indeed, related to reflectivity profiles, with strongest correlation between the PIA and the measured rainfall dual-frequency reflectivity ratio just above the surface. This relationship could be used as an estimator in the cases with severe nonuniform beam filling. [ABSTRACT FROM AUTHOR]

This paper presents a novel automatic real-time remote sensing algorithm that uses radar images and global positioning satellite system measurements to estimate the ice-drift velocity vector in a region around a free-floating and potentially moving vessel. It is motivated by the low image frequency of satellite systems together with the inconvenience of deploying and retrieving ice trackers (beacons) on the ice. The algorithm combines radar image processing with two Kalman filters to produce the estimated local drift vector decoupled from the ship motion. The proposed design is verified using a full-scale data set from an ice management operation north of Svalbard in 2015. It is found that the performance of the algorithm is comparable with that of trackers on the ice. [ABSTRACT FROM AUTHOR]

This paper presents a Ku -band (14–16 GHz) CMOS frequency-modulated continuous-wave (FMCW) radar transceiver developed to measure dry-snow depth for water management purposes and to aid in retrieval of snow water equivalent. An on-chip direct digital frequency synthesizer and digital-to-analog converter digitally generates a chirping waveform which then drives a ring oscillator-based Ku -Band phase-locked loop to provide the final Ku -band FMCW signal. Employing a ring oscillator as opposed to a tuned inductor-based oscillator (LC-VCO) allows the radar to achieve wide chirp bandwidth resulting in a higher axial resolution (7.5 cm), which is needed to accurately quantify the snowpack profile. The demonstrated radar chip is fabricated in a 65-nm CMOS process. The chip consumes 252.4 mW of power under 1.1-V supply, making its payload requirements suitable for observations from a small unmanned aerial vehicle. [ABSTRACT FROM PUBLISHER]

This paper presents the estimation of the ground elevation and canopy top elevation from the data collected by an airborne frequency-modulated continuous waveform profiling radar, Tomoradar. The estimated ground and canopy top elevations are critical for the derivation of reference information for the satellite-borne microwave radar data and the modeling of interaction between microwave radar signal and foliage. The methods of estimating the ground elevation and canopy top elevation from profiling radar are introduced, and the accuracy was evaluated via digital terrain model and Velodyne VLP-16 LiDAR integrated with the Tomoradar. To our knowledge, the ranging radar and the LiDAR data were simultaneously collected for the first time. The evaluation proved that the root-mean-square error (RMSE) of ground level estimation of the developed profiling radar can reach up to 0.33 m. When comparing the estimated canopy top peak elevation between the profile radar data and the LiDAR data, it was found that the side lobes of Tomoradar antenna system may produce undesired canopy backscatters when the size of the canopy gap is comparable to the footprint size of the main lobe, resulting in a higher canopy top elevation measurement from Tomoradar than that from LiDAR. The RMSE of the estimated canopy top peak elevation between two data sets was 0.32 m in the best case and 0.852 m on average. Moreover, the RMSE of point-to-point comparing the entire canopy tops elevation estimated from the data of two active remote sensing systems is 0.799 m after excluding the outliers. [ABSTRACT FROM AUTHOR]

The commonly applied K-distribution to model the synthetic aperture radar image amplitude of the heterogeneous (non-Gaussian) sea surface as the basis for vessel detection has shown deficiencies in practical cases, particularly for spacebased systems. Due to a deviation between the K-probability density function and measured histograms in the tails, even the inclusion of thermal noise is oftentimes not sufficient to cover the range of environments that are expected. As a consequence, virtually all detectors try to reduce the large number of obtained false detections by relying on rather heuristic postprocessing steps. Consequently, they forfeit the crucial property of a constant false alarm rate. This paper proposes a novel statistical sea clutter model that describes the data more accurately, especially in challenging environments and thermal-noise limited cases. This new model stands out through its numerical simplicity, permitting efficient parameter adaptation thereby enhancing robustness and reducing computational complexity. Accordingly, the presented sea data model has the potential to replace the widely adopted K-distribution as model of choice for future operational applications. [ABSTRACT FROM AUTHOR]

This paper presents a method for the remote interrogation of batteryless humidity sensors based on statistical estimations and 3-D beam scanning techniques. As a proof-of-concept demonstration, a Van-Atta reflectarray sensor is interrogated with a 24-GHz frequency-modulated continuous-wave transceiver at various reading ranges. The extension of the proposed approach to passive or moving sensors is reported, and the measurement results are discussed. The relative humidity (RH) is derived from the statistical analysis of multidimensional radar echoes, while method is proposed to detect the sensor among clutter without knowing its exact position. Moreover, it is demonstrated that the cross-polarization effect of the Van-Atta reflectarray combined with the 3-D beam scanning technique allows the indoor measurement of the RH up to 58 m. [ABSTRACT FROM PUBLISHER]

Radar tracking of aircraft targets at low elevation angles can be complicated by clutter from wind turbines, which we define to be clutter. In this paper, we study detection in a staring pulse-Doppler radar. By exploiting the second-order correlation structure of this wind-turbine clutter we derive a target detector that uses a sequence of adaptive coherence scores. The detector uses a multipulse coherence statistic consisting of an incoherent geometric average of coherently computed adaptive coherence scores. The detector compares favorably to a multipulse coherence detector that uses no modeling or estimation of the clutter. [ABSTRACT FROM PUBLISHER]