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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 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.

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]

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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]

In this letter, the clutter range dependence issue caused by crab angle is investigated in an airborne multichannel radar system. A new method is proposed to accomplish the crab angle estimation and the nonstationary error compensation. First, from the center-biased and spectrum-broadened characteristics of the clutter space-time spectrum in the case of nonneglected crab angle, a 1-D cost function based on space-time spectrum broadening degree is constructed to achieve the accurate crab angle estimation. Then, the clutter nonstationary errors can be effectively compensated in the post-Dopplerdomain,significantly improving the subsequent space-time adaptive processing (STAP) performance. Simulation results are presented to validate the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The range-ambiguous clutter in space-based early warning radar is more severe compared with that in airborne radar due to the faster movement velocity. Meanwhile, the clutter angle-Doppler characteristics vary with range owing to Earth’s rotation. As a result, the mainbeam clutter returned from different ambiguous ranges occupies most of the Doppler spectrum, which leads to the degradation of the traditional space–time adaptive processing (STAP) performance in canceling clutter. Though frequency diverse array (FDA) based on multiple-input multiple-output (MIMO) can provide the ability to identify the range-ambiguous clutter, it cannot perform well for space-based early warning radar because of the finite available vertical elements. In this letter, a novel STAP method, which utilizes the element-pulse coding (EPC) and FDA technique to mitigate the range-ambiguous clutter, is proposed. First, EPC is used to prewhiten the most range-ambiguous clutter via coding and decoding in horizontal elements and coherent pulses. Then the interval in the vertical frequency of the residual range-ambiguous clutter is expanded by FDA, and thus the targets and clutter from the vertical mainlobe are easily extracted using a spatial filter with a few vertical elements. Finally, the extracted clutter can be effectively suppressed through the traditional STAP method. Simulation results are provided to demonstrate the performance of the proposed method. [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]

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]

Near real-time ship monitoring is crucial for ensuring safety and security at sea. Established ship monitoring systems are the automatic identification system (AIS) and marine radars. However, not all ships are committed to carry an AIS transponder and the marine radars suffer from limited visibility. For these reasons, airborne radars can be used as an additional and supportive sensor for ship monitoring, especially on the open sea. State-of-the-art algorithms for ship detection in radar imagery are based on constant false alarm rate (CFAR). Such algorithms are pixel-based and therefore it can be challenging in practice to achieve near real-time detection. This letter presents two object-oriented ship detectors based on the faster region-based convolutional neural network (R-CNN). The first detector operates in time domain and the second detector operates in Doppler domain of airborne Range-Compressed (RC) radar data patches. The Faster R-CNN models are trained on thousands of real X-band airborne RC radar data patches containing several ship signals. The robustness of the proposed object-oriented ship detectors is tested on multiple scenarios, showing high recall performance of the models even in very dense multitarget scenarios in the complex inshore environment of the North Sea. [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]

Reasonable route planning and resource allocation strategy in the airborne radar systems (ARS), can sufficiently utilize the limited resources and promote the multitarget tracking (MTT) performance. However, using separately the route planning and resource optimization method cannot take full advantage of the airborne platform. Considering this issue, we propose a joint online route planning and resource optimization strategy in the ARS to improve the system capability for MTT. First, a kinematic model of the ARS, including the mathematical expression between the radar states and the system control parameters, is introduced, which integrates the route planning to the radar scheduling scheme. Next, the posterior Cramér–Rao lower bound about route planning and resource optimization variables for the tracking targets is derived. Then, a scaled-based utility function is established to quantify the MTT performance. Hereafter, a nonconvex problem is formulated by minimizing the utility function with route and resource constraints, and then a efficient three-stage partition-based solution is proposed. Finally, simulation experiments demonstrate the effectiveness of the proposed algorithm. Furthermore, over the traditional benchmark algorithm, the tracking performance of the proposed approach improves 30.44%. [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]

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]

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]

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]

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]

Frequency diverse array (FDA), which employs a small frequency increment across its array elements to generate controllable degrees-of-freedom (DOFs) in range dimension, has attracted extensive attentions in recent years. In order to extract and exploit the DOFs in range and angle dimensions, FDA has been combined with multiple-input multiple-output (MIMO) technique, which shows sufficient performance improvement in clutter suppression in scenarios with range ambiguities. Therefore, clutter rank evaluation is an important issue for FDA-MIMO radar mounted on a moving platform. In this article, a clutter rank evaluation criterion is developed with respect to different transmit/receive array configurations and different number of range ambiguities. It is based on a subspace transformation matrix that decouples the clutter subspace and allows a direct determination of clutter rank. With the proposed clutter rank evaluation criterion, the maximum resolvable number of range ambiguities can be determined, which is bounded by the system's DOFs. Three cases according to different relationships between uniform array element spacings are studied. Then, the aforementioned clutter rank evaluation method is extended to nonuniform array configurations. Moreover, the robustness of the method is studied in the presence of gain-phase errors. Several simulation results are provided to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Range-dependent clutter suppression is a challenging problem in nonsidelooking, bistatic, and conformal antenna array airborne radar, especially in the presence of range ambiguity. Superimposed stepped frequency (SSF) radar employs a small frequency increment across the stepped signals in each pulse, which introduces a dimension related to slant range. In this article, an airborne radar framework is established, which takes SSF signal as the transmit waveform. Thus, a two-stage adaptive clutter suppression method is proposed, which utilizes the degrees of freedom in range, space, and time domains provided by airborne SSF radar. In the first stage, the secondary range dependence compensation approach is adopted to distinguish the clutter of each range region in the carrier frequency domain. Then, a target-free covariance matrix is estimated by the compensated data, and the covariance matrix is used for the range-ambiguous clutter separation in the carrier frequency domain. Thus, the space-time snapshot of each range region can be extracted. In the second stage, a clutter segmentation processing method is devised for residual clutter suppression. For the near-range unambiguous clutter, the traditional clutter compensation approach is applied to further align the spectrum distribution of clutter, while the conventional space-time adaptive processing is utilized to suppress far-range clutter directly. Since the proposed method takes full advantage of the range dimension and the two stages of adaptive processing are data-dependent, excellent clutter suppression performance can be obtained. The proposed method can also extract the real range of the target since each range region is processed separately. Simulation results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Observations and analysis from the first airborne deployment of a G-band atmospheric radar, the Jet Propulsion Laboratory’s vapor in-cloud profiling radar (VIPR), are presented with a focus on ocean surface scatterometry and water vapor retrievals using the differential absorption radar (DAR) technique. We assess transceiver cross-calibration stability between the two DAR frequency channels using a combination of ground-based calibration measurements and airborne cloud observations that are validated by independent sensors. By comparing calibrated, unattenuated ocean surface backscatter measurements with existing models, we demonstrate the need for improvements in treating ocean surface scattering at G-band frequencies for future in-flight radar calibration applications. During science-oriented flights off the coast of California, we demonstrate partial column integrated water vapor (IWV) measurement capabilities with 0.3-mm precision in clear sky by performing a descent maneuver over an operational radiosonde (RS) launching site and comparing with the coincident in situ profiles to find a root mean square error (RMSE) of 0.5 mm. Furthermore, we present water vapor profiling and IWV measurements in the presence of clouds and precipitation when flying through a frontal weather system in the vicinity of Bodega Bay. By comparing with coincident RS profiles, we find an RMSE for in-cloud humidity profile retrievals of 1.1 ${\rm gm}^{-3}$ and precision of 0.6 ${\rm gm}^{-3}$ while the IWV retrievals reveal a bias from differential hydrometeor extinction of 5 mm. We provide a critical assessment of cloud-scattering-induced biases in the water vapor retrievals, as well as discuss a potential method for eliminating systematic error from the DAR measurements. [ABSTRACT FROM AUTHOR]

An extended Neyman–Pearson detector based on the combination of a traditional matched and wavelet filter in pulsed monostatic radar was proposed in this paper. Its properties were compared with properties of the cell average constant false alarm radar detector in the presence of white noise. The properties of detectors were examined in the receiver operating characteristic curves, parameter space. It consisted of false detection rate and the rate of true positive detected targets. In order to investigate the influence of temperature, the new parameter space was constructed: the temperature versus the rate of true positive detected targets. The traditional Neyman–Pearson detector based on a matched filter was fully operational and superior in the temperature range between 290 K and 350 K. Below this temperature range, its performance is completely degraded. It has been shown that by adding a wavelet filter, it can extend this temperature range between 260 K and 350 K. In the temperature range, where all detectors are fully operational, extended and classic Neyman–Pearson detectors had better performance than constant false alarm radar detector in the receiver operating characteristic curves' parameter space. [ABSTRACT FROM AUTHOR]

Passive operation is an important operational concept for future airborne radar platforms. Successful target detection requires an understanding of the underlying clutter statistics in order to set the detection threshold accurately. In addition, clutter statistics are important for modeling of passive radar performance and simulation of passive bistatic radar to aid in the development of new target detection algorithms. In this article, the clutter statistics of data from an airborne platform are studied over a range of bistatic geometries and receive polarizations. The illuminator is a digital video broadcast-terrestrial (DVB-T) station and the collected data spans both ground and maritime regions. The key contributions include a study of amplitude statistics using a number of common distributions and understanding the impact of the reference signal quality in terms of the clutter statistics. [ABSTRACT FROM AUTHOR]

Ship tracking facilitates a comprehensive insight into maritime traffic situations and ensures its safety and security. However, with the current operational surveillance systems, detecting several maritime threats is still a major challenge. In this article, we propose a supportive ship tracking concept using an airborne-based radar sensor. The proposed tracking algorithm is suitable for dense multitarget scenarios. Tracking is performed in the range-Doppler domain. The primary advantage of using the range-Doppler domain is that ships even with low radar cross section moving with certain line-of-sight velocity appear out of the clutter region, thus improving their detectability. In addition, a powerful track management system is also developed to handle false targets. The simulated and real experimental results from the DLR’s airborne radar sensors, F-SAR and DBFSAR, are presented to prove the concept. [ABSTRACT FROM AUTHOR]

We present new high-resolution snow depth data on Arctic sea ice derived from airborne microwave radar measurements from the IceBird campaigns of the Alfred Wegener Institute (AWI) together with a new retrieval method using signal peakiness based on an intercomparison exercise of colocated data at different altitudes. We aim to demonstrate the capabilities and potential improvements of radar data, which were acquired at a lower altitude (200 ft) and slower speed (110 kn) and had a smaller radar footprint size (2-m diameter) than previous airborne snow radar data. So far, AWI Snow Radar data have been derived using a 2–18-GHz ultrawideband frequency-modulated continuous-wave (FMCW) radar in 2017–2019. Our results show that our method in combination with thorough calibration through coherent noise removal and system response deconvolution significantly improves the quality of the radar-derived snow depth data. The validation against a 2-D grid of in situ snow depth measurements on level landfast first-year ice indicates a mean bias of only 0.86 cm between radar and ground truth. Comparison between the radar-derived snow depth estimates from different altitudes shows good consistency. We conclude that the AWI Snow Radar aboard the IceBird campaigns is able to measure the snow depth on Arctic sea ice accurately at higher spatial resolution than but consistent with the existing airborne snow radar data of NASA Operation IceBridge. Together with the simultaneous measurements of the total ice thickness and surface freeboard, the IceBird campaign data will be able to describe the whole sea-ice column on regional scales. [ABSTRACT FROM AUTHOR]

Multipolarizations of micro-Doppler signature (MDS) were combined to classify the elevation angle of a drone by a convolutional neural network (CNN). We classified the drone’s elevation angle based on the MDS, which depends on the elevation angle of the drone. To enhance the classification accuracy, we utilized micro-Doppler from multiple polarized radar signals. We utilized and analyzed four different polarizations for the receiver, namely, vertical/horizontal/right-handed circular polarization (RHCP)/left-handed circular polarization (LHCP), while the polarization for the transmitter was vertical. The four receivers with different polarizations were fully synchronized with Tx for accurate MDS measurement for each polarization. The radar data received from the multiple polarizations were combined for the classification algorithm based on CNN. The classification rate of the elevation angles of a drone was improved from 84.745% to 97.9% compared to a single polarization by using multiple polarizations. [ABSTRACT FROM AUTHOR]

Radar specific emitter identification (SEI) is the process of uniquely identifying an individual emitter from the same class of radars by their individual properties that arise from hardware imperfections. However, it is challenging or perhaps impossible to generate globally unique emitter identifiers by using SEI techniques alone, due to the increasing number of radars and the subtle differences in their signal properties. We therefore introduce a multitier radar emitter identification concept that includes radar function identification, model identification, and SEI. The combination of function identifiers, model identifiers, and specific emitter identifiers could generate globally unique radar emitter identifiers. In this article, we propose to use the radio frequency (RF) features extracted from time domain transient signals for radar model identification. The RF features include the duration, maximum derivative, skewness, kurtosis, mean, variance, fractal dimension, Shannon entropy, and polynomial coefficients of the normalized energy trajectory of a transient signal, as well as the area under the trajectory curve. We propose three RF fingerprints for radar model identification, each consisting of a predetermined subset of the features. The performance of the RF fingerprints was evaluated by using five classification algorithms with two radar datasets. Our results show attractive performance with respect to hetero-model radar identification. In particular, for the hetero-model radar dataset, the pair of the all-features (AF) fingerprint and gradient boosting algorithm achieved 91.9, 90.25, and 91.1% classification accuracy for three, four, and five emitters, respectively. On this basis, we conclude that the proposed AF fingerprint could be applied directly to radar model identification by training the gradient boosting algorithm using a dataset with many radars per model. [ABSTRACT FROM AUTHOR]

Merrill I. Skolnik was one of the early pioneers in radar systems development and engineering leadership. This article is a tribute to his 50 years' contribution to IEEE radar systems development. [ABSTRACT FROM AUTHOR]

Methods for modelling the radar scattering characteristics of resonance‐size airborne objects containing metallic and dielectric design elements are discussed. The developed algorithms are based on solving Fredholm second‐kind boundary integral equations (IEs) that place them within the context of the method of analytical regularisation. The magnetic field IE is used for metal elements, and the Müller IE set is used for dielectric elements. The proposed algorithms provide important novelties in calculating the radar scattering characteristics of objects with various curvature radii, including electrically thin scatterers. The description is accompanied by an analysis of developed algorithm convergence. For the validation, a comparison of results for model object obtained by different methods is presented. The results of modelling the radar scattering characteristics of an unmanned aerial vehicle and its separate metallic and dielectric elements within the VHF and S frequency bands are demonstrated and discussed. [ABSTRACT FROM AUTHOR]

In the conventional frequency diverse array (FDA) radar designs, generalized likelihood ratio test (GLRT) detection utilizes coherent pulses. However, the impacts of an FDA multiple-input multiple-output (FDAMIMO) radar system for detection with incoherent pulses have not been systematically investigated. In this paper, we present an incoherent square-law detector to analyse the performance of both the coherent and non-coherent airborne FDA-MIMO radars in a Neyman-Pearson sense. Moreover, the closed-form expressions of an incoherent square-law detector for the FDA-MIMO radars are derived. For a coherent FDA-MIMO radar, the optimal performance is achieved at a high signal-to-noise ratio (SNR), whereas the superiority of a non-coherent FDA-MIMO radar in distinguishing range dependent targets is validated. The corresponding theoretical derivations are verified by the extensive numerical results to show an improved performance. [ABSTRACT FROM AUTHOR]

We present a ground clutter reflectivity calculation method and a signal generation model of the simulated sea/land clutters of airborne radars using real navigation and radar operation information. The navigation and radar operation information were obtained by loading airborne radar on aircraft. The real navigation information and real sea/land clutters were obtained in the sea and land regions, and sea/land clutter reflectivity values calculated using the presented method were compared with the values of sea/land clutter reflectivity models of earlier studies. We confirmed the validity of the proposed sea/land clutter generation model by comparing real and simulated sea/land clutters. [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]

Generally ground clutter has serious range dependence and range ambiguity in the forward-looking array airborne radar system under a high pulse repetition frequency (PRF) system. In this work, a range ambiguous clutter suppression method based on transmitting beam main lobe correction for the FDA MIMO radar is proposed. Firstly, this method uses the designed transmission pulse weights to compensate for the initial phases formed by the accumulation of frequency increments between pulses, so as to solve the problem that the main lobe high gain illuminated angle is inconsistent between the MIMO equivalent transmitting beampattern pulses synthesized at the receiving in the traditional FDA MIMO system. Secondly, by restoring and compensating received echoes, the influence of the main lobe correction weights of the transmitting signal is eliminated. Finally, through the characteristics of transmitter correction compensation to distinguish different range ambiguous clutters, the echoes from the range ambiguous areas can be discretely distributed in the power spectrum while preserving the signal echoes in the observation area. Thus range ambiguous clutter suppression is realized. The simulation results show that the proposed method can improve the clutter suppression performance compared with the MIMO and linear frequency increment FDA radar. [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]

The results of the fabrication of active electronically scanned array (AESA) antennas with low-profile, low-weight, wide-scan, and thermal stability characteristics for aircraft-mounted radar are described. To reduce the size and weight of the antenna, a transmit– receive block is constructed in a quasi-tile structure in which the radio-frequency circuit-related transmit–receive module is a brick type, which is a flat structure, and the control board is a tile type, which is a stacked structure, to reduce the depth of the front of the antenna. In addition, the depth of the rear part of the antenna was reduced by manufacturing power and plate-shaped control-related modules at the rear of the antenna. The reduced antenna depth maximizes the effective isotropic radiated power (EIRP) and gain to noise temperature (G/T) by enlarging the antenna aperture. The manufactured antenna can scan a wide angle of ±70°. The cooling efficiency is improved by using a dual cooling structure that allows the cooling water to pass through the front cooling plate and then through the rear cooling plate. The EIRP of the manufactured AESA antenna is 104.04 dBmi, and G/T is 7.46 dB/K in Taylor weighting. [ABSTRACT FROM AUTHOR]

Previous work has shown that the relatively large resolution volume of spaceborne precipitation radars can affect precipitation measurements in several ways. During the Olympic Mountains Experiment (OLYMPEX), Ku- and Ka-band airborne radar measurements of precipitation were obtained during two Global Precipitation Measurement (GPM) overpasses, one case over land and one case over ocean. The authors compare the GPM-measured radar quantities with the same quantities inferred from the higher spatial resolution airborne radar data. Differences include smaller maximum reflectivity and path attenuation and more significant surface clutter in mountainous areas for GPM. [ABSTRACT FROM AUTHOR]

We report the analysis of opposite-side ambiguities in single-pass radar sounding interferometry. Nadir pointing radar sounders suffer inherent cross track ambiguities that cannot be separated with the power image alone. Interferometry can be used to interpret these ambiguities when data are collected with multichannel receivers. However, opposite-side surface clutter, volume scattering, and cross track range misalignment create unique interferometric phase and correlation signatures. Such signatures are observed experimentally in data collected by the Polarimetric Airborne Radar Ice Sounder (POLARIS) P-band multichannel radar sounder. We derive analytic expressions to predict the observations and validate them with simulation. In addition, we observe and explain a correlation dropout feature that is due to volume scattering competing with surface clutter in the null of the cross track antenna pattern. The purpose of this article is to explain opposite-side ambiguity signatures in radar sounder interferometry and provide models and techniques for scientific interpretation of interferograms. [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]

Hypersonic vehicles (HSV) have attracted much attention in recent years because of its military value. The radar system will face more serious clutter problem due to the increasing altitude and velocity. Thus, clutter characteristics analysis of hypersonic vehicles radar (HSV-R) is essential to clutter suppression. In this study, clutter model for HSV-R is proposed and the selection of pulse repetition frequency (PRF) is discussed. Finally, the results of simulation and the analysis of clutter characteristics under different PRFs are given. [ABSTRACT FROM AUTHOR]

Circular trace stripmap synthetic aperture radar (SAR) (CTS-SAR) is a new operation mode presented recently. Compared with linear trace stripmap SAR and staring SAR, it is similar to them. Meanwhile, it shows some unique features. The geometry relationship and work principle of CTS-SAR are introduced and deduced. After analysing the moving characteristics of airborne platform, a novel imaging method with motion compensation for airborne CTS-SAR is proposed. The impact of motion error and the performance of this new method are analysed. Finally, the results of computer simulation and real data processing validate the analysed results and the proposed imaging method. [ABSTRACT FROM AUTHOR]

Joint domain localisation (JDL) is a popular reduced-dimension space-time adaptive processing (STAP) technique for clutter suppression in an air-borne radar system. Here, the authors develop an improved JDL method by exploiting persymmetric covariance matrix, referred to as persymmetric joint domain localisation (Per-JDL), in order to make maximum use of training samples and further improve the STAP performance under small training data support. The proposed algorithm is verified to be efficient in training-limited scenarios by simulation results. [ABSTRACT FROM AUTHOR]

Simulation of the strong clutter occurring from the airborne radar is essential in the efficient development and performance evaluation of the aircraft radar system. If the efficient simulation of the clutter can be successful, algorithms can be proved and analyzed and also the performance evaluation is possible in the laboratory environment. Therefore, development and implementation of the airborne radar system can be achieved very economically in the effective way. However, the clutter simulation procedure is very difficult and tedious since the clutter environment changes in numerous ways as it depends on the flight path, direction of antenna beam, reflectivity of the surface, etc.. Thus, in this paper, the general Doppler spectrum model is suggested for efficient simulation of the various clutter environment. Also, it is shown that the various type of clutter in time domain can be generated easily by changing and adjustment of parameters in the general Doppler spectrum model. [ABSTRACT FROM AUTHOR]

Space–time adaptive processing (STAP) of multichannel radar data is an established and powerful method for detecting ground moving targets, as well as for estimating their geographical positions and line-of-sight velocities. Crucial steps for practical applications are: 1) the appropriate and automatic selection of the training data and 2) the periodic update of these data to take into account the change of the clutter statistics over space and time. Improper training data and contamination by moving target signals may result in a decreased clutter suppression performance, an incorrect constant false alarm rate threshold, and target cancelation by self-whitening. In this paper, two conventional and two novel methods for training data selection are evaluated and compared using real four-channel X-band radar data acquired with DLR’s airborne sensor F-SAR. In addition, a module for rejecting potential moving target signals and strong scatterers from the training data is proposed and discussed. All methods are evaluated for a conventional post-Doppler (PD) STAP processor and for a particular PD STAP that uses an a priori known road map. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the direction-of-arrival (DOA) of the ice-sheet data collected over Jakobshavn Glacier with the airborne Multichannel Radar Depth Sounder (MRDS) during the 2006 field season. We extracted weak ice–bed echoes buried in signals scattered by the rough surface of the fast-flowing Jakobshavn Glacier by analyzing the DOA of signals received with a five-element receive-antenna array. This allowed us to obtain ice thickness information, which is a key parameter when generating bed topography of glaciers. We also estimated ice–bed roughness and bed slope from the combined analysis of the DOA and radar waveforms. The bed slope is about 8° and the roughness in terms of rms slope is about 16°. [ABSTRACT FROM PUBLISHER]