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Non-cooperative targets, such as birds and unmanned aerial vehicles (UAVs), are typical low-altitude, slow, and small (LSS) targets with low observability. Radar observations in such scenarios are often complicated by strong motion clutter originating from sources like airplanes and cars. Hence, distinguishing between birds and UAVs in environments with strong motion clutter is crucial for improving target monitoring performance and ensuring flight safety. To address the impact of strong motion clutter on discriminating between UAVs and birds, we propose a frequency correlation dual-SVD (singular value decomposition) reconstruction method. This method exploits the strong power and spectral correlation characteristics of motion clutter, contrasted with the weak scattering characteristics of bird and UAV targets, to effectively suppress clutter. Unlike traditional clutter suppression methods based on SVD, our method avoids residual clutter or target loss while preserving the micro-motion characteristics of the targets. Based on the distinct micro-motion characteristics of birds and UAVs, we extract two key features: the sum of normalized large eigenvalues of the target's micro-motion component and the energy entropy of the time–frequency spectrum of the radar echoes. Subsequently, the kernel fuzzy c-means algorithm is applied to classify bird and UAV targets. The effectiveness of our proposed method is validated through results using both simulation and experimental data. [ABSTRACT FROM AUTHOR]

Forward‐looking radar imaging is a top priority due to a variety of applications. An airborne forward‐looking radar imaging approach via a modified propagator method (MPM) based on the planar phased array is proposed. It can obtain a better focusing effect without range migration correction. Through the MPM algorithm, the azimuth resolution can be enhanced greatly. Compared with the conventional synthetic aperture radar imaging algorithm, the left‐right ambiguity process can be avoided by generating two‐dimensional spatial spectra. Furthermore, the imaging results of different numbers of elements are given to provide an assessment of the imaging performance. Additionally, the authors proposed to apply the scanning planar phased array configuration to airborne forward‐looking two‐dimensional imaging for the first time. The validity of the method is proven by experiments. The image is more focused. Furthermore, the results of the experiments verify that the proposed method is fit for high‐speed situation and aircraft height variation condition. [ABSTRACT FROM AUTHOR]

This article introduces a comprehensive Mode-S radar simulation, designed to evaluate interrogation and reply signal functionality in various uplink formats (UFs) and downlink formats (DFs). Mode-S radar, crucial in modern aviation, facilitates communication between aircraft and ground systems, thereby enhancing aircraft tracking, situational awareness, and air traffic safety. Our simulation focuses on optimizing interrogation and reply sequences in the 1030- and 1090-MHz channels, respectively. It provides a practical solution for testing complex air flight scenarios, which may be impractical or costly in real life, by replicating challenging conditions in a computerized environment. This approach aids in developing advanced radar signaling algorithms for air traffic control. The simulator’s user-friendly interface displays real-time aircraft data, demonstrating its realworld applicability. Its successful operation underscores its potential to advance Mode-S radar technology and its value for research in the field. [ABSTRACT FROM AUTHOR]

The proposed "Guanlan" ocean science satellite, led by China's Laoshan Laboratory, includes an interferometric radar altimeter (IRA) as a key payload. As an integral part of its development, an airborne IRA experiment was conducted on 6 November 2021, with a flight path of approximately 90 km in the South China Sea. This study investigates the IRA's ability to observe ocean sea surface height (SSH) across scales ranging from meters to mesoscale. The sea surface height anomaly (SSHA) of the IRA is aligned with the SSHA of the AVISO at scales greater than 30 km, but also demonstrates the ability to capture small-scale SSHA changes in two dimensions. We analyzed wavenumber spectra of SSHA obtained from the airborne IRA, ICESat-2, and SARAL/AltiKa satellite for this region. The results show a good agreement in power spectral density (PSD) levels between ICESat-2, SARAL/AltiKa and IRA at scales larger than 30 km. Within the submesoscale range of 1–10 km, the IRA SSHA spectrum exhibits a distinctly negative slope and the lowest energy level. The minimum PSD level of the IRA fell in the range of 10−4–10−3 m2/cycle/km, at scales around 1 km, which is more than an order of magnitude lower than that of ICESat-2, forming a spectral gap that is in agreement with the theoretical expectation. Furthermore, IRA-derived wave direction and significant wave height matched well with the MFWAM wave data. The results of this study underscore the considerable potential of airborne IRA in capturing SSHA across a range of scales, from oceanic waves to submesoscale. [ABSTRACT FROM AUTHOR]

The structure and distribution of sub-glacial water directly influences Antarctic ice mass loss by reducing or enhancing basal shear stress and accelerating grounding line retreat. A common technique for detecting sub-glacial water involves analyzing the spatial variation in reflectivity from an airborne radar echo sounding (RES) survey. Basic RES analysis exploits the high dielectric contrast between water and most other substrate materials, where a reflectivity increase ≥ 15 dB is frequently correlated with the presence of sub-glacial water. There are surprisingly few additional tools to further characterize the size, shape, or extent of hydrological systems beneath large ice masses. We adapted an existing radar backscattering simulator to model RES reflections from sub-glacial water structures using the University of Texas Institute for Geophysics (UTIG) Multifrequency Airborne Radar Sounder with Full-phase Assessment (MARFA) instrument. Our series of hypothetical simulation cases modeled water structures from 5 to 50 m wide, surrounded by bed materials of varying roughness. We compared the relative reflectivity from rounded Röthlisberger channels and specular flat canals, showing both types of channels exhibit a positive correlation between size and reflectivity. Large (> 20 m), flat canals can increase reflectivity by more than 20 dB , while equivalent Röthlisberger channels show only modest reflectivity gains of 8–13 dB. Changes in substrate roughness may also alter observed reflectivity by 3–6 dB. All of these results indicate that a sophisticated approach to RES interpretation can be useful in constraining the size and shape of sub-glacial water features. However, a highly nuanced treatment of the geometric context is necessary. Finally, we compared simulated outputs to actual reflectivity from a single RES flight line collected over Thwaites Glacier in 2022. The flight line crosses a previously proposed Röthlisberger channel route, with an obvious bright bed reflection in the radargram. Through multiple simulations comparing various water system geometries, such as canals and sub-glacial lakes, we demonstrated the important role that topography and water geometry can play in observed RES reflectivity. From the scenarios that we tested, we concluded the bright reflector from our RES flight line cannot be a Röthlisberger channel but could be consistent with a series of flat canals or a sub-glacial lake. However, we note our simulations were not exhaustive of all possible sub-glacial water configurations. The approach outlined here has broad applicability for studying the basal environment of large glaciers. We expect to apply this technique when constraining the geometry and extent of many sub-glacial hydrologic structures in the future. Further research may also include comprehensive investigations of the impact of sub-glacial roughness, substrate heterogeneity, and computational efficiencies enabling more complex and complete simulations. [ABSTRACT FROM AUTHOR]

The paper explores the potential to enhance aviation safety, particularly in militarized regions, by outfitting aircraft with Side Looking Airborne Radar (SLAR) and employing space-time adaptive processing (STAP) algorithms. The research objective revolves around implementing a model of side-looking airborne radar and the corresponding STAP algorithms. This technology enables the detection of slow-moving targets amidst strong interference, encompassing both passive (clutter) and active (jammer) elements. Slow-moving targets relative to the aircraft's speed include tanks, combat vehicles, command vehicles, artillery, and logistical assets of enemy forces. The theoretical framework of space-time adaptive processing is presented, elucidating the sequential steps of the classical Sample Matrix Inversion Space-Time Adaptive Processing (SMI STAP) algorithm. The paper underscores the significance of characteristic parameters delineating a linear STAP processor. The proposed solution facilitates the detection of enemy combat measures and enhances aviation safety. It outlines a radar model installed beneath the aircraft's fuselage and elucidates algorithms for space-time adaptive processing of radar signals. The simulations conducted within the article were executed using the MATLAB environment. The simulation results indeed suggest that the proposed solution holds promise for deployment in equipping aircraft of one's own military and those engaged in operations within conflict zones. This paper stands as one of the few contributions in the literature addressing the augmentation of aircraft safety through radar and space-time adaptive processing. [ABSTRACT FROM AUTHOR]

Precipitation plays an important role in cloud and aerosol processes over the Southern Ocean (SO). The main objective of this study is to characterize SO precipitation properties associated with SO stratocumulus clouds. We use data from the Southern Ocean Clouds Radiation Aerosol Transport Experimental Study (SOCRATES), and leverage observations from airborne radar, lidar, and in situ probes. We find that for the cold‐topped clouds (cloud‐top‐temperature <0°C), the phase of precipitation with reflectivity >0 dBZ is predominantly ice, while reflectivity < −10 dBZ is predominantly liquid. Liquid‐phase precipitation properties are retrieved where radar and lidar are zenith‐pointing. Power‐law relationships between reflectivity (Z) and rain rate (R) are developed, and the derived Z–R relationships show vertical dependence and sensitivity to the presence of droplets with diameters between 10 and 40 μm. Using derived Z–R relationships, a reflectivity‐velocity (ZV) retrieval method, and a radar‐lidar retrieval method, we derive rain rate and other precipitation properties. The retrieved rain rate from all three methods shows good agreement with in‐situ aircraft estimates, with rain rates typically being quite light (<0.1 mm hr−1). We examine the vertical distribution of precipitation properties, and find that rain rate, precipitation number concentration, and precipitation liquid water all decrease as one gets closer to the surface, while precipitation size and distribution width increases. We also examine how cloud base rain rate (RCB) depends on cloud depth (H) and aerosol concentration (Na) for particles with a diameter greater than 70 nm, and find that RCB is proportional to H3.1Na−0.8 ${H}^{3.1}\,{N}_{a}^{-0.8}$. Plain Language Summary: Precipitation plays an important role over the Southern Ocean (SO), such as transferring water from the atmosphere to the ocean, and affecting clouds and aerosols (tiny airborne particles). This study aims to characterize SO precipitation properties using aircraft data that can count the number and size of cloud and precipitation droplets, as well as lidar and radar that measure light and microwaves respectively reflected by droplets. Using information from lidar, we can distinguish the precipitation phase, and we find that ice precipitation is more frequent when the amount of reflected energy measured by the radar (radar reflectivity) is larger than a certain threshold. We derived relationships between rain rate and radar reflectivity. We also find the precipitation properties inferred from radar and lidar data compare well with direct measurements from the aircraft, and the precipitation tends to be very light. We study how precipitation properties vary vertically, and find that as one gets closer to the surface, there is a decrease in precipitation droplet number and water, while there is an increase in the average size of droplets. We also find that rain rate depends on how thick the clouds are and the number of aerosols, consistent with theoretical expectations. Key Points: Liquid‐phase precipitation retrievals show good agreement with in situ observations and feature the prevalence of light rainReflectivity to rain rate relationships are developed, showing vertical dependence and sensitivity to the intermediate‐sized dropsThe below‐cloud precipitation phase with radar reflectivity >0 dBZ is mostly ice, while radar reflectivity <−10 dBZ is mostly liquid [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The inherent Doppler blind zone (DBZ) of airborne early warning radar can bring out target track termination with the worse effect in multi-target and clutter environment. Based on two-dimension assignment algorithm with DBZ information, a new plot-to-track association method based on multi-dimension assignment algorithm is proposed. Firstly, the evolution information of target track is used enough, and the radar's continuous multi-frame measurement data are used to perform sliding window processing. Secondly, the cost function of multi-dimension assignment is constructed. Finally, the solution of function on the condition of minimal cost is used as the targets plot-to-track assignment solution. The simulation results show that this method has further descent of track termination rate compared with two-dimension assignment algorithm in multi-target and clutter environment with DBZ. [ABSTRACT FROM AUTHOR]

When forming the radar situation of a terrain, in order to increase its information content and to extract useful information, multi-position spatially distributed systems for integrating multi-angle radar data established by small-sized UAV-based airborne radars are used. In this case, each radar station belonging to a multi-position system as a probing signal must have its own unique marked signal. Such a setup will allow the signals reflected from ground objects and zones to be "attached" to specific receiving-transmitting positions of the multi-position system. This requirement results from the fact that each transceiver position emits one probing signal, and then receives all the echo signals reflected from the underlying surface and previously emitted by other radar devices of the multi-position system. Such a setup of multi-position systems requires the researcher to look for and investigate specialized systems of marked code structures used to modulate the probing signals in order to identify them in a joint radar channel. Thus, the problem at hand is how to look for and investigate novel marked code structures used to generate a system of probing signals, the use of which will allow it to be "attached" to a specific receiving-transmitting position of a multi-position onboard system and to identify them in a joint radar channel in the course of the remote sensing of the underlying surface. The purpose of this work is to conduct a study on the subject of the squeak and choice of a system of code structures that have a low level of side lobes of autocorrelation functions and uniformly distributed values of the levels of the cross-correlation function. To achieve this goal, the relevance of the study is substantiated in the introduction. The second section analyzes the level of side lobes for classical and modified Barker codes with an asymmetric alphabet. On the basis of this analysis, it was concluded that it is expedient to apply this approach for codes longer than Barker codes. Therefore, in the third section, the features of the generation of M-sequences are considered. The fourth section presents a technique for searching for new marked code structures, taking into account their mutual correlation properties for modifying M-sequences in order to implement multi-positional systems. The fifth section presents computer experiments on the search for marked code structures based on the modifications of M-sequences and presents the numerical characteristics of the correlation properties of the considered marked codes. And finally, in the sixth section, the final conclusions of the study are presented and recommendations are given for their further practical application. The practical significance of this study lies in the fact that the proposed new marked code structures are necessary for the synthesis of probing signals in the implementation of spatially distributed systems that function for the high-probability detection and high-precision determination of the coordinates of physical objects and are also necessary for the formation of radar images in a multi-position mode. [ABSTRACT FROM AUTHOR]

Airborne radar plays a crucial role in detecting aerial targets, but its detection capability can be significantly affected by strong ground clutter when operating in down-looking mode. The range-Doppler (RD) results of ground clutter in airborne radar may overlap the range-Doppler results of the targets, causing target occlusion and rendering them undetectable. In addition to target detection, accurate extraction of target parameters is also of great importance. Due to the high-speed movement of the airborne platform, targets may exhibit range-Doppler ambiguity, necessitating the use of appropriate methods to resolve the range-Doppler ambiguity. Aiming at the problem of target occlusion by clutter with range-Doppler two-dimensional ambiguity during airborne radar down-looking target detection, this paper conducts a study on the detection of airborne radar down-looking targets based on orthogonal signals combined with pulse repetition frequency (PRF) staggered transmission. An optimization method is employed to design multiple sets of PRF values, aiming to reduce the radar blind zone. The range-Doppler two-dimensional ambiguity of targets is resolved using multiple sets of PRF, and coherent processing is performed on the corresponding echoes using the transmission intervals, maximizing the utilization of radar transmission energy. This approach enhances the signal-to-noise ratio (SNR) and improves the detection performance and parameter estimation accuracy, particularly for low SNR targets. The superiority of the proposed approach is demonstrated through simulation experiments. [ABSTRACT FROM AUTHOR]

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Many studies have performed microphysical retrievals using radars of different frequencies, platforms, and methodologies. However, little is known about the consistency of retrievals derived from different radar platforms (i.e., airborne or spaceborne vs. ground‐based) and their methodologies. This study is the first to directly compare snow mass‐weighted mean diameter (Dm) retrievals from both nadir‐pointing airborne multi‐frequency radars and ground‐based polarimetric range‐height indicator radar scans along the same airborne flight track with a resolution of O(10m) $\mathcal{O}(10\,\mathrm{m})$. Dm retrievals between each method produced mean absolute errors of 0.49, 0.74, and 0.93 mm where the largest differences were between the ground and aircraft retrievals. A triple‐frequency analysis suggests the possibility that snow aggregates were generally composed of needles. These results can be used as a benchmark for comparing retrieval methodologies and highlight the continued uncertainty regarding the optimal approach for ice microphysical retrievals. Plain Language Summary: Both airborne and ground‐based weather radar measurements can be used to estimate snowflake characteristics such as their mean size. However, it is difficult to compare the radar‐estimated mean sizes between these platforms because of the vast methodological differences in how these sizes are estimated and the spatial and temporal differences resulting from each radar's geographical location. This study is the first to directly compare snowflake size retrievals using ground‐based mobile radar scans that collected data along the same path as an overhead‐passing aircraft, thus directly minimizing any error resulting from matching values between radars aboard the aircraft and the ground radar. We also used the aircraft radars' multiple frequencies to investigate what types of particles were dominant throughout the storm. Through this multi‐frequency analysis, we found that it is possible that snow particles were aggregates of thin needles that were stuck together. These results can be used by other researchers and forecasters to understand how snowflake size estimates can vary between different platforms and methodologies. Key Points: Mobile X‐band polarimetric radar Range Height Indictor scans were directly collocated with overpassing multi‐frequency airborne radars during a snowstormThree separate mass‐weighted mean diameter retrievals had mean absolute errors of 0.49, 0.74, and 0.93 mm between each otherThese results provide a one‐of‐a‐kind, high‐resolution benchmark for comparing retrieval methods across various platforms [ABSTRACT FROM AUTHOR]

Space-time adaptive processing (STAP) is an important method of clutter suppression that requires adequate training samples. For an airborne conformal array radar, conventional STAP methods do not have enough training samples to acquire good performance due to the range dependent clutter caused by geometry and the problem of polarization. Sparse-recovery-based STAP (SR-STAP) methods have garnered significant attention in the past few decades because they only require a small number of training samples. Sparse Bayesian Learning (SBL) methods have seen increasing amounts of development due to its robust, self-regularizing nature and because it is not sensitive to user parameters, but it converges slowly. In this paper, a novel fast SBL (NFSBL) method is put forward to increase the rate of convergence. To minimize the SBL penalty function, the proposed method introduces the conjugate function to construct a surrogate function. Additional solution sparsity will be achieved through iteratively minimizing the surrogate function. Then, from the proposed method, we could obtain a more accurate clutter plus noise covariance matrix. Numerical simulation results express that this method could acquire better performance of STAP and improvement in convergence and computational complexity for a conformal array. [ABSTRACT FROM AUTHOR]

Wind-driven redistribution of snow on sea ice alters its topography and microstructure, yet the impact of these processes on radar signatures is poorly understood. Here, we examine the effects of snow redistribution over Arctic sea ice on radar waveforms and backscatter signatures obtained from a surface-based, fully polarimetric Ka- and Ku-band radar at incidence angles between 0 ∘ (nadir) and 50 ∘. Two wind events in November 2019 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition are evaluated. During both events, changes in Ka- and Ku-band radar waveforms and backscatter coefficients at nadir are observed, coincident with surface topography changes measured by a terrestrial laser scanner. At both frequencies, redistribution caused snow densification at the surface and the uppermost layers, increasing the scattering at the air–snow interface at nadir and its prevalence as the dominant radar scattering surface. The waveform data also detected the presence of previous air–snow interfaces, buried beneath newly deposited snow. The additional scattering from previous air–snow interfaces could therefore affect the range retrieved from Ka- and Ku-band satellite altimeters. With increasing incidence angles, the relative scattering contribution of the air–snow interface decreases, and the snow–sea ice interface scattering increases. Relative to pre-wind event conditions, azimuthally averaged backscatter at nadir during the wind events increases by up to 8 dB (Ka-band) and 5 dB (Ku-band). Results show substantial backscatter variability within the scan area at all incidence angles and polarizations, in response to increasing wind speed and changes in wind direction. Our results show that snow redistribution and wind compaction need to be accounted for to interpret airborne and satellite radar measurements of snow-covered sea ice. [ABSTRACT FROM AUTHOR]

Melting and refreezing processes in the firn of the Devon Ice Cap control meltwater infiltration and runoff across the ice cap, but their full spatial extent and effect on near-surface structure is difficult to measure with surface-based traverses or existing satellite remote sensing. Here, we derive the coherent component of the near-surface return from airborne ice-penetrating radar surveys over the Devon Ice Cap, Canadian Arctic, to characterize firn containing centimeter- to meter-thick ice layers (i.e., ice slabs) formed from refrozen meltwater in firn. We assess the use of dual-frequency airborne ice-penetrating radar to characterize the spatial and vertical near-surface structure of the Devon Ice Cap by leveraging differences in range resolution of the radar systems. Comparison with reflectivities using a thin layer reflectivity model, informed by surface-based radar and firn core measurements, indicates that the coherent component is sensitive to the near-surface firn structure composed of quasi-specular ice and firn layers, limited by the bandwidth-constrained radar range resolution. Our results suggest that average ice slab thickness throughout the Devon Ice Cap percolation zone ranges from 4.2 to 5.6 m. This implies conditions that can enable lateral meltwater runoff and potentially contribute to the total surface runoff routed through supraglacial rivers down glacier. Together with the incoherent component of the surface return previously studied, our dual-frequency approach provides an alternative method for characterizing bulk firn properties, particularly where high-resolution radar data are not available. [ABSTRACT FROM AUTHOR]

As a tropical cyclone (TC) intensifies, the tangential wind field expands vertically and increases in magnitude. Observations and modeling support vortex height as an important TC structural characteristic. The Tropical Cyclone Radar Archive of Doppler Analyses with Recentering data set provides kinematic analyses for calculation of the height of the vortex (HOV) in observed storms. Analyses are azimuthally‐averaged with tangential wind values taken along the radius of maximum winds. A threshold‐based technique is used to determine the HOV. A fixed threshold HOV strongly correlates with current intensity. A dynamic HOV metric quantifies vertical decay of tangential wind with reduced dependency on intensity. Statistically significant differences are present between dynamic HOV values in groups of steady‐state, intensifying, and rapidly‐intensifying cases categorized by subsequent changes in pressure. A tall vortex is always observed in cases meeting a pressure‐based rapid intensification definition. Taller vortices are also evident with slower intensification. Results suggest HOV may be a helpful predictor for TC intensification. Plain Language Summary: As a tropical cyclone gets stronger, the wind field of the storm grows taller in the atmosphere. The height‐intensity relationship is known to be present from the beginning of a tropical cyclone until its peak strength. A large data set of airborne radar observations in tropical cyclones is used to show the strength of the relationship between vortex height and current intensity. A tall vortex is always present in observed cases for periods of rapid intensification during which the minimum surface pressure at the storm center drops at a high rate. Drops in minimum surface pressure are associated with increases in wind and size in tropical cyclones. A taller vortex also favors intensification at slower rates. Improved understanding of the role that tropical cyclone height plays during intensification may be helpful for forecasting changes in intensity of these storms. Key Points: Vertical extent of the tropical cyclone wind field correlates strongly with current intensity in observed stormsDeep vertical vortex structure is always present in observed cases meeting a pressure‐based rapid intensification definitionVortex height decreases with increasing vertical wind shear, but taller storms intensify more in moderate shear [ABSTRACT FROM AUTHOR]

Aimingat non-side-looking airborne radar, we propose a novel unsupervised affinity propagation (AP) clustering radar detection algorithm to suppress clutter and detect targets. The proposed method first uses selected power points as well as space-time adaptive processing (STAP) weight vector, and designs matrix-transformation-based weighted input data, with which the first unsupervised weighted AP clustering is proposed by means of their similarity matrix, responsibility values and availability values. Then, new reconstructed weighted power inputs are designed, and the second weighted AP clustering is proposed. Finally, with their cluster results, a detection-discriminant criterion is designed for the judgment of target detection, and simultaneously, the clutter is suppressed. Compared with the conventional and important STAP, ADC and JDL algorithms, and several SO-based, GO-based and OS-based CFAR algorithms, the proposed unsupervised algorithm achieves much higher probability of detection and provides distinctly superior target-detection performance. With reasonable computation time, it can better conquer the range dependence in characteristic of clutter and better process non-independent identically distributed (non-IID) samples of non-side-looking radar. Sufficient simulations are performed, and they demonstrate that the proposed unsupervised algorithm is preferable and advantageous. [ABSTRACT FROM AUTHOR]

To meet the needs of flight teaching and training, aiming at the interactive, multi-input multi-output and comprehensive sequential logic controlling characteristic of integrated avionics system display and control interface for fighters, a functional simulation method by designing display and control logic independently is introduced. On the basis of this structure, a loosely coupled, modular and visual simulation method of display and control interface for multi-function fire control radar is presented, and the realization of display and control logic based on Simulink/Stateflow is introduced. The application result shows that the program progress is more intuitive, and the code is more maintainable, so this design method can improve the fidelity and developing efficiency of display and control simulation. All these researches can provide technology reference for the simulation of display and control interfaces for avionics systems and its subsystems. [ABSTRACT FROM AUTHOR]

Radars used by air-crafts have two important characteristics; First, they should have a real-time signal processing system finishing signal processing before deadline while getting and processing successive in-phase and quadrature data. Second, they can cover a lot of modes including A2A(Air to Air), A2G(Air to Gound), A2S(Air to Sea), and Ground Map(GM). So the structure of radar signal processing SWs in modern airborne radars are becoming more complicate. Also, the implementation of radar signal processing SW needs to reuse common code blocks between other modes for efficiency or change some of the code blocks into alternative algorithm blocks. These are the reason why the radar signal processing SW framework suggested in this paper is taking advantage of modular programming. This paper proposes an modular framework applicable on the airborne radar signal processing SW maintaining the real-time characteristic using the signal processing procedures for A2G/A2S as examples. [ABSTRACT FROM AUTHOR]

Dual-wavelength (3.2 and 0.32 cm , i.e., X- and W-radar bands) radar ratio (DWR) measurements in ice clouds and precipitation using Canada's National Research Council Institute for Aerospace Research airborne radar are compared to closely collocated particle microphysical in situ sampling data in order to develop relations between DWR and characteristic hydrometeor size. This study uses the radar and in situ data sets collected during the In-Cloud ICing and Large-drop Experiment (ICICLE) campaign in midlatitude frontal clouds. Since atmospheric particle scattering at X band is predominantly in the Rayleigh regime and the W-band frequency is the highest frequency usually used for hydrometeor remote sensing, the X–W-band combination provides a relatively strong dual-wavelength reflectivity difference. This study considers radar and in situ measurements conducted in relatively homogeneous cloud and precipitation conditions. Measurements show that under these conditions, the difference between the X-band radar reflectivities observed with vertical and horizontal pointing of the radar beam are generally small and often negligible. However, W-band reflectivities at vertical beam pointing are, on average, larger than those for horizontal beam pointing by about 4 dB , which is a non-Rayleigh scattering effect from preferentially oriented non-spherical particles. A horizontal radar beam DWR–mean volume particle size relation, Dv , provides robust estimates of this characteristic size for populations of particles with different habits. Uncertainties of Dv retrievals using DWR are around 0.6 mm when Dv is greater than approximately 1 mm. Size estimates using vertical radar beam DWRs have larger uncertainties due to smaller dual-wavelength signals and stronger influences of hydrometeor habits and orientations at this geometry of beam pointing. Mean relations among different characteristic sizes, which describe the entire particle size distribution (PSD), such as Dv , and other sizes used in various applications (e.g., the mean, effective, and median sizes) are derived, so the results of this study can be used for estimating different PSD characteristic sizes. [ABSTRACT FROM AUTHOR]

In order to quantitatively evaluate the influence of the aberration of the antenna radiation pattern of airborne radar on clutter feature, the range‐azimuth two dimensional (2D) model of the airborne radar clutter is established. Then the theoretic modelling and simulation analysis are proposed in three aspects, including the Doppler, power spectrum and space‐time 2D characteristics of the clutter. Finally, the processing of moving target indication, pulse Doppler and space‐time adaptive processing are used to suppress the clutter of the echo signals before and after the aberration. The results of the simulations indicate the aberration would elevate the sidelobe level, extend the power spectrum and bend the space‐time trajectory of the clutter Doppler spectra. And the residual clutter would be elevated nearly 5 dB after STAP processing. Then the pattern preserving and fast time cancel combined space‐time adaptive processing method is proposed, which can obtain narrow clutter notch and large improvement factor, and effectively suppress clutter. The modelling and quantitative analysis study have important theoretical and engineering significance for the detection capability of the airborne radar installed on the fuselage of the aircraft platform, the tactical and technical performance index, and improving the signal processing ability of airborne radar. [ABSTRACT FROM AUTHOR]

It is challenging to design complex structures and calculate their dimensions only on the basis of theory. This issue was resolved efficiently by the FEM. Using the applicable test, the mechanical properties of the materials used in the damper are estimated, effectively guiding the design of the device and boosting its vibration-reducing performance. A large-load unmanned aerial vehicle (UAV) airborne radar is the subject of this research article. According to particular use case, vibration dampers for the radar-mounting platform are designed using passive vibration isolation technology to reduce aircraft vibration transmission to the radar. A conference paper has already presented prior research on the same topic. Earlier research confirmed the vibration-isolating efficacy of the T-type rubber isolator, which can greatly improve the operational conditions of the airborne radar. In contrast, earlier studies relied more on experimental validation and did not use numerical simulations. This research's primary objective is the development of a T-type rubber isolator, whose vibration reduction performance is proven using FEM and experiments. Utilizing a suitable simulation analysis method to investigate the vibration reduction of an unmanned aerial vehicle's (UAV) airborne component is a crucial technical task. By comparing multiple material models, a more precise model for characterizing rubber was developed. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to study the space-time characteristics of sea clutter, the sea clutter is always measured by the airborne multichannel radar; however, the sea clutter shows the heterogeneity between range gates, which means the space-time covariance matrix's correspondence to the single range gate cannot be estimated accurately. Meanwhile, the measurement of the sea clutter data by the airborne radar is usually affected by the motion of the platform, which makes the analysis results unrepresentative of the space-time characteristics of the pure sea clutter. In this paper, a sea clutter measurement method based on L-band shore-based multichannel radar is proposed, where the transmit sub-array periodically moves with the pulse repetition period to obtain multiple sets of coherent processing interval pulses for each range gate. This measurement method can exclude the influences of the moving platform. Moreover, a sea clutter space-time signal model of the single range gate is proposed, and the model is used to simulate three-dimensional sea clutter data with space-time coupling characteristics. With verification of the measured and simulated data, it can be seen that the data composed of single range gate and multiple coherent processing interval pulses can accurately estimate the space-time covariance matrix corresponding to this single range gate. Furthermore, the space-time characteristics are analyzed based on the measured data. The results show that the eigenvalue spectrum and the spread width of space-time power spectrum are influenced by the backscattering coefficient of sea clutter and the speed of sea surface motion. In comparison, the decorrelation effect caused by the backscattering coefficient of sea clutter is stronger than that caused by the speed of the surface motion. The proposed method is helpful for guiding multichannel sea clutter measurement and the analysis results are of great significance to the clutter suppression algorithms of the marine multichannel radar. [ABSTRACT FROM AUTHOR]

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To enhance the system performance of airborne radar in a limited‐sample environment, a robust sparsity‐based tri‐iterative space‐time adaptive processing (RSBTI‐STAP) method is proposed here. First, the proposed RSBTI‐STAP method constructs the clutter dictionary matrix by exploiting the a priori knowledge of radar platform. Next, the clutter representation coefficient, array error and weighted vectors are iteratively updated until convergence so as to obtain the estimated values of these three parameters. Finally, combined with the estimated clutter representation coefficient and array error vectors, the STAP weight vector is calculated for the purpose of clutter suppression. The proposed method can be robust to the array amplitude/phase error and can be free of the hyperparameters. Additionally, it does not need the training samples and has the global convergent properties. Numerical experiments based on the simulated data demonstrate the effectiveness of the proposed RSBTI‐STAP method. [ABSTRACT FROM AUTHOR]

Airborne Frequency Diversity Array (FDA) radar operating at a high pulse repetition frequency encounters severe range-ambiguous clutter. The slight frequency increments introduced by the FDA result in angle and range coupling. Under these conditions, conventional space-time adaptive processing (STAP) often exhibits diminished performance or fails, complicating target detection. This paper proposes a method combining elevation oblique subspace projection with azimuth-Doppler STAP to suppress range-ambiguous clutter. The method compensates for the quadratic range dependence by analyzing the relationship between elevation frequency and range. It uses an elevation oblique subspace projection technique to construct an elevation adaptive filter, which separates clutter from ambiguous regions. Finally, residual clutter suppression is achieved through azimuth-Doppler STAP, enhancing target detection performance. Simulation results demonstrate that the proposed method effectively addresses range dependence and ambiguity issues, improving target detection performance in complex airborne FDA radar environments. [ABSTRACT FROM AUTHOR]

Drones and drone swarms, characterized by their low price and ease of deployment, are being utilized to launch assaults, and presenting a great threat to the public and homeland security in recent years. Countering drones or drone swarms is thus of great significance. Some effective counter approaches for a small group of drones have been studied. However, these approaches may be insufficient to counter a large-scale drone swarm due to the lack of efficient time-saving detecting technologies. Towards this end, this paper proposes a fast counter approach to deprive the drone swarm of its coordination and clustering capabilities in a short time by splitting the drone swarm into several unconnected components. To achieve efficient splitting, two efficient algorithms for searching critical nodes are proposed, namely, the genetic algorithm and the particle swarm optimization algorithm. Extensive simulation results are presented to validate the superior performances of the proposed two algorithms for splitting the drone swarms in different formations. The results show that the drone swarms lose their coordination ability as they are forced to split into multiple components with a constraint of group size. The high accuracy and efficiency of the proposed algorithms are also verified by a series of comparative experiments. [ABSTRACT FROM AUTHOR]

Herein, we implement a software-in-loop simulation (SILS) system for fighter radar systems. The implemented SILS system simulates fighter radar environments and hardware by mathematical modeling, generates radar-simulated digital signals, and stores/analyzes simulation results. It includes a personal computer (PC)-based virtual radar processing unit, which can be used to develop radar control and process algorithms and codes and can also examine the functions and performance of the software and code of actual radar processing equipment by connecting actual equipment. Because antenna and transceiver models are included, the performance of the initial hardware designs at the system level can be examined in the simulation environment, thereby increasing the hardware design and development speed. We demonstrate the validity and usefulness of the SILS system, implemented using the radar environment and hardware mathematical models obtained from the development of fighter radars for numerous years, through SILS-based test results. [ABSTRACT FROM AUTHOR]

When a missile-borne radar system works in downward-looking surveillance mode, the broadened ground clutter signal in virtue of platform high-speed motion will be received by the radar receiver, which will cause difficulty in moving target detection and attacking. Unlike airborne and spaceborne platforms, a missile-borne platform exhibits some unique motion characteristics, such as diving, spinning, and coning, causing the clutter space–time distribution property significantly different from those of airborne and spaceborne radar platforms. In addition, the forward target striking requirements make the missile-borne clutter space–time spectrum further exhibit the severe range-dependent property. To deal with these issues, accurate motion modeling of a missile-borne radar platform is first carried out in this article, where the complex platform motions including forward-looking diving, spinning, and coning are considered. Then, the autocorrelation processing combined with iterative adaptive approach is applied to estimate the clutter angle-Doppler center frequencies, so as to effectively realize the clutter nonstationary compensation along spatial and temporal directions. Finally, a time-domain sliding window-based subspace projection method is proposed to achieve the robust clutter suppression. Both simulation and real-measured radar data processing results are presented to validate the effectiveness and feasibility of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In an airborne maritime radar, inverse synthetic aperture radar (ISAR) is used to image and classify non-cooperative targets. In this article, we investigate a 3D-ISAR as an alternative representation that can potentially improve the final target classification by automatically extracting key features from the radar data, such as the length, width, and height of a target. The technique works by estimating the target scatterers’ positions using measurements from multiple ISAR images. This has previously been achieved using a single receive channel that exploits the temporal motion of the target or with a multichannel dual-baseline interferometric system that uses the phase differences in both the along- and across-track directions. In this article, we combine aspects of these two techniques using a single along-track baseline suitable for airborne maritime radar systems. [ABSTRACT FROM AUTHOR]

Space-time adaptive processing (STAP) is an effective technology in clutter suppression and moving target detection for airborne radar. Because airborne radar moves at a constant acceleration, and there is a lack of independent and identically distributed (IID) training samples caused by the heterogeneous environment, using the conventional STAP methods directly cannot ensure a good performance. To eliminate these effects and improve the performance of clutter suppression, a STAP method based on a sparse Bayesian learning (SBL) framework for uniform acceleration radar is proposed here. This paper introduces the signal model of the uniform acceleration radar. To promote the sparsity, a generalized double Pareto (GDP) prior is introduced into our method, and the estimation of hyper parameters via expectation maximization (EM) is given. The effectiveness of the proposed method is demonstrated by simulations. [ABSTRACT FROM AUTHOR]

This article presents detailed geometric analyses of ground clutter in bistatic passive airborne radars. Analytic closed-form solutions are derived for finding the intersection of iso-ranges and iso-velocities. This allows clutter bistatic coordinates to be easily converted to its Cartesian coordinates. Based on those solutions, a theoretical clutter map in the bistatic coordinates can be calculated assuming uniform clutter distribution on the Earth’s surface. This is done by first converting a resolution cell in the bistatic coordinates into a corresponding cell in the Cartesian coordinates. Next, the power distribution in the bistatic coordinates is calculated taking into account range dependency, incident angles, and the radiation patterns of the transmitter and the receiver. The aim of this analysis is to characterize clutter in terms of expected mean power map rather than in terms of statistical distribution. The obtained results provide insights into the expected characteristics of clutter, which can be helpful in designing signal processing algorithms for ground moving target indication (GMTI) and synthetic aperture radar (SAR). The theoretical clutter distribution on the range-velocity map is compared with real-life data acquired with a Digital Video Broadcasting–Terrestrial (DVB-T)-based passive radar and good agreement between theory and measurement is presented. [ABSTRACT FROM AUTHOR]

A target-tracking method using the ground moving target indicator (GMTI) mode on active electronically scanned array (AESA) radar is proposed. The GMTI mode can operate in wide ground areas. However, the 3-dB beamwidth of the X-band radar is narrow, and a target is detected on multiple adjacent beams. To delete overlapping target plots, beam-to-beam processing considering a real-time system is proposed. In addition, a track while scan (TWS) multiple-target-tracking algorithm was constructed for the system. Through a flight test with true car mounted GPS, it was confirmed that the real-time processing ability and target-tracking performance of the GMTI algorithm were satisfactory. [ABSTRACT FROM AUTHOR]

An airborne radar echo signal includes signals returned from clutter and a target; thus, simulating the signal from the clutter may be crucial for predicting and analyzing accurate radar performance. Because it can be extremely difficult and expensive to obtain real measured signal data for various scenarios, an accurate signal generation method is required. Existing weather clutter and ground clutter simulators for an X-band airborne radar are combined to simulate the echo signal when two clutters exist simultaneously. The weather clutter effect becomes more significant with increasing frequencies, such as in the X-band. The proposed simulator can generate time-do- main signals by considering the random characteristics of the clutter signal and the Doppler effect caused by the movement of aircraft and clutter. In addition, a simple scheme is proposed for generating signals from artificial structures. Finally, the finite bandwidth of the transmitted chirp signal is calculated to improve the accuracy of the generated signal. [ABSTRACT FROM AUTHOR]

Over the past 50 years, the British Antarctic Survey (BAS) has been one of the major acquirers of aerogeophysical data over Antarctica, providing scientists with gravity, magnetic, and radar datasets that have been central to many studies of the past, present, and future evolution of the Antarctic Ice Sheet. Until recently, many of these datasets were not openly available, restricting further usage of the data for different glaciological and geophysical applications. Starting in 2020, scientists and data managers at BAS have worked on standardizing and releasing large swaths of aerogeophysical data acquired during the period 1994–2020, including a total of 64 datasets from 24 different surveys, amounting to ∼ 450 000 line-km (or 5.3 million km 2) of data across West Antarctica, East Antarctica, and the Antarctic Peninsula. Amongst these are the extensive surveys over the fast-changing Pine Island (BBAS 2004–2005) and Thwaites (ITGC 2018–2019 & 2019–2020) glacier catchments, and the first ever surveys of the Wilkes Subglacial Basin (WISE-ISODYN 2005–2006) and Gamburtsev Subglacial Mountains (AGAP 2007–2009). Considerable effort has been made to standardize these datasets to comply with the FAIR (findable, accessible, interoperable and re-usable) data principles, as well as to create the Polar Airborne Geophysics Data Portal (https://www.bas.ac.uk/project/nagdp/ , last access: 18 July 2022), which serves as a user-friendly interface to interact with and download the newly published data. This paper reviews how these datasets were acquired and processed, presents the methods used to standardize them, and introduces the new data portal and interactive tutorials that were created to improve the accessibility of the data. Lastly, we exemplify future potential uses of the aerogeophysical datasets by extracting information on the continuity of englacial layering from the fully published airborne radar data. We believe these newly released data will be a valuable asset to future glaciological and geophysical studies over Antarctica and will significantly extend the life cycle of the data. All datasets included in this data release are now fully accessible at https://data.bas.ac.uk (British Antarctic Survey, 2022). [ABSTRACT FROM AUTHOR]

The retrieval of continuous ice core records of more than 1 Myr is an important challenge in palaeo-climatology. For identifying suitable sites for drilling such ice, knowledge of the subglacial topography and englacial layering is crucial. For this purpose, extensive ground-based ice radar surveys were carried out over Dome Fuji in the East Antarctic plateau during the 2017/18 and 2018/19 austral summers by the Japanese Antarctic Research Expedition, on the basis of ground-based radar surveys conducted over the previous ∼ 30 years. High-gain Yagi antennae were used to improve the antenna beam directivity, thereby significantly decreasing hyperbolic features of unfocused along-track diffraction hyperbolae in the echoes from mountainous ice–bedrock interfaces. We combined the new ice thickness data with the previous ground-based data, recorded since the 1980s, to generate an accurate high-spatial-resolution (up to 0.5 km between survey lines) ice thickness map. This map revealed a complex landscape composed of networks of subglacial valleys and highlands. Based on the new map, we examined the roughness of the ice–bed interface, the bed surface slope, the driving stress of ice and the subglacial hydrological condition. These new products and analyses set substantial constraints on identifying possible locations for new drilling. In addition, our map was compared with a few bed maps compiled by earlier independent efforts based on airborne radar data to examine the difference in features between datasets. Our analysis suggests that widely available bed topography products should be validated with in situ observations where possible. [ABSTRACT FROM AUTHOR]

Ambiguity clutter for airborne radar systems is usually caused by a uniform pulse repetition interval (UPRI) waveform, which significantly degrades target detection and location performance. To address this issue, this article proposes an ambiguity clutter suppression method resorting to a pseudorandom pulse repetition interval (PrPRI) waveform. First, an airborne radar clutter model accounting for multiple range rings with PrPRI waveform is developed. Next, a nonuniform coherent processing framework is introduced to eliminate the clutter folded in the range and Doppler domain. In particular, the reasons for the enlargement of the area free of clutter corresponding to PrPRI mode are analyzed, as well as the maximum unambiguous Doppler frequency, maximum unambiguous range, and design principles for PRI are derived. Finally, numerical examples are designed to verify that the nonuniform coherent processing framework can enlarge the clutter-free area and achieve unambiguity target detection and location. [ABSTRACT FROM AUTHOR]

Consider the moving target detection performance degradation of airborne multiple-input multiple-output (MIMO) radar in the presence of inaccurate target prior information. This paper proposes a joint design method of transmit waveform and receive filter bank of airborne MIMO radar based on feasible point pursuit successive convex approximation (FPP-SCA). Firstly, a set of receive filter banks is designed in the region where the target may appear on the angle-Doppler plane, and the worst-case output signal-to-clutter-plus-noise ratio (SCNR) is maximized as the optimization criterion. Secondly, considering the energy constraint and similarity on the transmit waveform, the maximin joint design problem is formulated to improve the robustness of the MIMO space-time adaptive processing (STAP) radar against the uncertainty of target parameters. Finally, an FPP-SCA algorithm is employed to solve the maximin nonconvex joint design problem. Simulation results demonstrate the effectiveness of the proposed method in terms of better output SCNR, lower computational load, and more robustness against the errors of target parameters. [ABSTRACT FROM AUTHOR]

Dual-wavelength (3.2 and 0.32 cm, i.e., X- and W-radar bands) radar ratio (DWR) measurements in ice clouds and precipitation using the Canada's National Research Council Institute for Aerospace Research airborne radar are compared to closely collocated particle microphysical in situ sampling data in order to develop relations between DWR and characteristic hydrometeor size. This study uses the radar and in situ data sets collected during the In-Cloud ICing and Large-drop Experiment (ICICLE) campaign. Since atmospheric particle scattering at X-band is predominately in the Rayleigh regime and the W-band frequency is the highest frequency usually used for hydrometeor remote sensing, the X-Wband combination provides relatively strong dual-wavelength reflectivity difference. This study considers radar and in situ measurements conducted in relatively homogeneous cloud and precipitation conditions. Measurements show that under these conditions, the difference between the X-band radar reflectivities observed with vertical and horizontal pointing of the radar beam are generally small and often negligible. However, W-band band reflectivities at vertical beam pointing are, on average, larger than those for horizontal beam pointing by about 4 dB, which is a non-Rayleigh scattering effect from oriented non-spherical particles. A horizontal beam DWR - mean volume particle size, Dv, relation provides robust estimates of this characteristic size for populations of particles with different habits. Uncertainties of Dv retrievals using DWR are around 0.6 mm when Dv is greater than approximately 1 mm. Size estimates using vertical radar beam DWRs have larger uncertainties due to smaller dual-wavelength signals and stronger influences of hydrometeor habits and orientations at this geometry of beam pointing. Mean relationships among different characteristic sizes describing the entire particle size distribution (PSD) such as Dv, and other characteristic sizes used in different applications (e.g., the mean, effective, and median sizes) are derived, so the results of this study can be used for estimating different PSD characteristic sizes. [ABSTRACT FROM AUTHOR]

The signal coherence on target is vulnerable toconfiguration perturbationsof an airborne distributed radar system where radar nominal positions are disturbed by unknown position errors to radar actual positions in three-dimensional space. This article copes with the configuration calibration problem of an airborne distributed radar system using several auxiliary devices in known locations, e.g., ground auxiliary receivers. To warrant parameter identifiability, for given transmitted signals from radars, two types of echoes are exploited, including the internal ones received by radars and external ones received by auxiliary receivers. The range measurements can be extracted from these echoes subsequently. The theoretical analysis claims that an identifiability condition for configuration calibration, precluding pathological configurations, is to have at least two auxiliary receivers when the location of one radar is known. Besides, configuration calibration is a highly nonlinear problem due to the coupling of position errors between two different radars and to the existence of second-order position error terms in the range measurement equations. We introduce the novel idea of auxiliary ranges to eliminate the second-order position error terms and the iterative fashion to handle the coupling in the methodology to enable the formulation of pseudolinear equations, thereby leading to the establishment of an algebraic solution for radar position estimation. Numerical simulations are included to corroborate the theoretical results and to demonstrate the superiority of the devised method in comparison with the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The optimization of normalized radar cross-section (NRCS) sampling by a scatterometer allows an increase in the accuracy of the wind retrieval over the water surface and a decrease in the time of the measurement. Here, we investigate the possibility of improving wind vector measurement with an airborne rotating-beam scatterometer mounted under the fuselage. For this purpose, we investigated NRCS sampling at various incidence angles, and the possibility of using NRCS samples obtained during simultaneous measurement at different incidence angles to perform wind retrieval. The proposed wind algorithms are based on a geophysical model function (GMF). Sea wind retrieval was carried out using Monte Carlo simulations with consideration of a single incidence angle or combinations of several incidence angles. The incidence angles of interest were 30°, 35°, 40°, 45°, 50°, 55°, and 60°. The simulation showed that the wind speed error decreased with an increase in the incidence angle, and the wind direction error tended to decrease with an increase in the incidence angle. The single incidence angle case is characterized by higher maximum wind retrieval errors but allows for a higher maximum altitude of the wind retrieval method's applicability to be achieved. The use of several neighboring incidence angles allows a better wind vector retrieval accuracy to be achieved. The combinations of three and four incidence angles provided the lowest maximum wind speed and direction errors in the range of the incidence angles from 45° to 60° but, unfortunately, provide the lowest maximum altitude of applicability of the wind retrieval method. At the same time, the combination of two incidence angles is characterized by slightly higher maximum wind retrieval errors than in the cases of three and four incidence angles, but they are lower than in the case of the single incidence angle. Moreover, the two incidence angles' combination is a simpler way to decrease the wind retrieval errors, especially for measurement near an incidence angle of 30°, providing nearly the highest maximum altitude of the wind retrieval method applicability. The results obtained can be used to enhance existing airborne radars and in the development of new remote sensing systems. [ABSTRACT FROM AUTHOR]

Airborne multichannel high-resolution radar (HRR)-ground moving target indication (GMTI) is of great significance to wide-area surveillance, traffic monitoring, and target recognition. The Aerospace Information Research Institute, Chinese Academy of Sciences, produced an advanced airborne digital array radar with high resolution and conducted an experiment with slow and weak cooperative moving targets in 2021. In this article, an overall processing framework for target detection, parameter estimation, and target tracking using this system is introduced. For HRR detection, the echo energy of targets is spread into multiple range units, so-called range-spread targets; thus, using detectors designed for pointlike targets will severely degrade the detection performance, especially for slow and weak targets. To address the adaptive detection of such range-spread targets embedded in Gaussian clutter with an unknown covariance matrix, a novel two-step generalized space–time adaptive processing (GSTAP) algorithm is proposed, which offers an enhanced clutter suppression capability compared with natural competitors. Moreover, a tracking method is implemented in the range-Doppler domain to avoid track loss caused by azimuth relocation error and reject discrete false alarms. Both simulation and experimental results are presented to demonstrate the effectiveness of the proposed method and provide a paradigm for further research. [ABSTRACT FROM AUTHOR]

This paper describes a technique for identifying hydrometeor particle types using airborne HIAPER Cloud Radar (HCR) and High Spectral Resolution Lidar (HSRL) observations. HCR operates at a frequency of 94 GHz (3 mm wavelength), while HSRL is an eye‐safe lidar system operating at a wavelength of 532 nm. Both instruments are deployed on the NSF‐NCAR HIAPER aircraft. HCR is designed to fly in an underwing pod and HSRL is situated in the cabin. The HCR and HSRL data used in this study were collected during the Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES). Comprehensive observations of the vertical distributions of liquid and mixed‐phase clouds were obtained using in situ probes on the aircraft and remote sensing instruments. Hydrometeor particle types were retrieved from HCR, HSRL, and temperature fields with a newly developed fuzzy logic particle identification (PID) algorithm. The PID results were validated with in situ measurements collected onboard the HIAPER aircraft by a 2D‐Stereo (2D‐S) cloud probe. Particle phases derived from the PID results compare well with those obtained from the 2D‐S observations and agree in over 70% of cases. Size distributions are also consistent between the two methods of observation. Knowledge of the particle type distribution gained from the PID results can be used to constrain microphysical parameterizations and improve the representation of cloud radiative effects in weather and climate models. Key Points: A fuzzy logic hydrometeor particle identification method is presented that uses airborne cloud radar and lidar observationsThe method classifies cloud and precipitation particles into eleven types of different phases and sizesA comparison of hydrometeor classifications with in situ measurements of Southern Ocean clouds show agreement in over 70% of cases [ABSTRACT FROM AUTHOR]

In this study, hourly data assimilation (DA) cycling is performed during a 24-h time period for Hurricane Matthew (2016), assimilating ground-based (GBR) and tail-Doppler radar (TDR) observations together, as well as separately using HWRF and its Hybrid 3DEnVar DA system. The objective is to examine the impacts of assimilating such data on the analysis and prediction of the weakening and re-intensification stages of the eyewall replacement cycle (ERC) of Matthew. Experiments assimilating GBR observations make quicker corrections to the initially inconsistent storm structure than does the TDR experiment, resulting in the primary and secondary eyewalls being realistically represented during the DA cycling period. The TDR experiment analyses show less-realistic concentric eyewall structure before, during, and after TDR observations become available. The forecasts from experiments assimilating GBR observations show more-realistic structural and point intensity changes for the ERC consistently throughout the cycling period when compared with the experiments assimilating TDR observations. Combined assimilation of GBR and TDR observations show similar ERC forecasts, on average, to the GBR experiment. The superior performance of the GBR experiments is shown to be tied to its earlier and longer availability despite its limited low-level coverage especially at the early stage of the cycling. The inferior performance of the TDR experiments even during the availability of TDR is hypothesized to be a result of rapidly changing 3D observational coverage during the high-frequency cycling. Brief mechanism diagnostics additionally suggest the need of properly initializing the TC concentric eyewalls to capture the ERC during the forecasts. [ABSTRACT FROM AUTHOR]

Multi-aircraft cooperative path planning is a key problem in modern and future air combat scenario. In this paper, this problem is studied in aspect of airborne radar detection to maintain a continuous tracking of a manoeuvring air target. Firstly, the objective function is established in combination with multiple constraints considered, including Doppler blind zone constraint, radar viewing aspect constraint, baseline constraint, and so on. Then, the above optimal control problem is transformed into a nonlinear programming problem with a series of algebraic constraints by hp-adaptive Gauss pseudospectral method (HPAGPM). And it is solved by GPOPS software package based on MATLAB. Simulation results show that the optimized cooperative paths can be got to achieve continuous tracking of maneuvering air target by HPAGPM. [ABSTRACT FROM AUTHOR]

Range-ambiguous clutter is an inevitable issue for airborne forward-looking array radars, especially with the high pulse repetition frequency (PRF). In this paper, a method to suppress the range-ambiguous clutter is proposed in an FDA-MIMO radar with a forward-looking planar array. Compressed sensing FDA technology is used to suppress the range-ambiguous clutter and the forward-looking non-uniformity short-range clutter of radar. Specifically, first, the range ambiguous clutter in different regions is separated by the characteristics of the planar array radar elevation dimension and FDA radar range coupling. Meanwhile, regarding the issue of the FDA radar main lobe moving between coherent pulses, a main lobe correction (MLC) algorithm proposes a solution for the issue, where the FDA radar cannot coherently accumulate signals in the case of non-full angle illumination. Finally, compressed sensing technology and elevation dimension filtering are utilized to suppress the range ambiguous clutter at the receiver, with the approach alleviating the range dependence of clutter in the observation region. A small number of clutter snapshots can obtain an approximately ideal clutter covariance matrix through compressed sensing sparse recovery. The method not only reduces the number of training samples, but also overcomes the problem of clutter non-uniformity in the forward-looking array. Therefore, the clutter suppression problems faced by the high repetition frequency airborne radar forward-looking array structure are solved. At the analysis stage, a comparison among the conventional MIMO and FDA methods is carried on by analyzing the improvement factor (IF) curves. Numerical results verify the effectiveness of the proposed method in range-ambiguous clutter suppression. [ABSTRACT FROM AUTHOR]