This letter is the first to analyze the impact of image pixel correlation in combination with sea surface texture on the detectability of vessels in synthetic aperture radar (SAR). The multilook intensity probability density function (pdf) changes considerably when the pixels are not statistically independent. The pdf tail becomes elongated. The letter investigates theoretically and empirically the deviation between the multilook intensity histogram and various model pdfs when pixel correlation occurs in both calm (homogeneous) and rough (heterogeneous) sea surfaces, respectively. In the literature, it had been concluded that the classic gamma distribution (GD), when using an effective number of looks, fits the data sufficiently well. This, however, is shown to be only true for the bulk of the pdf, whereas the tail can divert significantly from the histogram. As a consequence, the required detection threshold becomes compromised, either causing more false alarms or missing true vessels. It is further demonstrated that a recently introduced discrete compound model, in contrast to the state-of-the-art K-distribution (KD), is capable of mitigating the problem.

Ship detection algorithms in Synthetic Aperture Radar (SAR) imagery are broadly categorized into: (i) those that interpret sea clutter according to a pre-defined Probability Density Function (PDF), detecting anomalies in positions within the tail of the PDF based on a specified Probability of False Alarm (PFA); and (ii) those which utilize a sufficiently large training dataset to learn the decision boundary between the target and clutter classes. Despite numerous publications in both categories, a proper quantitative comparison of their performance is lacking. This study is a step towards crossing this chasm by conducting a direct comparison between two real-world representatives: (i) SUMO’s K-distribution Constant False Alarm Rate (K-CFAR/SUMO) detector, and (ii) the Deep Learning Model that topped the xView3 (1stDLM/xView3) challenge organized by the Defense Innovation Unit and Global Fishing Watch. The performance of both algorithms is characterized by tracking the number of False Alarms (FAs) and Missed Detections (MDs) in three labeled Sentinel-1A repeat-pass SAR images acquired in the Gulf of Guinea. The results demonstrate that 1stDLM/xView3 outperforms K-CFAR/SUMO, achieving the best FAs-MDs trade-off.

Empirical modeling of Radar Cross Section (RCS) is crucial in defence applications, particularly for guiding the design of specialized Ship Detection Modes (SDMs) tailored for small vessels. This paper presents a novel Gaussian Process Regression (GPR) model for RCS prediction of ships in Inverse Synthetic Aperture Radar (ISAR) imagery. Leveraging 586 Motion Compensated (MO-COMP) ISAR frames representing five ship classes from the real-world Small Craft Automatic Target Recognition (SCATR) dataset, three variants of (i) baseline Multiple Linear Regression (MLR) model, and (ii) GPR model, are constructed. The demonstrated efficacy of the GPR-based approach surpasses that of the baseline MLR model, emphasizing its significant improvement in RCS modeling.

Dual polarimetric (DP) and compact polarimetric (CP) SAR modes are preferred over quad-channel fully polarimetric (FP) modes for wide-area maritime domain surveillance applications because they provide twice the swath width. Recently, the multilook complex (MLC) product was introduced for RADARSAT Constellation Mission (RCM) imagery, which preserves the polarimetric phase information at a considerably lower data volume over the traditional phase-preserved single-look complex (SLC) product. From statistical theory, the optimal detector for polarimetric data has been previously derived and is known as the optimal polarimetric detector (OPD). However, for a deterministic target model, this detector cannot be applied to MLC data and is also impractical, because it requires complete a priori knowledge of the target. Instead, a suboptimal detector, known as the polarimetric whitening filter (PWF), is often used in practice. This letter proposes a new detector called “quadratic matched filter (QMF)” for CP and DP data that can be applied to MLC products for improved vessel detection over the PWF. A technique to estimate target parameters at processing time is also proposed, which can be used to estimate target parameters for both OPD and QMF. The feasibility and improved performance of the QMF detector are demonstrated through simulated receiver operating characteristic (ROC) performance analysis, and by demonstrating detection performance on an image acquired by RCM. It is shown that the QMF provides approximately 1.5 and 3 dB improvement in signal-to-clutter-plus-noise ratio (SCNR) and peak-signal-to-clutter-plus-noise ratio (PSCNR), respectively, over PWF.

Automatic vessel detection based on wide-area synthetic aperture radar (SAR) imagery is achieved via a statistical hypothesis test in which a ship is declared detected when the pixel intensity exceeds a predetermined threshold. Inherent to the physical principle of SAR as a pulsed radar system, not only legitimate vessels are detected but also ambiguous reflections caused by the periodic sampling of the scene. These ambiguous returns occur in both directions, azimuth and range, and can originate at land or ships. Depending on the chosen beam mode and system parameters, many also exceed the threshold and can severely degrade the overall performance quality. In the literature, several elaborate technological and signal-processing techniques were proposed to either entirely avoid the emerging of ambiguities or at least suppress them significantly. While hardware-based solutions are not readily available on existing spacecraft and potentially cost prohibitive on future ones, most processing algorithms are computationally too laborious for near real-time applications. This article presents an alternative solution. As SAR-based ship detection is not about creating neat imagery, ambiguities may be tolerated as long as they can be reliably identified as such during a follow-on examination. This step is being proposed to be a novel additional statistical test that decides which hypothesis (vessel or ambiguity probability) was more likely to have generated the prior detected pixel cluster. The effectiveness of the method is shown theoretically and corroborated with real RADARSAT Constellation Mission (RCM) data.

False alarms (FAs) pose a major challenge for operational ship detection in spaceborne Synthetic Aperture Radar (SAR) imagery. This paper presents a novel algorithm for identification and tracking of FAs in repeat-pass Radar Constellation Mission (RCM) imagery. The algorithm benefits from that not only ambiguities but also fixed ocean structures and small islands are recurrently detected at predetermined geographic locations in the repeat-pass acquisitions. Efficacy of the proposed algorithm is demonstrated through tracking an azimuth ambiguity, a small island, and an elevation grating lobe range ambiguity in a stack of twenty-six Ship Detection RCM images acquired near Galápagos Islands.

As a two-dimensional spatial filter, the unidirectional electronically steerable planar phased-array SAR antenna of the Radar Constellation Mission (RCM) samples the space-time process in azimuth and elevation, respectively, with spatial intervals and visible region defined by the corresponding interelement spacings and wavenumbers. Since position and wavenumber are conjugate Fourier transform variables, interelement spacings need to abide by the Nyquist-Shannon criterion. Further, since the antenna’s response is a 2π-periodic function, it produces an infinite number of periodically spaced peaks that are equal in strength to the main lobe peak. If any of these peaks is shifted into the visible region, due to azimuth and/or elevation steering, it becomes a grating lobe that warrants attention. This paper investigates Grating Lobe Ambiguities due to Elevation steering (E-GLAs) in ScanSAR RCM imagery. E-GLAs resemble legitimate targets and they pose a challenging source of false alarms for operational ship detection. Using theoretical analysis, simulations and a real-world Ship Detection dataset, it is demonstrated that E-GLAs become visible for off-nadir angles ≥ 50.38°. A novel algorithm is presented to automatically locate E-GLAs in repeat-pass images. Efficacy of the algorithm is demonstrated through tracking a verified E-GLA in a stack of 26×2 RCM images near Galápagos Islands, processed using downlinked and definitive satellite orbits, respectively. Results based on definitive orbits are shown to outperform their downlinked counterparts.

Aim of this article is to analytically derive the statistics of the magnitude and phase of the complex sample correlation coefficient between two Gaussian synthetic aperture radar (SAR) acquisitions, the foundation of interferometric SAR (InSAR), and polarimetric SAR. In particular, several novel closed-form expressions containing only elementary functions for the probability density functions (pdf) and the central moments are derived when the complex sample coherence is averaged over an integer number of independent samples (multilooking). Based on these rather simple expressions, a promising way to overcome the assumption of an underlying normal distribution for the InSAR data is proposed. Jointly, these two approaches permit a physically sound, robust, and highly accurate description of the InSAR statistics of severely heterogeneous scenes, a crucial prerequisite to many applications.

This paper presents first results of open ocean surface current retrieval in the satellite line-of-sight (LOS) direction using RADARSAT-2 along-track interferometry (ATI) over the expected track of the Gulf Stream (GS). Results are compared to measurements derived from NASA's Ocean Surface Current Analyses Real-time (OSCAR) dataset, which provides global near-surface ocean current estimates. Results show close spatial correspondence, and a RMS difference of approximately 21 cm/s was observed between the two estimates over the region identified as GS. However, due to its significantly higher spatial resolution, measurements obtained from RADARSAT-2 MODEX ScanSAR showed small scale surface current features that were entirely missed in the OSCAR dataset. This increased the RMS difference over the entire scene to approximately 50 cm/s.

The trimodal discrete (3MD) radar clutter model is a simple and accurate model for the interference distribution, which facilitates the computation of the probability of false alarm as a function of the detection threshold. Four estimation methods for the 3MD parameters are presented: two method-of-moments estimators-one based on an analytic solution to the moment equations for integer order from zero to five and the other using a nonlinear least-squares (LS) fit to 50 sample moments of fractional order; a nonlinear LS fit to the complementary cumulative distribution; and the maximum likelihood estimator (MLE). The methods were tested on both measured radar sea clutter data and simulated data and compared with the Cramér-Rao lower bound. The accuracy of all four methods is satisfactory, with the MLE the most accurate, but also the most computationally intensive. The analytic solution to the moment equations is the fastest method, two orders of magnitude faster than the MLE, but it is intractable for more than three modes. The other methods can all be used to estimate parameters for more than three modes if required.

This paper examines the attainable performance of various Doppler sublook or subband cross correlation techniques for vessel detection in synthetic aperture radar images. Research from the past two decades claims that these techniques were capable of improving the detection of small ships in challenging maritime environments. Despite many published experimental examples, a thorough analytical investigation corroborating this claim is noticeably absent. This paper is based on a rigorous theoretical analysis founded on the statistical properties of a textured sea surface model in thermal noise with simultaneous consideration of a constant false alarm rate. Emphasis has been placed on the correct accounting for detrimental physical effects caused by the Doppler spectrum being split into nonoverlapping parts, which have not been sufficiently considered in the literature to date. The theoretical results are confirmed via simulations and are substantiated with real RADARSAT-2 data. The analysis in this paper has neither found theoretical nor empirical evidence that sublook correlation techniques outperform the classical detector based on the image magnitude.

Initial results of newly developed dual-channel polarimetric SAR-GMTI modes on RADARSAT-2 are presented, showing combined capabilities to detect ships both in open water and in a river channel surrounded by land and to differentiate land and target types. The potential to use motion information along with backscattering characteristics of HH and VH polarizations to differentiate ships from icebergs are discussed.

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

This letter presents a theoretical analysis of the impact of thermal noise on the statistics of the classical as well as a modified estimator for the cross-correlation coefficient between two receive channels, which follow a noisy compound clutter model. This correlation coefficient, in the synthetic aperture radar (SAR) context often called coherence, is widely used as an important quality parameter in the field of SAR interferometry, SAR change detection, and SAR ground moving target indication. Based on a novel closed-form expressions for the probability density function (pdf) for integer number of averaged samples (or looks), it is shown that, contrary to widespread belief, the clutter texture does not cancel out when the noise contribution is taken into account. It is further demonstrated that the new pdfs can be used to derive the bias and variance of the sample coherence in analytical closed form. Thereby, the impact of the texture on the estimators is analyzed.

This paper compares the imaging quality of several multichannel processing methods that have been proposed for high-resolution wide-swath (HRWS) synthetic aperture radar (SAR) systems. A review of the different reconstruction methods is performed and their imaging performances are investigated for an exemplary multi-channel HRWS SAR.

This paper investigates and demonstrates enhancements to Maritime Domain Awareness (MDA) through the use of a multi-aperture space-based SAR. In contrast to a single channel SAR, it shows how modes can be designed to collect data over a wide swath (enabling wide area surveillance) at high resolution (offering improved vessel detectability and potential for classification). This paper also explores how these same data can be processed using different algorithms to enhance ship detection through clutter suppression and outlines how to estimate vessel headings and speeds. Additionally, it shows that in littoral zones, ambiguities from on-shore clutter can be minimized. Demonstrations of the claims are made using data collected by RADARSAT-2 in a dual-aperture configuration.

This paper addresses signal reconstruction for future multiple-input multiple-output synthetic aperture radars (SARs) equipped with a multichannel antenna to enable wide-area high-resolution imaging. To image large swaths without range ambiguities, these high-resolution wide-swath (HRWS) SAR systems use a low pulse repetition frequency (PRF). Such a PRF, however, causes the radar echoes received by each channel to be strongly aliased. By introducing new techniques, this paper extends the theory of multichannel signal processing for reconstructing the SAR signal from the aliased signals. The reconstruction performances of the proposed processing methods in terms of signal-to-noise ratio, resolution, point target ambiguity ratio, peak-to-sidelobe ratio, and signal-to-ambiguity-plus-noise ratio are investigated according to the PRF and compared with each other for an exemplary HRWS SAR system.

A new method for processing multichannel synthetic aperture radar (SAR) data to achieve desirable image characteristics is presented. The method is optimal because it is derived by minimizing a mean-square-error cost function and generalizes current methods for high-resolution wide-swath SAR signal processing. The proposed method is easily implementable, can support a wide range in the pulse repetition frequency (PRF), including cases with highly nonuniform spatial sampling, and is robust against PRFs where current projection techniques fail, cases where the PRF is ideally suited to clutter suppression. Point spread functions for the proposed algorithms are presented, and the theory and simulations are further corroborated by results using multichannel SAR data measured by RADARSAT-2. We demonstrate that, if RADARSAT-2 were able to illuminate a 250-km swath (300 km ground range), then, conceptually, the new method would be able to process the highly nonuniformly sampled data to provide an extremely wide mode at approximately 5-m azimuth resolution.

Ground moving target indication (GMTI) from space has currently raised interest from wide area traffic monitoring as well as for military surveillance activities. This paper presents theoretical and real data GMTI results of RADARSAT-2's Moving Object Detection Experiment based on data gathered during the commissioning phase in February 2008. The proposed constant false alarm rate target detection is based on a novel and thorough analysis of the multilook test statistics. The practical and relevant case in which a target, for instance a passenger car, occurs in onlyl-out-of-nground resolution multilook cells is analyzed. This general case is analyzed for the determination of adequate detection thresholds as well as the anticipated probability of detectionPdparticularly with regard to a varying degree of terrain heterogeneity and target characteristics. The overall false alarm ratePfais significantly reduced by a complementary detection step using the along-track interferometric phase. The validity of these theoretical findings are corroborated by real two-channel space-based synthetic aperture radar-GMTI data of civilian vehicles of opportunity, whose main parameters have been estimated and compared with the derived Cramér-Rao Bounds.

The papers in this special issue cover the most topical research areas in Synthetic Aperture Radar (SAR) techniques and technologies as bistatic SAR, innovative system concepts, polarimetric systems and data analysis, polarimetric SAR interferometry, as well as advanced processing techniques for image generation and information extraction.

This paper derives an optimum processing method for ground moving-target indication (GMTI) with a multichannel synthetic aperture radar (SAR) system. This method enables efficient detection of moving objects and accurate estimation of their parameters and does not require any knowledge of the street network. The processing is applied to data acquired with the Canadian RADARSAT-2 satellite. Results of the performed trial are compared with the expected GMTI performance of the radar in order to validate the theory.

This paper studies the statistics of clutter data measured with a multichannel space-based synthetic aperture radar (SAR) for the purpose of ground moving target indication (GMTI) and presents an algorithm that implements an adaptive constant false-alarm rate (CFAR) detector. It discusses the differences between airborne and space-based SAR-GMTI clutter measurements and proposes how to develop the statistics of the latter from widely published results for the former. Based upon one of the differences, it proposes an adaptive CFAR detector and demonstrates detection using measured RADARSAT-2 data. The adaptive CFAR algorithm does not require a texture distribution for heterogeneous clutter.

This paper presents the theoretical and experimental performance evaluation of a novel and innovative concept to add a multichannel ground moving target indication (GMTI) capability to a synthetic aperture radar (SAR) reflector antenna with a standard single feed. This approach exploits the capability to achieve a phase center displacement by combining signals obtained from different electromagnetic excitation modes of the feedhorn. While, in the past, this so-called multimode concept has been mainly analyzed in simulation and by various antenna laboratory measurements, several flight experiments have been recently conducted to verify and demonstrate its GMTI performance. The theoretical and experimental analysis provides qualitative and quantitative insights into the effectiveness of multimode SAR-GMTI applications, such as the SAR image-based along-track interferometry (ATI) or post-Doppler GMTI approaches based on space-time adaptive processing. In addition, it introduces practical lessons learned, along with an example of the detection and parameter estimation for a large vessel using ATI. This paper finishes with an examination of the expected performance improvement when the transmitted modes are alternated between subsequent pulses. This toggling results in a time-multiplexed three-channel GMTI system with significantly enhanced estimation performance.

The 29 papers in this special issue cover the most topical research areas in SAR techniques and technologies, such as bistatic SAR, innovative system concepts, polarimetric systems and data analysis, polarimetric SAR interferometry, and advanced processing techniques for image generation and information extraction.

Recently, theoretical investigations have shown that switching between parts of the transmit and/or receive aperture in a pulse-to-pulse cycle may improve the ground moving target indication (GMTI) performance of a two-channel radar system. This paper intends to verify these findings experimentally for the switching concept for the first time. Accordingly, six different GMTI modes were implemented in the system PAMIR (phased-array multifunctional imaging radar) of the Fraunhofer Institute for High Frequency Physics and Radar Techniques (Fraunhofer FHR) including three switching modes. An experiment was conducted using six cooperative vehicles following a predefined scenario to compare the GMTI performance and, in particular, the positioning accuracy of the different GMTI modes. The results of this experiment as well as the underlying signal processing are presented in this paper. The analysis is based on a multilook constant false-alarm rate detection scheme. Due to the heterogenous nature of the considered scene, the well-known test statistic for homogeneous terrain had to be extended accordingly, and a novel test statistics is proposed.

Bistatic SAR is a promising and useful supplement to a classical monostatic SAR system. Since transmitter and receiver are spatially separated, additional information of a scene may be provided. Further, as shadowing, layover, and foreshortening depend on the bistatic geometry, which can be quite different to the monostatic case, they can contribute to image analysis and classification. The transmitter and receiver are located on different platforms, which may either be close together or hundreds of kilometers apart. Typical platforms are satellites, UAVs, aircrafts, and towers. This paper presents recent bistatic SAR experiments with spaceborne, airborne, and stationary sensors, which have been conducted at FHR or in cooperation with Defence Research & Development Canada. Image results are presented and analyzed with respect to scattering behavior and resolution and compared to monostatic images.

This paper presents an overview of various detection and estimation algorithms that have been implemented in the RADARSAT-2 MODEX Processor as well as experimental plans for the validation and demonstration of the space-based GMTI mode. Preliminary RADARSAT-2 GMTI results are also presented.

Along-Track Interferometry (ATI) for the indication of moving targets with two channel Synthetic Aperture Radar (SAR) shows a low detection probability for a small number of looks. This paper proposes an enhancement called Better ATI (BATI). It is characterized by a constant parameter added to the interferometric SAR image before determining its phase. Statistical analysis shows that the new technique significantly outperforms ATI, is comparable to Displaced Phase Center Antenna (DPCA) for homogeneous terrain and may outperform DPCA in heterogeneous terrain. The theoretical results are confirmed successfully with experimental data.

Ground moving target indication (GMTI) from space by existing dual-channel radar systems such as TerraSAR-X and RADARSAT-2 has been shown to perform only insufficiently with respect to the relocation error of targets to their true ground position. Only two parallel receiver channels are too little to suppress the severe ground clutter and to estimate the target's parameters. Although this deficiency may partly be alleviated through antenna aperture switching, the resulting positioning accuracy is still not adequate for effective traffic monitoring purposes. Satisfactory results are only achievable with extended apertures, primarily with satellite constellations. This letter presents a statistical analysis of the performance of different concepts for cooperating back-to-back flying satellite systems. Particularly in anticipation of TanDEM-X, which will form the first operational GMTI-capable coherent synthetic aperture radar constellation after its launch in 2009.

Ground moving target indication (GMTI) by space-based radar systems requires special antenna and data acquisition concepts to overcome the problem of discriminating target signals from clutter returns. Owing to the high satellite speed, the clutter contains a broad mixture of radial velocities within the antenna beam, leading to a large Doppler spread. Effective clutter suppression can solely be achieved by multiple aperture or phase center antennas. For space-based systems, however, the number of receiver channels connected to subapertures is very limited due to their weight, volume, and high data rates (current systems such as TerraSAR-X and RADARSAT-2 possess only two). This classical along-track interferometry architecture, in which the antenna is split into two halves, achieves only suboptimum GMTI performance. This paper presents and statistically analyzes an innovative approach to create additional independent phase centers to improve the GMTI performance considerably. The extra degrees of freedom are created by cyclical phase and amplitude switchings of the transmit/receive modules for transmitter and receiver between pulses, hence trading Doppler bandwidth for extra spatial diversity. In the first part of this paper, different strategies of spatial-temporal diversity are introduced and analyzed for realistic system parameters with respect to ambiguities and detection performance. The second part is concerned with the elaborate theoretical analysis of the relocation improvement for the spatial diversity approach.

Ground moving target indication (GMTI) by space based radar can effectively only be performed with a multi- aperture / multi-channel system or a satellite cluster [1]. To keep weight, power consumption, data rate and costs low, the technique of switching subapertures from pulse to pulse has been proposed. While the detection performance using STAP (space-time adaptive processing) has been analysed in several publications, the estimation performance and the mechanisms leading to good or bad aperture switching strategies, have not yet been treated sufficiently. In fact, aperture partitions well suited for detection must not necessarily be good for estimation. This paper is thought as a contribution to fill the knowledge gaps concerning repositioning algorithms and performance analysis.

Recent analysis of a polarimetric synthetic aperture radar (PolSAR) velocity experiment has shown that azimuth ambiguities can provide useful information for the detection of moving targets with an across-track velocity component in PolSAR images using cross-polarization clutter cancellation. This paper examines this phenomenon using theoretical analysis and simulations and illustrates its application with experimental results. It is shown that, for reciprocal scatterers, the phase difference between HV and VH images is zero, whereas for HV and VH ambiguities, the phase difference is pi. For land applications, clutter cancellation is essential for the detection of moving targets in PolSAR images. For maritime applications, it can be used to distinguish images from ambiguities. However, it is important to note that the underlying physical reasons for the performance of clutter cancellation are entirely different from ground moving target indication along-track interferometric SAR. It is also shown that cross-pol clutter cancellation is related to filtering of a double-rate-sampled single-channel SAR signal.

This paper investigates the effects of target acceleration on estimating the velocity vector of a ground moving target from single-pass dual-channel synthetic aperture radar data. Although vehicles traveling on roads and highways routinely experience acceleration, the majority of estimation algorithms assume a constant velocity scenario, which may result in erroneous estimates of target velocity. It is shown that under most conditions, acceleration has only minor effects on the estimation of across-track velocity using along-track interferometric phase. However, under the assumption of constant velocity, acceleration may significantly bias the estimate of along-track velocity. The influence of both along-track and across-track accelerations is examined through simulations of an airborne geometry and experimental data from Environment Canada's airborne CV 580 dual-channel synthetic aperture radar system.

This paper examines the statistics of the phase and magnitude of multilook synthetic aperture radar (SAR) interferograms toward deployment of along-track interferometry (ATI) for slow ground moving-target indication (GMTI). While the known probability density function (pdf) of the interferogram's phase (derived under the assumption of Gaussian backscatter) is shown to agree almost perfectly for a wide variety of backscatter conditions, the corresponding magnitude's pdf tends to deviate strongly in most cases. Motivated by this discrepancy, a novel distribution is derived for the interferogram's magnitude. This pdf, called the polynomial or p-distribution, matches the real data much more accurately, particularly for heterogeneous composite terrain. For extremely heterogeneous terrain, such as urban areas, both pdfs for interferometric phase and magnitude fail and are extended. Based on these statistics, a completely automatic detection scheme with constant false-alarm rates (CFARs) for slow moving targets is proposed. All involved parameters required to determine the detection thresholds are estimated from the sample data. It is demonstrated, on the basis of experimental airborne SAR data, that this detector is capable of detecting slow moving vehicles within severe ground clutter.

The RADARSAT-2 satellite includes an experimental mode, called the moving object detection experiment (MODEX), which is to be used to perform ground moving target indication (GMTI) using a C-band synthetic aperture radar (SAR). During MODEX operation, the SAR antenna is partitioned into two subapertures along the satellite track to sequentially observe the same scene from the same spatial point. By appropriate processing of the returned signals from each channel, detection of temporal changes in the scene (i.e. moving targets) can be accomplished. The MODEX configuration will be used by the Canadian Department of National Defense RADARSAT-2 GMTI demonstration project, which aims to develop a SAR-GMTI processing system to investigate the military and commercial utility of space-based moving target measurements. This paper discusses a conceptual SAR-GMTI processor design in terms of selected algorithms and their performance, such as along track interferometry (ATI), displaced phase center antenna (DPCA) and iterative moving target (terrain) matched filtering (MTMF). Processing issues arising in space based radar (SBR) GMTI are also discussed. It is anticipated that the ultimate processor design will incorporate these algorithms as independent processing configurations, along with selection rules that will optimize their use to the contents of the image scene.

This paper investigates the capability of classical two-channel SAR ground moving target indication (GMTI) techniques, such as displaced phase center antenna (DPCA) or along-track interferometry (ATI) when implemented on azimuth-uncompressed SAR data, rather than the processed SAR image. By transforming the data into the Doppler frequency domain complete target detection and parameter estimation scheme is proposed. In contrast to the conventional image based algorithms, the proposed techniques are able to detect even fast movers. The GMTI feasibility is demonstrated with measured airborne data.

In interferometric SAR applications, the complex coherence between two channels, /spl rho/e/sup j/spl theta//, and the effective number of looks, n, are required to describe the joint channel statistics. Accurate modeling of the statistics is critical in the determination of Ground Moving Target Indication (GMTI) CFAR detection rules in along-track interferometry, and the estimation of topography accuracy in across-track interferometry. In this paper, we propose a method for estimating n and /spl rho/ based on the interferometric phase density function. We validate the robust, real-time implementable method with real SAR data in various types of terrain. Particularly, we show how the method can be extended to model the phase distribution even in extremely heterogeneous terrain. We show that the estimation relies only upon the multi-looked interferogram, without reference to the individual channels thereby reducing data storage requirements.

The on-orbit alignment of the antenna beams of both the X-band and C-band radar systems during operations of the shuttle radar topography mission/X-band synthetic aperture radar (SRTM/X-SAR) was a key requirement for achieving best interferometric performance. In this paper, we consider the X-SAR antenna beam alignment in azimuth. For a single-pass cross-track SAR interferometer, we establish the relation between yaw and pitch misalignment of the antenna beams and the resulting relative shift of the Doppler frequency bands. This relation is used to provide solutions for the mechanical adjustments of the outboard antenna and electronic beam steering to correct for azimuth misalignment. Furthermore, the effects of the X-SAR effective outboard antenna pattern on the azimuth beam alignment are analyzed. As a result, a so-called "relaxing" factor is derived, which increases the limit for the difference in antenna azimuth angle with respect to the requirement on spectral overlap, and hence spatial interferogram resolution. However, we also show that the alignment requirement is driven by the constraint on decreasing the azimuth ambiguity-to-signal ratio (AASR) for the effective outboard antenna pattern to reduce the resulting additional height error. The strategy for misalignment determination and correction is presented, and results of the analysis of the in-flight X-SAR antenna beam alignment are discussed.

The probability density function (pdf) of the multi-look interferometric phase between two complex synthetic aperture radar (SAR) images is parameterized by the number of looks and the complex correlation coefficient. In practice, adjacent pixels in a real SAR interferogram, are statistically dependent due to filtering, and hence, the number of looks is usually smaller than the number of samples averaged. It has been shown that compensation with an effective number of looks, rather than an intractable rederivation of the pdf, can account for the statistical dependence. This paper addresses the challenge of how to determine a suitable value for the effective number of looks. It is shown that an optimum value can be found via a maximum-likelihood estimator (MLE) based on the interferometric phase pdf. However, since such an MLE is computationally intensive and numerically unstable, an estimator based on the method of moments (MoM) possessing similar fidelity is proposed. MoM is fast and robust and can be used in operational applications, such as determining constant false alarm rate (CFAR) detection thresholds for moving-target detection in SAR along-track interferometry.