Showing papers on "Moving target indication published in 2011"

Radar Detection of Moving Targets Behind Corners

Abstract: Detection of moving objects concealed behind a concrete wall corner has been demonstrated, using Doppler-based techniques with a stepped-frequency radar centered at 10 GHz, in a reduced-scale model of a street scenario. Micro-Doppler signatures have been traced in the return from a human target, both for walking and for breathing. Separate material measurements of the reflection and transmission of the concrete in the wall have showed that wall reflections are the dominating wave propagation mechanism for producing target detections, while wave components transmitted through the walls could be neglected. Weaker detections have been made of target returns via diffraction in the wall corner. A simple and fast algorithm for the detection and generation of detection tracks in down range has been developed, based on moving target indication technique.

The Influence of Target Micromotion on SAR and GMTI

Abstract: This paper analyzes the influence of typical target micromotions on synthetic aperture radar (SAR) images, azimuth resolution limit, SAR/ground moving target indication (GMTI), and MTI. According to the micromotion periods contained in the coherent processing interval, a new range model expansion and a generalized paired echo principle are proposed and applied to underlie the analysis. Several new kinds of image characteristics including gray strips, ghost points, and fences are reported, which are sheerly distinct from those of slow movers. Micromotion will also cause a prominent range cell migration even if its amplitude is far smaller than the range resolution. SAR/GMTI and MTI techniques will, in general, become invalid for micromotion targets. The influence is eventually demonstrated by the simulated data in the airborne single-channel geometry, and it can be used for SAR image interpretation as well as passive jamming.

Application of clutter reduction techniques for detection of metallic and low dielectric target behind the brick wall by stepped frequency continuous wave radar in ultra-wideband range

Abstract: A study of clutter reduction techniques for detection of metallic and non-metallic (low dielectric constant) targets behind a brick wall with the help of ultra-wideband (UWB) through wall imaging system is presented. It is known that sometimes the clutter level is comparable to the level of target reflection that makes it difficult to detect the target correctly. Detection of low dielectric constant materials becomes more difficult due to low reflection from such targets. Therefore there is a need to analyse various clutter removal techniques and check the performance of these techniques for enhancement of target signal-to-clutter ratio. For this purpose, an UWB stepped frequency wave radar is indigenously assembled with the use of vector network analyser, which works in the frequency range of 3.95–5.85 GHz. An experiment is carried out for detection of metal as well as Teflon (low dielectric constant) targets with the application of clutter reduction techniques. The authors have considered statistical-based techniques like singular value decomposition, principle component analysis, factor analysis and independent component analysis (ICA) for clutter removal. It is observed that the signal-to-clutter ratio for metal target detection is quite enhanced by all the four techniques, whereas only ICA is able to enhance the signal-to-clutter ratio for a low dielectric constant target like Teflon.

Ground Moving Target Indication via Multichannel Airborne SAR

Abstract: We consider moving target detection and velocity estimation for multichannel synthetic-aperture-radar (SAR)-based ground moving target indication (GMTI). Via forming velocity versus cross-range images, we show that small moving targets can be detected even in the presence of strong stationary ground clutter. Furthermore, the velocities of the moving targets can be estimated, and the misplaced moving targets can be placed back to their original locations based on the estimated velocities. An iterative adaptive approach, which is robust and user parameter free, is used to form velocity versus cross-range images for each range bin of interest. Moreover, we discuss calibration techniques to estimate the relative antenna distances and antenna gains in practical systems. Furthermore, we present a simple algorithm for stationary clutter cancelation. We conclude by demonstrating the effectiveness of our approaches by using the Air Force Research Laboratory publicly released Gotcha airborne SAR-based GMTI data set.

A Novel Moving Target Detection Approach for Dual-Channel SAR System

Abstract: A novel approach to moving target detection is proposed for dual-channel SAR system. This approach is on the basis of eigen- decomposition of the sample covariance matrix and examines the statistic of the second eigenvalue and the Along-Track Interferometric (ATI) phase for ground moving target indication. Based on this statistic, a new Constant False Alarm Rate (CFAR) detector can be designed to solve the problem of GMTI. To detect slow moving targets more accurately, the second eigenvalue and the ATI phase pre- thresholds are implemented before a CFAR detector. Experimental results on measured SAR data are presented to demonstrate that this novel detector has wider range of detection velocity and lower false alarm probability.

Along-track interferometry for simultaneous SAR and GMTI: application to Gotcha challenge data

Abstract: This paper describes several alternative techniques for detecting and localizing slowly-moving targets in cultural clutter using synthetic aperture radar (SAR) data. Here, single-pass data is jointly processed from two or more receive channels which are spatially offset in the along-track direction. We concentrate on two clutter cancelation methods known as the displaced phase center antenna (DPCA) technique and along-track SAR interferometry (AT-InSAR). Unlike the commonly-used space-time adaptive processing (STAP) techniques, both DPCA and AT-InSAR tend to perform well in the presence of non-homogeneous urban or mountainous clutter. We show, mathematically, the striking similarities between DPCA and AT-InSAR. Furthermore, we demonstrate using experimental SAR data that these two techniques yield complementary information, which can be combined into a "hybrid" technique that incorporates the advantages of each for significantly better performance. Results are generated using the Gotcha challenge data, acquired using a three-channel X-band spotlight SAR system.

Track Segment Association for GMTI Tracks of Evasive Move-Stop-Move Maneuvering Targets

Abstract: In a real tracking system, track breakages (TBs) can occur due to highly maneuvering targets, low detection probability, or clutter. In [27], a track segment association (TSA) approach was developed for an airborne early warning (AEW) system to improve track continuity by "stitching" broken track segments pertaining to the same target. However, this technique cannot provide satisfactory association performance in tracking with a ground moving target indicator (GMTI) radar ground moving targets employing evasive move-stop-move maneuvers. To avoid detection by a GMTI radar, targets can deliberately stop for some time before moving again. Since a GMTI radar does not detect a target when the radial velocity (along the line-of-sight from the sensor) falls below a certain minimum detectable velocity (MDV), the move-stop-move maneuvers of the targets usually lead to broken tracks as a result. We present a new TSA technique which employs a dummy track to formulate a complete association. By using an interacting multiple model (IMM) estimator with state-dependent mode transition probabilities (IMM-SDP) for track segment prediction (forward and backward), the proposed algorithm can effectively stitch both "regular" broken tracks and broken tracks due to targets' move-stop-move maneuvers. Comparisons are given to show the advantages of the proposed algorithm in broken tracks reduction and track continuity improvement.

Bistatic MIMO radar space-time adaptive processing

Abstract: Bistatic multiple-input multiple-output (MIMO) radar systems have the advantages of both bistatic radar and MIMO radar. In addition, the transmit angle can be obtained by processing the receive data. In this paper, bistatic MIMO and space-time adaptive processing (STAP) are applied to ground moving target indication (GMTI). It is shown that the clutter spectrum is a curve in 3-dimensions (transmit angle, receive angle and Doppler frequency) after compensation. The performances of single input multiple-output (SIMO) and MIMO cases are compared. The results show that the bistatic MIMO-STAP outperforms its SIMO counterparts in both signal interference and noise ratio (SINR) and SINR loss.

Target Tracking With Target State Dependent Detection

Abstract: Target tracking algorithms usually treat the probability of detection as independent of the target state. In most cases, this assumption is not true, with subsequent degradation in the target tracking performance from both expected and optimal levels. One typical example is the Doppler frequency based clutter rejection, the other is obfuscation (shadowing) of ground based targets, and the third is antijamming notch filtering. This dependence of the probability of target detection on the target trajectory state modulates the measurement likelihood, which, in turn, introduces measurement nonlinearity. In this paper, we first present a general algorithm for target tracking in clutter when the probability of detection is target state dependent, and then proceed to an algorithm where both target state estimate and the probability of detection are modeled by Gaussian mixtures. The probability of target existence is recursively updated as the track quality measure used for false track discrimination. A two-sensor-based ground maneuvering target tracking in clutter simulation validates this approach.

Tracking Move-Stop-Move Targets with State-Dependent Mode Transition Probabilities

Abstract: This paper presents a method for tracking ground moving targets with a GMTI radar. To avoid detection by the GMTI radar, targets can deliberately stop for some time before moving again. The GMTI radar does not detect a target when the radial velocity (along the line-of-sight from the sensor) falls below a certain minimum detectable velocity (MDV). We develop a new approach by using state-dependent mode transition probabilities to track move-stop-move targets. Since in a real scenario, the maximum deceleration is always limited, a target cannot switch to the stopped-target model from a high speed. Therefore, with the use of the stopped-target model, the Markov chain of the mode switching has jump probabilities that depend on the target's kinematic state. A mode transition matrix with zero jump probabilities to the stopped-target mode is used when the speed is above a certain "stopping" limit (above which the target cannot stop in one sampling interval, designated as "fast stage") and another transition matrix with non-zero jump probabilities to the stopped-target mode is used when the speed is below this limit (designated as "slow stage"). The stage probabilities are calculated using the kinematic state statistics from the interacting multiple model (IMM) estimator and then used to combine the state-dependent mode transition probabilities (SDP) in the two different transition matrices. The experimental results show that the proposed algorithm outperforms previous methods.

Target detection in high-resolution sea clutter via block-adaptive clutter suppression

Abstract: Attentions have been focused on the moving target detection in a high-resolution sea clutter. This study commences with a proposal of median-based estimator to estimate the power spectrum of high-resolution sea clutter by the time series observed in adjacent range cells and time intervals. The estimator provides a robust estimation when just a few aberrant time series happen in observation. Based on the estimator, a block-adaptive clutter suppression filter (BACSF) is designed to suppress the clutter prior to the pulse integration. Then, the residual clutter, the output of the BACSF, is modelled as spherically invariant random vector. Upon applying an adaptive normalised matched filter (ANMF) to the residual clutter, a residual clutter's ANMF detector is derived. Moreover, in high-resolution radar background, considering that the approximately stationary intervals of sea clutter and residual clutter are much shorter than the coherent processing interval, another heuristic block-ANMF detector is proposed. It can integrate more pulses and can achieve better performance than the ANMF detector does. This study concludes with the experiments of simulated target against the real sea clutter. The experimental results demonstrate that, when target's Doppler frequency is beyond strong clutter region, the ANMF detector and block-ANMF detector perform better in the residual clutter than in the clutter.

A compressive sensing approach to moving target indication for urban sensing

Abstract: In this paper, we apply compressive sensing to moving target indication for urban sensing and through-the-wall imaging applications using stepped-frequency radar. In particular, we consider sparsity-driven imaging combined with change detection. Stationary targets and clutter are removed via change detection, resulting in a sparse scene of few slow-moving targets inside enclosed structures and behind walls. Using compressive sensing, a sizable reduction in the number of samples is achieved without degradation in system performance. Laboratory experiments are conducted to validate the proposed approach.

Design and performance analysis of orthogonal coding signal in MIMO-SAR

Abstract: Multi-input multi-output (MIMO) radar which has evident advantages in many applications is a new radar system. Applying the MIMO technique to the earth observing synthetic aperture radar (SAR) system offers effective ways for the improvement of high resolution and wide swath imaging and ground moving target indication (GMTI) systems. Designing the optimal orthogonal waveform is a crucial problem in the research on MIMO radar. First, the index definition of synthetic integrated side-lobe level ratio (ISLR) is proposed by focusing on the SAR application and considering the cross-correlation energy influences between orthogonal coding signals with the same frequency band. Second, it is theoretically demonstrated that the performance of synthetic ISLR of orthogonal coding signals with the same frequency band cannot meet the demands of SAR imaging, which has been proved by one-dimensional numerical simulation. Third, it has been shown through numerical simulation that the performance of synthetic ISLR of orthogonal coding signals still cannot be improved by dealing with the mismatched filtering. Finally, a set of orthogonal phase coding signals are designed for multiple MIMO-SAR antennas. The conclusions are verified through MIMO-SAR imaging and InSAR simulation experiments.

Doppler-offset waveforms for MIMO radar

Abstract: In a Multiple-Input, Multiple-Output (MIMO) radar, independent waveforms are transmitted from different locations, with the resulting reflections processed to form a “virtual antenna array” that is larger than the physical aperture of the radar. This paper examines the design of Doppler-offset waveforms for use in adaptive MIMO GMTI radar systems. Such waveforms provide good adaptive cancellation performance, but are also subject to strong range and Doppler ambiguities. We analyze these ambiguities, and show how they relate to array topology and waveform design. Then, we describe a new waveform approach, called “Dithered DDMA,” which enables high performance clutter cancellation over large range-Doppler regions without introducing ambiguous ranges or blind speeds, and without increasing the computational load on the MIMO processor.

Efficient Strip-Mode SAR Raw-Data Simulation of Fixed and Moving Targets

Abstract: The performance of the high-resolution synthetic aperture radar (SAR) with moving-target indication and imaging systems can be analyzed and evaluated by modeling the whole imaging system through a simulation. The raw-data generation in the time domain achieves a realistic simulation procedure provided that computational complexity can be tolerable. In this letter, we proposed an efficient SAR raw-data generator of a scene that includes both static and moving targets. The raw data set of an extended scene and the moving target is simulated in the frequency domain separately and superposed in the time domain. The generated raw data for fixed and moving targets are also processed and analyzed.

Intent Inference and Syntactic Tracking with GMTI Measurements

Abstract: In conventional target tracking systems, human operators use the estimated target tracks to make higher level inference of the target behaviour/intent. The work presented here develops syntactic filtering algorithms that assist human operators by extracting spatial patterns from target tracks to identify suspicious/anomalous spatial trajectories. The targets' spatial trajectories are modeled by a stochastic context free grammar (SCFG) and a switched mode state space model. Bayesian filtering algorithms for SCFGs are presented for extracting the syntactic structure and illustrated for a ground moving target indicator (GMTI) radar example. The performance of the algorithms is tested with the experimental data collected using DRDC Ottawa's X-band Wideband Experimental Airborne Radar (XWEAR).

Decision-Level Fusion Performance Improvement From Enhanced HRR Radar Clutter Suppression

Abstract: Airborne radar tracking in moving ground vehicle scenarios is impacted by sensor, target, and environmental dynamics. Moving targets can be characterized by 1-D High Range Resolution (HRR) Radar profiles with sufficient Signal-to-Noise Ratio (SNR). The amplitude feature information for each range bin of the HRR profile is used to discern one target from another to help maintain track or to identify a vehicle. Typical radar clutter suppression algorithms developed for processing moving ground target data not only remove the surrounding clutter, but a portion of the target signature. Enhanced clutter suppression can be achieved using a Multi-channel Signal Subspace (MSS) algorithm, which preserves target features. In this paper, we (1) exploit extra feature information from enhanced clutter suppression for Automatic Target Recognition (ATR), (2) present a Decision-Level Fusion (DLF) gain comparison using Displaced Phase Center Antenna (DPCA) and MSS clutter suppressed HRR data; and (3) develop a confusion-matrix identity fusion result for Simultaneous Tracking and Identification (STID). The results show that more channels for MSS increase identification over DPCA, result in a slightly noisier clutter suppressed image, and preserve more target features after clutter cancellation. The paper contributions include extending a two-channel MSS clutter cancellation technique to three channels, verifying the MSS is superior to the DPCA technique for target identification, and a comparison of these techniques in a novel multi-look confusion matrix decision-level fusion process.

Performance Measures and MHT for Tracking Move-Stop-Move Targets with MTI Sensors

Abstract: We consider the problem of tracking ground-based vehicles with moving target indicator (MTI) sensors. MTI sensors can only detect a target if the magnitude of the range-rate exceeds the minimum detectable velocity, and as a result targets typically exhibit evasive move-stop-move (MSM) behavior in order to avoid detection. Further complexity is added by the fact that the environment is cluttered, resulting in both missed detections and spurious false measurements. A key problem is then to distinguish between a missed detection of a moving target and a lack of a detection due to the target stopping (or moving at low velocity). In this paper, we provide a novel framework for calculating performance measures (which are not necessarily bounds) for this problem. Our approach unifies state-of-the-art posterior Cramer-Rao lower bound (PCRLB) approaches for dealing with manoeuvring targets (namely, the best-fitting Gaussian approach) and cluttered environments (the measurement sequence conditioning approach). Our approach is also able to exploit the correlation between the number of measurements at each sampling time and the target motion model. Furthermore, we are able to show that established PCRLB methodologies are special cases of this unifying approach. We therefore provide a general technique for calculating performance bounds/measures for target tracking that can be applied to a broad range of problems. We also introduce a multiple hypothesis tracker (MHT) implementation for this problem. In simulations, the MHT is shown to accurately track the target, and provided that the probability of detection is close to unity, the new performance measure is an extremely accurate predictor of the localization performance of the MHT. If the probability of detection is lower, and except when employing a short scanback, the MHT performance is significantly better than the measure. In such cases the true limit of performance is the measure calculated by assuming the correct motion model, and data association hypotheses are known. The MHT filter is also shown to maintain track of the target in a high percentage of simulations, even with a scanback of just a few time steps. Therefore if track maintenance is the most important requirement, the employment of long scanbacks is not essential. We conclude that our PCRLB-like measure and MHT implementation provide effective approaches for performance prediction and target tracking, respectively, in the challenging MTI domain.

Heart-beat detection and ranging through a wall using ultra wide band radar

Abstract: Heart-beat detection has found many applications in military and bio-medical areas. Many of these applications focus on the use of impulse based ultra wide band (UWB) radars. This in-turn requires expensive hardware and consumes more power (for a given range) compared to stepped frequency continuous wave (SFCW) radars. However, the micro-Doppler characteristic of human body can be detected by SFCW radar at much lower sampling rates and power. It can help in distinguishing a living and a non-living target. In addition, SFCW radar can help separate Doppler signatures in down-range, thus enabling it to look for multiple human targets. UWB radars operate at a bandwidth higher than 0.5 GHz and have the benefit of high range resolution. This paper focuses on the experimentation of a technique to obtain the range and Doppler of a human body using UWB-SFCW radar and moving target indicator (MTI) filter, in the presence of an interfering wall.

Large along-track baseline SAR-GMTI: First results with the TerraSAR-X/TanDEM-X satellite constellation

Abstract: In the paper first ground moving target indication (GMTI) and parameter estimation results obtained with the spaceborne TerraSAR-X/TanDEM-X satellite constellation are presented and discussed. For processing a dual-platform GMTI algorithm developed by the authors was used. This algorithm enables the estimation of the true geographical positions, the velocities and the headings of the detected targets with high accuracy. The algorithm is verified and evaluated using ground truth reference data.

Method for locating static human body through wall based on respiratory character

Abstract: The invention provides a method for locating a human body through a wall and belongs to the technical field of radar detection. The method comprises the following steps: 1) preprocessing echo signals of two receiving antennae to form two quick and slow time data matrixes; 2) performing moving target indication (MTI) filtering; 3) performing band-pass filtering; 4) performing fast Fourier transform (FFT) spectrum analysis on two quick and slow time data matrixes which are subjected to the band-pass filtering respectively to form two range delay-Doppler frequency (RD) data matrixes; 5) detecting two-dimensional adaptive cell average constant false alarm rate; 6) estimating the echo distance delay of a static human body corresponding to the two receiving antennae by use of a moving window extremum method on two detected RD planes to; and 7) carrying out elliptical cross positioning. The method ensures the accuracy of static human body echo delay estimation through frequency domain accumulation of respiratory character signals, combined inhibition of various different clutters and elimination of range delay fuzzy so as to realize the accurate positioning of a static human body, and has the prominent advantages of strong interference resistance, high positioning accuracy and strong practicality.

Velocity ambiguity resolving for moving target indication by compressed sensing

Abstract: A novel velocity ambiguity resolving method is proposed for moving target indication, in which compressed sensing (CS) is applied to recover the unambiguous Doppler spectrum of targets from randomly pulse repetition frequency-jittering pulses. Weighting in CS recovery is utilised to suppress the clutter by using prior knowledge of the clutter spectrum. Experimental results demonstrate the effectiveness of the proposal.

Target statistical correlation characteristic for spatial-frequency jointly diversity multiple-input multiple-output radar

Abstract: In diversity multiple-input multiple-output (MIMO) radar system, the mutual correlation of target echo signals in its diversity channels is an important concern for designing signal processing algorithms. The target temporal, spatial and frequency correlation characteristic is studied at the background of a diversity MIMO radar with multiple widely separated radar sites all capable of working at multiple carrier frequencies. With a two-dimensional round-shaped scatterers centre target model, the correlation coefficient of target echo signals in any type of diversity channel pair (DCP) is proved to be a function of the target size and the equivalent frequency interval. The theoretical correlation coefficient is verified by numerical experiments. The correlation coefficient of target echo signals often depends on the target location, which is shown for two typical DCP types.

Common waveform for simultaneous SAR and GMTI

Abstract: Surveillance RADARs normally share time for detecting fixed and moving targets. With modern digital waveform synthesis and high performance computing, it is feasible to collect signals that use space, time and frequency encoding to simultaneously operate in GMTI and SAR modes. This paper summarizes a new waveform and adaptive RADAR architecture with the potential for simultaneous SAR and GMTI operation, along with a detailed simulation of target detections.

Automatic target recognition with unknown orientation and adaptive waveforms

Abstract: In previous work, we have demonstrated the utility of a feedback loop for enabling optimized transmit pulse shaping in radar target recognition. This previous work was based on low-fidelity target models, but in this paper, we demonstrate the closed-loop, adaptive-waveform approach applied to high-fidelity target model signatures generated by commercial electromagnetic FDTD software. We also incorporate the radar equation into our models for us in the waveform design procedure. Because SNR varies with range, so do our optimized waveforms for target recognition. Constant-modulus waveform constraints are enforced, and a template-based classification strategy is used.

Extended and multiple target tracking: Evaluation of an hybridization solution

Abstract: In the usual multiple target tracking systems, detections associated to the targets are considered as issued from a single point source. This hypothesis is true if the size of the sensor resolution cells is bigger than the size of the target and if there is only one target in the resolution cell. Due to the increasing resolution capabilities of modern sensors this hypothesis is considered valid for the small targets (like ground vehicles). However, in real situations observed with modern GMTI (Ground Moving Target Indicator) sensors we cannot neglect the sensor resolution phenomenon: for littoral surveillance applications, the large targets (or extended targets) can generate more than one detection at a time; in addition for ground surveillance applications the distance between the individual targets can often be less than the size of the resolution cell which produces only one detection for a group of targets. On those considerations, we must adapt our individual targets' tracking algorithm with the extended and group tracking algorithms. In this paper, we test a very simple hybridization between a multiple target tracking algorithm and the recent bayesian approach for extended object tracking and group tracking represented by a random symmetrical positive definite matrix.

Parameter Estimations Based on DPCA-FrFT Algorithm for Three-channel SAR-GMTI System

Abstract: On the basis of deep analysis of DPCA technique and FrFT, the DPCA-FrFT algorithm which can realize detection and parameter estimations of moving target for three-channel SAR-GMTI system, is presented in this paper. Because of the good capability of DPCA technique for clutter cancellation and the nice attribute of FrFT for LFM signal detection, the DPCA-FrFT algorithm can suppress the clutter and realize the localization and velocity estimations well in different SCR conditions. The simulation results validate the effectiveness of this algorithm.

Improvement in detection with forward scattering radar

Abstract: Forward scattering radar (FSR) has advantages over traditional monostatic radar such as an enhanced radar cross section. Enhancement of the radar cross section can increase the detection range of the FSR system. This feature has renewed interest in FSR. The latest development of the FSR system for ground application does not consider a rough environment and there is no advanced signal processing technique for the detection procedure, which have delayed the deployment of FSR. Therefore, this paper analyzes a signal processing technique that extracts the Doppler signal scattered from a moving target under the influence of ground clutter, receiver noise and surrounding noise. The scattered Doppler signal is processed for target detection. Two methods, namely the use of the Hilbert transform and wavelet technique, are evaluated. Results show that target detection using a Hilbert transform is applicable only for certain conditions but target detection employing the wavelet technique is more robust against clutter and noise. An inclusive comparison of various wavelet threshold selection rules for different types of wavelet filters and levels of decomposition is conducted to study the effect on target detection with FSR. Two sets of field experiments were carried out to validate the proposed method, and target signals under the influence of large clutter were successfully detected using the proposed method with a confidence level exceeding 75%.

Detect and autofocus the moving target by its range walk in time domain

Abstract: Due to its radial velocity, the range walk (linear term of range migration) of a moving target in synthetic aperture radar (SAR) image is usually bigger than that of the stationary target. Hence in the time domain after range cell migration correction, the trajectory of most moving target is usually characterized by an approximate sloping line, while the trajectory of stationary targets is lines parallel to the azimuth direction (flight path). Exploiting this difference, we propose a novel ground moving target indication method to detect the moving target in time domain, which is different from the conventional methods. The proposed method has the advantage of detecting the slow moving target and can be used in low pulse repetition frequency SAR. Moreover, an autofocus technique is proposed to improve the focusing effect and the parameter estimation accuracy of the moving target. Raw SAR data is used to demonstrate the performance of the proposed method.