Modified Adaptive 2-D Calibration Algorithm for Airborne Multichannel SAR-GMTI

Ground moving target indication (GMTI) plays an important role in surveillance and reconnaissance applications, but it is a difficult problem due to the impacts of stationary clutter. This paper proposes a multichannel synthetic aperture radar (SAR) using waveform diversity, namely, multiple-input multiple-output (MIMO) SAR and distinct carrier frequency for GMTI applications. The proposed approach employs MIMO configuration with multiple antennas in azimuth and orthogonal waveform diversity. In doing so, multiple independent transmit-receive channels are formulated at the receiver. Since each antenna uses both waveform diversity and distinct carrier frequency, after clutter cancellation and noise suppression by the displaced phase center antenna (DPCA) and along-track interferometry (ATI) combined processing algorithm, the cross-track velocity is estimated through double-interferometry processing. Next, the Doppler parameters of moving targets are estimated with the fractional Fourier transform algorithm and then GMTI is obtained by a joint signal processing algorithm. Finally, the moving targets are focused with a general chirp scaling imaging algorithm. All the proposed methods are verified by simulation results.

In this paper, we present the results of a modeling study to examine the interference effect of microDopplers caused by offshore wind farms on airborne sensors operating in the synthetic aperture radar (SAR) and ground moving target indicator (GMTI) modes. The modeling is carried out by generating CAD instantiations of the dynamic wind turbine and using the high-frequency electromagnetic code Xpatch to perform the scattering calculations. Artifacts in the resulting SAR and GMTI signatures are evaluated for interference with tracking of boats in coastal waters. Results of signal filtering algorithms to reduce the dynamic turbine clutter in both SAR images and GMTI displays are presented.

This paper investigates different metrics for ground moving target indication (GMTI) with a multichannel synthetic aperture radar (SAR). These metrics are especially sensitive to targets that have an across-track component of velocity, v/sub y/, although they can also detect targets with an along track velocity component, v/sub x/. Not only are the metrics suitable for fully SAR compressed data, they are also meaningful when computed for range (pulse) compressed but Doppler uncompressed data (raw data). The use of both data domains allows for target detection over a larger v/sub y/ range than either used individually. For large v/sub y/, side-lobe suppression in fully SAR compressed data simultaneously suppresses the targets, giving an advantage to the raw data domain. For low v/sub y/, and especially with low RCS targets, the SAR compression gain facilitates detection, giving an advantage to the SAR compressed domain. By viewing the SAR compression as the application of a linear filter, the metrics are shown to be suitable for target detection after any linear filtering of the raw data, such as a linear time-frequency filter, or a simple transformation into the Doppler domain using an FFT filter. The metrics have in common that they are all based on the eigenvector decomposition of the sample covariance matrix. Their statistical properties are analytically compared and their detection capabilities are demonstrated on measured two-channel airborne SAR data in a variety of data domains. Some metrics are shown to allow target detection with low false alarm rates even in heterogeneous terrain, such as in urban areas, without compromising the probability of detection.

Multiple-input multiple-output synthetic aperture radar (MIMO SAR) system has drawn considerable attention for its wider detected swath without decreasing PRF compared to the traditional multichannel synthetic aperture radar (MC-SAR) system. For MIMO SAR system, how to extract the matched signal or suppress the unmatched interferences is the foremost task. Using the OFDM chirp signals as the transmitted signals, the robust principal component analysis (RPCA) based method can be employed for ground moving target indication (GMTI) with no need for separating the matched signal and unmatched interferences. The simulation demonstrates the effectiveness of RPCA based method for GMTI in MIMO SAR system.

The azimuth multichannel synthetic aperture radar (SAR) system is used in ground moving target indication (GMTI). But for Ka-band SAR, the conflicts between high gain and wide swath coverage are very strict. The digital beamforming (DBF) scan-on-receive (SCORE) algorithm can solve this problem very well. This letter introduces a multichannel SAR system with three receiving antennas in the azimuth direction. For each azimuth antenna, eight subapertures are arranged in the elevation direction in order to obtain higher gain and a lower data rate through the DBF-SCORE algorithm. Airborne flight experiments with this system are accomplished successfully and quantities of experimental data are acquired. In this letter, we first derive the signal forms and weighting coefficients in the DBF-SCORE procedures. Then, different GMTI methods including along-track interferometry and displaced phase center antenna are introduced for azimuth multichannel SAR–GMTI based on the DBF-SCORE technology. Finally, airborne raw data with cooperating moving targets are processed successfully, and the estimation errors of the radial velocities meet the expected accuracy requirements.

This letter addresses an efficient algorithm for ground moving target detection and estimation of motion parameters by synthetic aperture radar (SAR). The proposed method outperforms the conventional robust principal component analysis (RPCA)–based ground moving target indication (GMTI) methods that were proposed in the literature. The ability to estimate the radial and along-track velocities of ground moving targets is provided. The rank constraint in the conventional RPCA problem will be automatically relaxed by employing a dictionary matrix for clutter representation. Thus, the new optimization problem will be solved easier with lower degrees of freedom. Furthermore, this dictionary helps to suppress the clutter of higher Doppler frequencies in case of wind blowing scenarios and intrinsic clutter motion modeling. By employing another dictionary matrix for all possible moving targets with different location and velocity, each solution of the optimization problem will be reasonable as it corresponds to a moving target. Although, the two dictionary matrices impose extra computational burden, this load will be prepared prior to other GMTI processing by the information of the SAR system and scenario parameters. Moreover, the algorithm is proposed for the single-channel SAR configurations and has lower computational load than the conventional RPCA-GMTI methods that have to process the recorded data of multichannel systems. Numerical and experimental results are used to evaluate the performance of the proposed method and validate the theoretical discussions.

This paper addresses four-dimensional ground moving target indication (GMTI) using a multi-channel wide band (WB) synthetic aperture radar (SAR) system. With no acceleration attached to the target the motion of the target is related to two ground and two speed coordinates. However, four other dimensions are used in WB SAR GMTI processing during the detection phase: azimuth, range, bearing, and the relative speed between the object and the SAR platform. In the detection phase, blind hypotheses are used, and the discretization steps between the hypotheses are a trade-off between the number of hypotheses tested and detectability. As the integration angle increases, the step size in the image dimensions and in the relative speed has to be reduced. In this paper we determine the discretization step in all four dimensions for moving target detection, and relate it to radar system parameters. The discretization is derived from the moving target impulse response, assuming independency between the dimensions. In the paper the number of hypotheses per square meter is given for an airborne low frequency and a microwave GMTI WB SAR system.

This paper studies the range equation modeling of a ground moving target for multichannel medium-Earth-orbit (MEO) synthetic aperture radar (SAR) ground moving target indication (GMTI), an issue which is challenging to tackle due to the non-linear motion of the radar platform and the Earth rotation. In the paper, the coordinates of the multichannel MEO SAR and the target, as well as the target’s range equation with respect to each channel, are developed. Moreover, an expression of concise form is derived for the target’s quadratic-approximated range equation, which will benefit the design of GMTI methods. Furthermore, theoretical analyses are conducted to reveal the dependency between the accuracy of the quadratic-approximated range equation and the parameters of the radar and the target. Numerical simulations are carried out to investigate the influence of the quadratic approximation of the range equation on the GMTI performance and to figure out the quadratic-approximated range equation’s scope of application.

Moving targets localization is an important challenge in current synthetic aperture radar (SAR) — ground moving target indication (GMTI) system. The along track interferometry (ATI) method is usually used for GMTI in SAR, however, which suffers from ambiguous parameters estimation due to wrapped phase and less robust to estimation errors (of system parameters and motion parameters of the moving targets). Focusing on these, we propose a new neural network based method to improve the moving targets localization performance. After analyzing the main error source of the conventional ATI method, we utilize an error back propagation (BP) neural network to replace the processing after range compression in the ATI method. And the proposed method is proved effective by the experiments, and it performs much better than the conventional ATI method in localization accuracy, efficiency and robustness.

A Multi-Input Multi-Output (MIMO) Synthetic Aperture Radar (SAR) system has been considered for its potential to simultaneously improve the performance of stationary scene imaging and ground moving target indication (GMTI) by utilizing multiple subarrays both at transmission and reception. To successfully exploit the potential benefits of MIMO SAR for practical imaging application, a signal model for MIMO SAR system with colocated arrays is presented in this paper, then we propose a novel procedure for imaging processing by coherently combining the returns from multiple receive subarrays. Our approach can make efficient use of the transmitted waveform power, and resulting in higher Signal-to-Noise Ratio (SNR) images. The effectiveness of model and MIMO SAR imaging method proposed in this paper are demonstrated by simulation experiments.

Ground moving target indication (GMTI) using synthetic aperture radar (SAR) is studied in this paper. For systems using long integration time relative speed between the target and the SAR platform has to be included in the detection algorithm. A separation between the true relative speed and the relative speed used in the SAR process will cause unfocused targets. Unfocused targets decrease the detectability. In the detection phase of SAR moving targets blind hypothesis on relative are used. The step size between the hypotheses or the quantization step in relative speed is a trade off between the number of hypotheses to test and detectability. A large number of tests will increase detectability but will also increase computation load and vice versa. The importance of relative speed increases as the azimuth integration time gets larger. Long integration time is associated with low signature moving targets detection in strong clutter environment and especially for SAR GMTI at low frequencies. In this paper we determine the optimum quantization of relative speed for moving target detection. The optimum quantization is derived from the moving target impulse response. By using the optimum quantization the computation burden in SAR GMTI is reduced and the detectability secured

Ground moving target indication (GMTI) has been extensively applied in modern warfare. In this letter, a novel deceptive jamming technique for countering multichannel synthetic aperture radar (SAR)-GMTI is presented, which is implemented with the frequency diverse array (FDA). Different from the phased array (PA), FDA modulates the transmitting signal with multiple frequencies across its array elements, which, consequently, enables range-dimension false target deception for SAR imaging. Furthermore, to achieve effective deception for the GMTI, micromotion modulation is adopted to simulate dynamic features of the moving targets. Mathematical derivation and simulation results show that the proposed technique can efficiently produce massive false targets in both the range and azimuth dimensions.

Modern high-performance Synthetic Aperture Radar (SAR) systems have evolved into highly versatile, robust, and reliable tactical sensors, offering images and information not available from other sensor systems. For example, real-time images are routinely formed by the Sandia-designed General Atomics (AN/APY-8) Lynx SAR yielding 4-inch resolution at 25 km range (representing better than arc-second resolutions) in clouds, smoke, and rain. Sandia's Real-Time Visualization (RTV) program operates an Interferometric SAR (IFSAR) system that forms three-dimensional (3D) topographic maps in near real-time with National Imagery and Mapping Agency (NIMA) Digital Terrain Elevation Data (DTED) level 4 performance (3 meter post spacing with 0.8-meter height accuracy) or better. When exported to 3-D rendering software, this data allows remarkable interactive fly-through experiences. Coherent Change Detection (CCD) allows detecting tire tracks on dirt roads, foot-prints, and other minor, otherwise indiscernible ground disturbances long after their originators have left the scene. Ground Moving Target Indicator (GMTI) radar modes allow detecting and tracking moving vehicles. A Sandia program known as "MiniSAR" is developing technologies that are expected to culminate in a fully functioning, high-performance, real-time SAR that weighs less than 20 lbs. The purpose of this paper is to provide an overview of recent technology developments, as well as current on-going research and development efforts at Sandia National Laboratories.

The understanding of maneuvering forces is invaluable to the warfighter, as it enhances understanding of enemy force structure and disposition, provides cues to potential enemy actions, and expedites targeting of time critical targets. Airborne ground moving target indicator (GMTI) radars are a class of highly-effective, all-weather, wide-area senors that aid in the surveillance of these moving ground vehicles. Unfortunately conventional GMTI radars are incapable of identifying individual vehicles, and techniques for exploiting information imbedded within GMTI radar reports are limited. The Defense Advanced Research Projects Agency (DARPA) Moving Target Exploitation (MTE) program is working to mitigate these deficiencies by developing, integrating, and evaluating a suite of automated and semi-automated technologies to classify moving targets and units, and to provide indications of their activities. These techniques include: aid in the interpretation of GMTI data to provide moving force structure analysis, automatic tracking of thousands of moving ground vehicles, 1-D target classification based upon high-range- resolution (HRR) radar profiles, and 2-D target classification based upon moving target imaging (MTIm) synthetic aperture radar (SAR). This paper shall present the MTE concept and motivation and provide an overview of results to date.

In this study, a new method of effective baseline estimation is presented, which can be used for ground moving target indication (GMTI) mode of synthetic aperture radar (SAR).The basic idea is to perform the baseline estimation via exploiting the slope of the along-track interferometric (ATI) phase ramp in two-dimensional frequency domain. An integrated scheme of effective ATI-baseline estimation is proposed, which includes two key procedures: fine co-registration and median filtering. The proposed algorithm is tested with real SAR data. The results show that the incorporation of the fine co-registration and the median filtering procedures in the estimation scheme represents an accurate solution to the effective baseline estimation problem.