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Currently, the main type of antennas for early warning radar targets is a large-aperture active phased array antennas, the main elements of which are receive-transmit modules (RTM). The elements included in the RTM are not absolutely identical, in that their parameters may differ from the nominal values because of production variation, temperature effects, aging, etc. As a result, the amplitude-phase field distribution on the antennas aperture, which leads to a decrease in the directional factor of antenna, an increase in the level of the side beams of the directional pattern and, as a consequence, to a deterioration in the performance characteristics of the radar. Therefore, the task of developing ways to calibrate RTM becomes urgent to ensure the identity of their parameters. In accordance with this, the paper proposes a RTM calibration technique that ensures the accuracy and reliability of calibration and a variant of its technical implementation.

Accurate estimation of the clutter covariance matrix for the cell under test (CUT) is a committed step in the spatial-temporal adaptive processing (STAP) algorithm. The unique nonstationary characteristic of signal for space-based early warning radar (SBEWR) leads to the spatial variation of training sample and the insufficient number of optional independent identically distributed (i.i.d.) training samples, which brings difficulties to training sample selection and covariance matrix estimation. To improve the estimation accuracy of clutter covariance matrix and the performance of STAP for SBEWR in a heterogeneous environment, a novel training sample selection and clutter covariance matrix estimation method is proposed. The method based on clutter subspace reconstruction and spectrum correction technology can improve the estimation accuracy of clutter covariance matrix in the case of nonstationary signals and heterogeneous environments. The clutter covariance matrix estimated by the proposed method is similar to the clutter covariance matrix of the CUT, and the performance of STAP is improved. The experimental results confirm the performance of the proposed method.

The process of creating modern early warning radar stations is characterized by minimizing the cost and time of work at the same time by reducing the risks associated with the use of new technical solutions. The article considers a variant of a typical representation of a network schedule for creating an early warning radar stations. It is noted that the schedule drawn up in this way is some approximation to the actual work being performed, as a result of which the necessary design decisions to adjust the process of creating early warning radar stations are taken late. The use of a network model is proposed for effective management of the radar creation process and the formation of network schedules for both individual stages and the entire project as a whole. Based on the analysis of a unified range of early warning radar stations, it is noted that the network model for reducing the risks of creating a radar should take into account both the multivariance of the tasks to be solved and the uncertainty of the parameters of the work performed. The main features of the proposed model are considered. The implementation of the proposed network model in the design of radar design for complex atmospheric research is shown as an example. During the research, several variants of radar implementation were considered and the optimal one was selected according to the proposed criteria.

In this paper, feasibility study along with conceptual design of missile-borne synthetic aperture radar (SAR) has been accomplished, which can effectively improve the detection capability and the blow precision of a missile. First, SAR echo signal modeling, geometry configuration for missile-borne SAR scenario, and an appropriate image formation algorithm are presented. Then, a system block diagram along with complete discussions about different parts and system design considerations of the SAR seeker are explained. Finally, simulation of the whole system along with raw data generation considering the imaging geometry of the missile-borne SAR seeker has been performed. Experimental results show that the proposed system is capable of imaging and targeting in the complicated geometry of missile-borne SAR.

In this paper, a precise beam position design algorithm for space-based early warning radar (SEWR) based on the actual antenna pattern search is proposed. In the proposed algorithm, the beam positions along elevation and azimuth dimensions are filled according to the main lobe widths of elevation and azimuth antenna patterns, respectively, and thus the beam position designment is more accurate since the range and azimuth angle dependences are considered. Based on the designed beam positions, the precise dwell time can be obtained according to the coverage rata of a SEWR system. The beam position designment results by using the proposed method provide a reference for the beam filling designment of a space-based radar.

For the traditional early warning radar, only one weight vector is calculated in engineering application for adaptive spatial filtering in a pulse reputation interval (PRI). Therefore, if the training data do not contain the jamming, then the adaptive spatial filtering calculated cannot suppress the jamming. If the adaptive weights update in the whole range domain, the target signal may be contained in the training data, resulting in signal self-cancelling effect. In this paper, we propose a non-homogeneous detector (NHD) based method for updating the adaptive weights in the whole range domain when the training data is contaminated by target signal. The principle is given, and the effectiveness is verified by simulations.

In this paper, the feasibility of a bistatic passive system for maritime surveillance and marine navigation is considered based on the communication satellite constellation Inmarsat as a source of illuminating signals. A power budget analysis is detailed for Inmarsat signals, considering both the reference and the radar channels. The effect of sea clutter is also examined. It is shown that relatively poor range resolution can be improved if the available communication channels are combined to improve the bandwidth, a process that also improves the sensitivity. For the first time, detection and preliminary bistatic range-Doppler tracking are presented for a representative maritime target.

Distributed inverse synthetic aperture radar (ISAR) exploits the data acquired by multiple radar sensors carried by multiple platforms working in formation to increase the cross range resolution with respect to the value achievable by single platform systems. In this frame, the paper addresses the problem of the estimation of the ship dynamics, i.e., yaw, pitch, and roll rotation motions, exploiting the signals collected by such multiplatform radar imaging systems providing angular diversity in order to enable the focusing of the distributed ISAR images. Specifically, in this work a multi-angle formation of sensors is considered and the corresponding maximum likelihood estimator and Cramer Rao bound are derived. Then, a new Doppler matching based technique is proposed as a suboptimal approach exploiting only the linear component of the phase of the received signals. The performance analysis proves the effectiveness of the proposed techniques to separately estimate the horizontal, radial, and vertical components of the rotation vector, therefore making possible both the focusing and accurate cross-range scaling of the distributed ISAR products (as well as of the low-resolution ISAR images regarding the different sensors) and, as a further advantage, providing knowledge of the orientation of the corresponding image projection planes. The analysis of experimental multisensor datasets confirms the feasibility of the proposed techniques.

In this paper, the feasibility of a bistatic passive maritime surveillance system based on the use of communication satellites as illuminators of opportunity is considered and confirmed experimentally. A theoretical comparison of the characteristics of a radar using Inmarsat and Iridium signals as donors has been performed. The procedure of enhancing the range resolution by coherently combining available scarce active communication channels in the frequency domain is presented with the example of the Inmarsat I-4 satellite broadband global area network signals. Parameters affecting the performance of range-Doppler mapping of a target are investigated based on the analysis of the ambiguity function of the combined signals. An experimental set-up with a stationary passive receiver designed for acquisition and processing of Inmarsat signals is presented and the results are shown. The detection and estimation of radial velocities by reflected Inmarsat signals are presented for the first time. The detected maritime targets ranged in size from a large passenger ferry to a small boat. The potential limitations of the concept are outlined, together with ways to overcome them.

We present a polarimetric analysis of small drones from different aspect angles. Polarimetric analysis can provide more information of a target, since the returned radar signal is affected by different wave polarization. The analysis is performed with micro-Doppler signature (MDS) to investigate micromotions of the drone detected by the radar. We measured operating small drones in an anechoic chamber from two aspect angles, 0° and 90°. An outdoor experiment was carried out with metal clutters for verification in real environment. The indoor analysis result shows that copolarized antenna receives signals better than cross polarized when the aspect angle is 0°, and vice versa. We also verified that cross-polarized antenna receives MDS from the drone better than copolarized antenna, from outdoors when an aspect angle is almost 90°. By utilizing the polarimetric characteristic of the drone at this frequency band, it is preferable to use a polarimetric radar for drone detection.

Ionospheric sounding is a technique that provides real-time data on high-frequency ionospheric-dependent radio propagation. This letter presents a Universal Software Radio Peripheral-based ionospheric sounding radar, which relies on a basic system consisting of a synchronized transmitter and receiver. The radar has the advantages of miniaturization, modularization, low power, and low cost. The three most significant features of the radar system are that it is software-defined and universal platform-based and that it has low transmitting power. This novel software-defined vertical-incidence radar system can probe the ionosphere and obtain real-time plasma parameters according to the simulation. Ionograms that directly express probe results are generated by MATLAB after data processing and simulation. Successful development of such an ionospheric sounding software radar will allow universalization and miniaturization of an ionosonde radar system. This letter introduces the implementation of the novel ionospheric sounding radar.

A high-frequency (HF) sky-wave radar always monitoring large area of sea surface, for detecting sea surface moving objects, there must be big data waiting to be processed. A set of data processing methods were proposed, the successful implementation of HF sky-wave radar on the sea moving target detection. By setting the HF sky-wave radar parameters, after the initial data processing, the gotten HF sky-wave radar data were saved. Then a new HF sky-wave radar data processing method was provided, this method was the so-called three-step detection method (TSTM) which based on the constant false alarm rate (CFAR) technique. By using TSTM, setting the decision threshold G, with false alarms being ruled out, a moving target was detected out at last, its speed was calculated. The results also proved that TSTM could effectively reduce the sea clutter, and greatly lessen the echo-broadening and double-image caused by ionosphere contamination.

Two-component clutter models are utilised to model and simulate the spatial-temporal characteristics of radar sea clutter backscatter returns from moving airborne platforms. Simulated data is shown to accurately model real data as assessed by comparing unprocessed data characteristics from real and simulated data sets as well as outputs from a single-channel coherent detectors and space-time adaptive processing based detectors. The proposed model is shown to provide improved performance over recently proposed models.

The NASA International Space Station (ISS)-RapidScat scatterometer operated on board the ISS from October 2014 into August 2016. It was developed using a combination of new subsystems and spare SeaWinds scatterometer engineering model subsystems to interface with the ISS. Using commercial (nonflight-qualified) parts in the new assemblies, developing RapidScat required a relatively small budget and short time schedule (just over two years). This article describes RapidScat's development from the perspective of radar system engineering, particularly in relation to performance requirements and testing.

An explicit expression for stochastic processes describing the dual-polarization weather radar echoes is presented. The probability distributions of the proposed model are defined in terms of the point values assumed by polarimetric and Doppler variables in the relevant radar sampling volume. The statistical properties of the model are discussed in order to verify its faithfulness as representative of real radar signals. The discussion considers the most general situation, i.e., it is not related to specific hydrometeor distributions or beam filling conditions.

The use of satellite signals for passive radar detection has become quite attractive in the recent years. This paper focuses on the detection and the shadow inverse forward scatter radar (SISAR) imaging of aircrafts in the passive forward scatter radar (FSR) system using global navigation satellite system (GNSS) satellites as illuminators of opportunity. The signal model derived from GNSS tracking loop is given and its Doppler character is analyzed. Then, by comparing GNSS FSR and ground-based FSR, the SISAR signal model and the imaging method for GNSS FSR are constructed. Experiments using airliners as targets were carried out, in which forward scattering signals of both GPS satellites and BeiDou satellites were captured. The experimental results verified the correctness of the given model as well as the effectiveness of the novel imaging method.

A stepped-frequency radar that allows for adaptability in the radiated spectrum while maintaining high-resolution radar imagery has been developed. The spectrally agile frequency-incrementing reconfigurable (SAFIRE) radar system is a vehicle-mounted, ground-penetrating radar that is capable of producing high-resolution radar imagery for the detection of obscured targets (either buried or concealed surface targets). It can be easily transitioned between forward- and side-looking orientations. The SAFIRE system is capable of precisely excising subbands within its operating bandwidth, thus making the system “spectrally agile.” It is also highly reconfigurable thereby allowing for on-the-fly adjustment of many of the system parameters. The spectrally agile and reconfigurable aspects of the SAFIRE radar together with its enhanced IF processing scheme represent a novel contribution to the state of the art. This paper discusses the system design, implementation, and performance characteristics, and also presents preliminary high-resolution imagery.

In very high resolution spaceborne-squinted sliding spotlight synthetic aperture radar, the traditional imaging algorithms based on the equivalent squint range model (ESRM) cannot be applied, because the ESRM model is inaccurate in this case. For this problem, this paper proposes a squint equivalent acceleration range model to precisely take into account the spaceborne-squinted curved orbit. Then a full-aperture squint-imaging algorithm is proposed based on this new range model, which can handle the azimuth variation of the equivalent velocity and the range variation of the 2-D frequency spectrum. The results of the simulation validate the effectiveness of new range model and imaging algorithm.

Toward a maritime surveillance objective, many ship detection and tracking algorithms have been investigated but are faced with poor performance in practical ocean environments. Compact high-frequency (HF) radar has also faced critical issues due to its long coherent processing interval and varying response from its orthogonal antenna structure. Hence, a simulator based on compact HF radar is proposed in this letter to provide a guideline for effective assessment of ship detection and tracking algorithms while considering these practical issues. To validate the proposed simulator, the simulator generated data has been compared with real data obtained by the compact HF radar sites.

Based on the narrowband radar, an imaging method for space targets is proposed in this letter, which is named as single-range interferometric imaging. First, the theory of space target echo signal interferometric processing in narrowband radar is explained. Then, through conducting short-time Fourier transform on the echo signal received by three antennas, the curves on time-frequency plane correspond to different scatterers are effectively extracted and separated and the interferometric phase of different scatterers is obtained. Finally, 2-D imaging for space target is realized. Compared to existing methods, only a single multiantenna radar is needed to obtain the 2-D image of target with accurate scaling result. The simulation results under different occasions have confirmed the effectiveness of the proposed method.

The analysis and correction of the bias occurring in weather radar polarimetric measurements is a challenging problem. Polarization coupling due to the cross-polar radiation pattern of the radar’s antenna is known to be responsible for errors in the estimation of the polarimetric covariance matrix, and consequently in the hydrometeor classification and quantification, either when using the ATSR or the SHV method. An alternative method for Doppler and polarimetric measurements based on transmitting three different polarizations (3-PolD) has been proven to provide accurate polarimetric covariance matrix estimates without making any hypothesis about the target polarimetric response or its Doppler spectrum. This method does not reduce the Doppler capabilities or the unambiguous range of the radar despite alternately transmitting 3-PolD. These characteristics have encouraged evaluating the polarimetric parameter biases due to cross-polar radiation when this method is used. Biases are calculated considering reflector antenna systems as well as phased-array antenna systems. The results show that this method may guarantee a tolerable bias level even with a poor co- to cross-polar antenna pattern ratio.

Future weather radar systems will need to provide rapid updates within a flexible multifunctional overall radar network. This naturally leads to the use of electronically scanned phased array antennas. However, the traditional multifaced planar antenna approaches suffer from having radiation patterns that are variant in both beam shape and polarization as a function of electronic scan angle; even with practically challenging angle-dependent polarization correction, this places limitations on how accurately weather can be measured. A cylindrical array with commutated beams, on the other hand, can theoretically provide patterns that are invariant with respect to azimuth scanning with very pure polarizations. This paper summarizes recent measurements of the cylindrical polarimetric phased array radar demonstrator, a system designed to explore the benefits and limitations of a cylindrical array approach to these future weather radar applications.

形態: カラー図版あり, Physical characteristics: Original contains color illustrations, Accepted: 2017-03-07, 資料番号: PA1720013000

This paper proposes a new scheme for improving the classification performance of inverse synthetic aperture radar (ISAR) images. The proposed scheme utilizes the trace transform to gather abundant information from an ISAR image, regardless of the spatial distribution of the target response in the ISAR image. In simulations using ISAR images with various spatial distributions, the proposed scheme substantially improved the classification performance compared with existing methods, which are highly vulnerable to spatial variation.

Weather radar variables provide useful information about the characteristics and motion of hydrometeors. However, the bulk information may be masked, when the meteorological signal of interest is contaminated by clutter. The dual-polarimetric spectral densities (DPSDs) may unveil additional information about the polarimetric characteristics of the groups of scatterers moving at different Doppler velocities in a given radar resolution volume. Previous DPSD estimation methods required averaging a large number of spectra (obtained from different spatial locations or times), or averaging in frequency to get accurate estimates; though by doing so, the resolution is degraded, and the important features of the meteorological phenomenon may be masked. In an attempt to overcome these limitations, the Bootstrap DPSD estimator is proposed, which allows the estimation of DPSDs from a single dwell with minimal spatial, temporal, or spectral resolution loss. The performance and the limitations of the Bootstrap and conventional DPSD estimators are assessed when identifying signals with different polarimetric signatures of scatterers moving at different radial velocities in the radar volume. The advantages of the Bootstrap DPSD estimator as a tool for the polarimetric spectral analysis are demonstrated with a few examples of polarimetric spectral signatures in data from tornado cases. It is expected that, with the Bootstrap DPSD and the polarimetric spectral analysis, it will be possible to better understand tornado dynamics and their connection to weather radar measurements, as well as to elucidate important scientific questions that motivated this paper.

In order to enhance the performance of spaceborne synthetic aperture radar–ground moving target indication (SAR-GMTI) systems, multichannel systems with large and preferably nonuniform baselines are required. In this paper, SAR-GMTI algorithms for multichannel SAR systems, which we call multichannel displaced phase center antenna (DPCA), multichannel along track interferometry (ATI), and multichannel DPCA-ATI, are presented. Multichannel DPCA is a deterministic algorithm for clutter and azimuth ambiguity suppression. It successfully suppresses not only uniform azimuth ambiguities but also nonuniform isolated ones, since it does not require uniform clutter covariance assumption as adaptive algorithms do. Multichannel ATI and multichannel DPCA-ATI are the algorithms for target radial velocity estimation. Both of them reduce the target radial velocity ambiguities, which arise with the long baseline systems, by exploiting the multiple receive channel signals. And multichannel DPCA-ATI further achieves robust performance to clutter influence by suppressing the clutter and the azimuth ambiguity in advance. The performances of the proposed algorithms are shown through airborne Ku-band three-channel SAR experiments. It is shown that the multichannel DPCA suppresses strong azimuth ambiguity up to more than 20 dB, and the accuracy of the radial velocity estimation of the multichannel DPCA-ATI is on the order of 0.1 m/s. Furthermore, statistical performance analysis is presented to discuss the potential performance on the spaceborne system.

The possibility of obtaining cross-range profiles of aerial targets is contemplated in this paper by applying inverse synthetic aperture radar (ISAR) techniques against FM-based passive radar data. The considered application is shown to pose a number of limitations, mostly related to the very long coherent processing interval required to attain a reasonable cross-range resolution. To mitigate such limitations, a suitable two-stage ISAR processing scheme is proposed for the estimation of the target motion induced phase history and its compensation. The results are shown against experimental data sets collected by a very high frequency (VHF) band passive radar receiver developed at Sapienza University of Rome. This allows to demonstrate the effectiveness of the proposed approach that provides the FM-based passive radar with advanced capabilities for air traffic surveillance applications.

In modern warfare, as a long distance detection equipment, a reconnaissance radar is crucial to monitor the sensitive regions and the intelligence of airborne targets. It is important for the opponent to identify the tactical information about the enemy’s reconnaissance radar. It has a great influence on the war. Scanning cycle of the monitoring radar is an important parameter for the counterreconnaissance of the hostile radar source in the electronic countermeasure. Since the pulse Doppler (PD) radar is one of the most widely used type in modern reconnaissance radar domains, this paper focuses on scanning cycle estimation of the reconnaissance radar (PD radar) using a single unmanned aerial vehicle (UAV). We propose an effective method to reconstruct the main-beam pattern (MBP) curve of the radar antenna based on the norm approximation algorithm, and then the reconstructed MBP curve of the radar antenna is exploited to estimate the scanning cycle of the reconnaissance radar. By hovering the UAV at the same place, the scanning cycle of the reconnaissance radar can be estimated according to the reconstructed MBP curve. In the simulation section, we check the validity and robustness of the proposed method through the performance comparison with the Cramer-Rao lower bound.

The aim of the radar systems is to collect information about their surroundings. In many scenarios besides static targets there are numerous moving objects with very different characteristics, such as extent, movement behavior or micro-Doppler spread. It would be most desirable to have algorithms that extract all information on static and moving object automatically, without a system operator. In this paper, we present measurements conducted with a commercially available high-resolution multi-channel linear frequency-modulated continuous-wave radar and algorithms that do not only produce radar images but a description of the scenario on a higher level. After conventional spectrum estimation and thresholding, we present a clustering stage that combines individual detections and generates representations of each target individually. This stage is followed by a Kalman filter based multi-target tracking block. The tracker allows us to follow each target and collect its properties over time. With this method of jointly estimating tracks and characteristics of each individual target in a scenario, inputs for classifiers can be generated. Which, in turn, will be able to generate information that could be used for driver assistance or alarm trigger systems.

Multiple-input-multiple-output (MIMO) radar image processing presents problems difficult to address by modifying conventional monostatic radar methods as Fourier range migration. When the distance between the transmitter and receiver is comparable to the target size, the single phase center approximation is not accurate. Furthermore, if the antenna radiation pattern significantly deviates from a spherical wave, the symmetries assumed in most range migration techniques are violated. We present a rapid Fourier-based MIMO reconstruction called Fourier accelerated multistatic imaging (FAMI) suitable for massively parallel computation that accounts for frequency-dependent radiation patterns, does not require the single phase center approximation, and is able to dynamically adapt to different target support volume shapes. FAMI is especially suitable for frequency-diversity antenna systems that use spectrally modulated coded spatial radiation patterns.

The infrared detection technology of ballistic missile based on near space platform can effectively make up the shortcomings of high-cost of traditional early warning satellites and the limited earth curvature of ground-based early warning radar. The operating range of the infrared system based on the near space platform is the key index for detecting ballistic missile. In order to analyze the operating range of infrared detection system based on near space platform, an improved range equation from investigating the characteristics of point source target is discussed and deduced. The simulation results show this method has scientific guiding significance for system overall scheme demonstration and design technically.

Space-borne early warning radar has great military and civil significance in ground, air, and space moving target detection in virtue of its wide-area coverage ability, where air moving target indication (AMTI) is an essential task for space-borne early warning radar. As for the AMTI mode, it is inevitably to handle the ground strong clutters due to the large surveillance area, and space-time adaptive processing (STAP) technique can be successfully applied to suppress the troubled clutter effectively. However, the clutter rejection performance of STAP will be restricted by many non-ideal factors, such as range ambiguity, channel number, and yaw angle induced by earth's rotation; thus it is necessary to analyze the influence of these practical non-ideal factors. In this paper, the multichannel signal model of clutter and air moving target in a space-borne radar (SBR) system are deduced. Then, we analysis the adverse influences of these non-ideal factors on STAP in detail. Finally, some simulation processing results are provided to validate the STAP performance with the consideration of these engineer factors, which can provide some useful guides of SBR system design with AMTI mode.

Thales SRA (Surface Radars) has launched the development of a new early warning radar family dedicated to the early detection of ballistic missiles (primary mission) and air breathing targets/space objects (secondary missions).The radar is named GAX000 (Ground Alerter) and is available in 3 different versions GA1000, GA3000, GA5000.This publication focuses on the key technical choices in the design of the radar. It first explains the rationale for the development of such a radar and then it describes the Thales experience in low frequency Early Warning Radars. In continuation, this publication describes the key features of the radar, presents the design choices driven by customer operational requirements and by performance requirements.

In order to simulate the spaceborne early-warning radar echo, a clutter simulation model is proposed. In spaceborne radar clutter simulation, the problem of two-dimensional widening in the range-Doppler domain of traditional simplified model is analyzed, as a result of beyond the precondition of the conventional airborne clutter simulation model. For the spaceborne condition, a new simplification is proposed. Taking into account the accuracy and efficiency of the simulation, a simplified spaceborne warning radar clutter model is proposed. The simulation results show that the new model improves the accuracy of the clutter simulation compared with the traditional one, and the simulation efficiency is taken into account as well.

Discriminating between meteorological and nonmeteorological radar returns is necessary for a number of radar applications, including hydrometeor classification, quantitative precipitation estimation (QPE), and the computation of specific differential phase KDP. The algorithm proposed, MetSignal, uses polarimetric radar data and is simple by design, allowing users to adjust its performance based on the location’s specific needs. The MetSignal algorithm is a fuzzy logic technique with a few postprocessing rules and has been selected for implementation on the WSR-88D network in the United States.

This letter aims to show the potential of using polarimetric parameters to distinguish between large birds and unmanned aerial vehicles (UAVs) of comparable size in the context of a modern long-range air defense radar. Time is a critical resource in such systems, and techniques for robust noncooperative target recognition not relying on spatial resolution or long dwell times are highly desired. Furthermore, methods less dependent on target micromotion are, in many cases, required. Methods exploiting polarimetric features are shown to have potential in both cases. An experiment in S-band shows that a simple nearest-neighbor classifier can achieve good separation between UAVs and birds both with and without detectable micromotion based on a set of polarimetric parameters alone.

The detection of ground moving targets with arbitrary linear motion from an airborne multichannel radar via a long coherent processing interval is considered. The technique maximizes the target signal energy in synthetic aperture radar (SAR) images by matching to the target's linear motion profile. A reparameterization of the target's linear motion is developed that decouples the array processing from the image formation process. An explicit approach to forming SAR images focused with respect to a particular along-track velocity is presented. The ground clutter is canceled via an adaptive array technique, which also yields an estimate of the target radial velocity. Because the algorithm generates estimates of the target's along-track and cross-track velocity components, a unique determination of the target's motion parameters is possible. The approach is derived and investigated via simulated point spread functions. Algorithm performance is demonstrated on the GOTCHA SAR ground moving target indication data set.

On phased-array radars, scanning is done by stepping the beam from one direction to the next direction and dwelling long enough at each direction to achieve acceptable errors of estimates. Combining data from the three directions is suggested to obtain superresolution similar to that available on the national network of weather radar (Weather Surveillance Radar-1988 Doppler or WSR-88D). Spectral analysis of such data is addressed, and it is demonstrated that the Doppler spectra of simply concatenated time series have very strong sidebands due to the discontinuity of the signals from the three beam positions. This artifact degrades the performance of the spectral clutter filters and other methods that rely on spectral processing to enhance the weather signal. Special adjustments of the signals at each range location before concatenating (splicing) are proposed to mitigate the effects of discontinuities in time and thus improve clutter filtering. The adjustment is such that the total information contained in the signal can be preserved in subsequent processing. Spectral quality of the concatenated signals is quantified via results from simulations. Samples of spectra obtained with the National Weather Radar Testbed are presented to substantiate the predictions. A ground clutter detector/filter accepted by the National Weather Service is applied to the conditioned time series data, and the ensuing fields of reflectivity factor and Doppler velocity are compared to the fields from which clutter had not been removed.

In this study, the authors consider the coupled sequential detection and estimation of weak targets for track-before-detect algorithm in long range early warning radar. They present a new strategy and develop a coupled cost function consisting of detection, position estimation and tracking estimation loss. In the proposed procedure, the sequential stopping and detection rules are simplified. Moreover, they derive the lower bounds of the detection and estimation probabilities, which can be used to design the suitable related parameter values. Finally, several numerical simulations of the new strategy and the comparisons are presented and discussed.

In this letter, pioneering experimental results of passive synthetic aperture radar (SAR) imaging are presented. The classical active SAR radar operates in monostatic geometry. The SAR sensor presented in this letter is a passive radar utilizing commercial Digital Video Broadcasting—Terrestrial transmitters as illuminators of opportunity. It works in a bistatic configuration, where the receiver is placed on a moving platform and the transmitter is placed on the ground and is stationary. The imaged scenes are stationary surfaces on Earth such as agriculture or urban areas, buildings, etc. In this letter, pioneering results of signal processing verified by a measurement campaign are presented. In the experiment, two synchronized passive radar receivers were mounted on a small airborne platform. The main goal of the presented experiment was to verify the possibility of ground imaging using passive SAR technology and validate previously presented theoretical results.

The pose of a rotational symmetry target in a wideband radar is the angle between its symmetry axis and the radar line of sight. It is a required parameter for target absolute attitude measurement using the bistatic radar measuring system. In this letter, a 3-D electromagnetic model (3-D EM model)-based method is proposed for estimating the target pose from fully polarimetric wideband radar measurements. The 3-D EM model is established offline based on the target geometric structure. Scattering features at different target poses can be accurately predicted by this model. In the proposed algorithm, a synthetic high-resolution range profile (HRRP), which is proved to be only related to the target pose, is first generated from the sum of echoes in radar copolarization channels. Then, by matching this synthetic HRRP with the synthetic HRRPs recovered by the 3-D EM model, the target pose is obtained. Experiments using both data predicted by a high-frequency electromagnetic code and data measured in an anechoic chamber verify the validity of the method.

Performance of space–time adaptive processing (STAP) with adaptive matched filter detection for maritime surveillance is assessed using simulated maritime surface targets embedded in real radar sea clutter data and compared with conventional pulse-Doppler processing. Pre-Doppler and post-Doppler suboptimal STAP are examined, with pulse repetition interval (PRI)-staggered post-Doppler shown to provide best overall detection and constant false alarm rate performance. A two-component clutter model fit is used to explain variations of clutter characteristics and detector performance with Doppler frequency.

The influence of intelligence gathering inaccuracy, especially the estimate error of radar kinematic parameter, on the performance of deceptive jamming against synthetic aperture radar (SAR) is studied in this paper, filling a knowledge vacancy in the field of SAR electronic countermeasures. For the first time, an equivalence relationship between non-ideal jamming and ground moving target is derived and verified in raw phase history data domain and radar image domain. A novel and elegant way to quantify the defocus and displacement of false target in radar image is proposed based on the equivalence relationship. Work presented in this paper can guide the design of jammer’s intelligence gathering subsystem and optimize jamming configuration, from the view of jammer. The results also avail electronic counter-countermeasures, from the view of radar.

A 3-D inverse synthetic aperture radar (ISAR) image can provide target’s information in the range, azimuth, and height dimensions. Since the height resolution is related to the variant observing angles, the existing 3-D ISAR imaging methods are highly dependent on the radar’s hardware complexity (two or more sensors). In this paper, we propose a novel 3-D shipborne ISAR imaging method, which utilizes the maneuvering movement of one single shipborne radar to obtain the height resolution, and hence, the restriction on the hardware complexity is relaxed. Moreover, a novel cubic chirplet decomposition algorithm based on Radon transform is proposed to estimate the signal parameters, and additional data from narrow-band tracking radar and shipborne attitude indicator is used for image scaling and distortion elimination. Therefore, the high-quality 3-D ISAR image can be achieved. Simulation results verify the effectiveness of the proposed methods.

This paper proposes a method on high-frequency vibration compensation of helicopter-borne synthetic aperture radar (SAR) in terahertz band. The SAR signal model with platform vibration is established based on the mechanism of a helicopter's vibration. Then successive Doppler keystone transform (SDKT) is used to correct the range cell migration induced by the vibration. Finally, the analytical formula of the platform vibration phase error is given as well as its compensation to achieve a focused image.

Here, we present a method for extracting urban areas from X-band fully polarimetric synthetic aperture radar (SAR) data by reducing the effects of polarization orientation angle (POA). The proposed classifier performs two classifications utilizing characteristics of X-band scattering in land cover. One classification uses total power of scattering and volume scattering derived by using four-component decomposition methods with correction for the POA effect. The other classification uses polarimetric coherence between $S_{ HH}$ and $S_{ VV}$ . These two results are intersected and final urban areas are extracted after postclassification processing. We applied the proposed method to airborne X-band fully polarimetric SAR data of the polarimetric and interferometric airborne synthetic aperture radar system, developed by the National Institute of Information and Communications Technology, Japan. Validation of the results for three Japanese urban areas shows that the proposed method provides an acceptable overall accuracy of approximately 80%–90% at a 100-m spatial scale. It is also shown that texture-based classifiers using single polarimetric data have accuracy limitations when applied to extracted urban areas where the POA of objects is not uniform.