Moving target imaging algorithm for SAR data

A digital processing algorithm for fine-resolution imaging of synthetic aperture radar (SAR) moving targets is described. The targets may have any translational and rotational motion components relative to the data collection platform. The algorithm requires the presence of up to three prominent points in the image of the target; the signals from these points provide estimates of the unknown target motion parameters. Phase compensation and data formatting based on these estimates eliminate motion-induced phase errors. This algorithm has been implemented on a VAX computer and used to process both simulated and real SAR data of moving targets. Results obtained using the simulated data are presented     

基于杂波对消-自聚焦的多通道SAR-GMTI

对超高频(UHF)波段多通道合成孔径雷达(SAR)动目标检测技术进行研究,解决了长相干积累时间导致动目标在方位向散焦严重的问题。采用分块自聚焦技术对多通道SAR地面移动目标指示(GMTI)系统自适应杂波抑制后的SAR图像进行处理,改善杂波抑制后的SAR图像中动目标的聚焦情况,增强动目标与周围剩余杂波的对比度,进而提高恒虚警率(CFAR)检测的性能。与传统杂波抑制后直接进行CFAR检测方法相比较,该方法降低了检测虚警概率。实测数据处理结果显示动目标的信杂比明显提高,动目标方位向聚焦成功,证明了该方法的有效性。     

无人机载多传感器图像融合评述

为了能为作战指挥系统提供清晰的局部战场信息,提高对局部战场低可观测目标的检测概率、定位精度及识别概率,迫切需要对无人机载SAR、可见光传感器、红外探测器等图像信息及其他非图像信息融合处理。提出了无人机载多传感器图像融合技术需要研究的内容,如: 图像融合新方法研究;无人机载SAR图像的非平稳性处理;基于图像融合目标检测和处理技术; 无人机载图像和非图像信息的融合问题;无人机载多传感器图像融合的实现及评估;多无人机载合成孔径雷达的协同成像;用图像融合的方法实现对运动目标检测等。分析了所提出研究内容的可行性,剖析了其中的关键技术,拟定了可能的技术路线。     

High Range Resolution Profiles as Motion-Invariant Features for Moving Ground Targets Identification in SAR-Based Automatic Target Recognition

A quantitative model analysis is presented to justify the extraction of high range resolution (HRR) profiles from synthetic aperture radar (SAR) images as motion-invariant features for identifying moving ground targets. A comparative study is conducted to assess the effectiveness in the identification process between using HRR profiles and SAR images as target signatures. The results indicate that HRR profiles are just as viable as SAR image for identification. Furthermore, a score-level multi-look fusion identification method has been investigated. It is found that a correct accurate identification rate of greater than 99 percent, a low false alarm rate, and a high level of identification confidence can be achieved, providing very robust performance.     

分数傅立叶变换用于抑制SAR杂波背景检测慢速动目标

慢速运动目标在时、空、频域上都落入主杂波区。利用单通道SAR图像中静止背景的信息抑制静止杂波,可改善检测动目标的性能。分数傅立叶变换是线性变换,不存在交叉项,采用分数傅立叶变换搜索匹配动目标信号,使其能量汇聚。对称计算旋转角正负对称的分数傅立叶变换,在两个对称的分数傅立叶域中得到两个复信号,这两个复信号中静止背景的模处处相同,而包含动目标的区域,模的幅度有很大差别,计算对称的分数傅立叶域信号对应位置模的差,取绝对值,可对消静止背景,敏锐地检测动目标。实测数据表明本算法有效。     

利用分数阶Fourier域滤波的机载SAR多运动目标检测

 强度相差较大的多运动目标检测是机载合成孔径雷达 ( SAR)技术的一个重点和难点,传统的频域滤波和现代的时频分布方法都无法解决这个问题。首先分析了机载 SAR运动目标回波本质上为线性调频信号,据此提出一种基于分数阶 Fourier域滤波的运动目标检测新方法,并且应用逐次消去的思想有效地解决了强度相差较大的多目标检测问题。仿真的结果验证了算法的有效性。     

SAR imaging of moving targets

A method of forming synthetic aperture radar (SAR) images of moving targets without using any specific knowledge of the target motion is presented. The new method uses a unique processing kernel that involves a one-dimensional interpolation of the deramped phase history which we call keystone formatting. This preprocessing simultaneously eliminates the effects of linear range migration for all moving targets regardless of their unknown velocity. Step two of the moving target imaging technique involves a two-dimensional focusing of the movers to remove residual quadratic range migration errors. The third and last step removes cubic and higher order defocusing terms. This imaging technique is demonstrated using SAR data collected as part of DARPA's Moving Target Exploitation (MTE) program     

Target motion compensation in synthetic aperture radar

In a synthetic aperture radar (SAR) targets on the ground that are moving become smeared as a result of velocity components parallel to the motion of the radar and are moved to radically different angular positions if they have velocity components perpendicular to the motion of the radar. Methods for restoring moving targets to their correct size and position are described. The samples collected for SAR processing are frequency-modulated RF pulses. Mathematically this leads to spectra that are described by Fresnel integrals. For stationary targets, the spectrum is symmetrical around the origin. If there is a moving target in a range cell, its Doppler spectrum will be displaced from the origin and may undergo other changes as a result of its nonzero velocity. Proper compensation to locate the target at the correct position requires that the spectrum be translated to a position dependent on the along-track velocity rather than to the origin. From the central frequency, the along-range velocity component can be estimated and the length of the translation can then be found. After translation, the spectrum is converted back to the time domain and the customary SAR processing is performed     

Multiple moving target detection and trajectory estimation using a single SAR sensor

A novel methodology is presented for determining the velocity and location of multiple moving targets using a single strip-map synthetic aperture radar (SAR) sensor. The so-called azimuth position uncertainty problem is therefore solved. The method exploits the structure of the amplitude and phase modulations of the returned echo from a moving target in the Fourier domain. A crucial step in the whole processing scheme is a matched filtering, depending on the moving target parameters, that simultaneously accounts for range migration and compresses two-dimensional signatures into one-dimensional ones without losing moving target information. A generalized likelihood ratio test approach is adopted to detect moving targets and derive their trajectory parameters. The effectiveness of the method is illustrated with synthetic and real data covering a wide range of targets velocities and signal-to-clutter ratios (SCRs). Even in the case of parallel to platform moving target motion, the most unfavorable scenario, the proposed method yields good results for, roughly, SCR > 10 dB.     

Moving Targets Processing in SAR Spatial Domain

This paper presents a novel technique to estimate the initial coordinates and velocity vector of moving targets, including those with velocities above the Nyquist limit, using a single synthetic aperture radar (SAR) sensor without increasing the pulse repetition frequency (PRF). The basic reasoning is that, although the returned echoes may be undersampled in the azimuth direction, their phase and amplitude are informative with respect to the moving target trajectory parameters. Therefore, the so-called blind angle ambiguity, inherent to systems using a single SAR sensor, is overcome. The proposed method samples the data in the spatial domain, along the signature curve which depends on the moving target trajectory parameters. The resulting algorithm is a highly efficient (from the computational point of view) ID matched filter. The effectiveness of the proposed scheme is illustrated using simulated SAR data and real data from the MSTAR public release data set, corresponding to a static SAR scene and a static BTR-60 with simulated motion.     

A technique for enhanced slant range resolution for SAR systems inknowledge-based environment

Synthetic Aperture Radar (SAR) is an airborne (or spaceborne) radar mapping technique for generating high resolution maps of surface target areas including terrain. High resolution is achieved by coherently combining the returns from a number of radar transmissions. The resolution of the images is determined by the parameters of the emissions, with more data giving greater resolution. A requirement of the Microwave Radar Division's SAR radar is to provide classification of targets. This paper presents a technique for enhancing slant range resolution in SAR images by dithering the carrier centre frequency of the transmitted signal. The procedure controls the radar waveforms so they will optimally perform the classification function, rather than provide an image of best quality. It is shown that a Knowledge-Based engineering approach to determining the waveform of the radar gives considerably improved performance as a classifier of targets (of large radar cross-section), even though the corresponding image is degraded     

Synthetic Aperture Imaging Radar and Moving Targets

This paper considers the effects of slowly moving targets as they appear in the output of an airborne coherent side-looking synthetic aperture imaging radar. The image of a moving reflector is described, and two approaches to airborne moving target indication (AMTI) are summarized. It is shown that the effects of target movement are decreased as the radar scan rate is increased, and are increased as the (Doppler processed) compression ratio is increased.     

空中运动目标的识别和跟踪控制

针对空中运动目标的识别和跟踪,提出图像匹配算法和连通域算法相结合的方法。该方法主要用图像匹配算法获得目标的位置信息,当图像匹配算法失效时,则采用连通域算法重新捕获目标、获得图像模板。同时,为提高跟踪的实时性,采用最小二乘线性预测法来预测目标的运动轨迹。在实验室的目标跟踪系统平台上,该方法能够对运动目标进行稳定的识别和跟踪。     

Automatic target recognition of time critical moving targets using1D high range resolution (HRR) radar

Synthetic Aperture Radar (SAR) imaging and Automatic Target Recognition (ATR) of moving targets pose a significant challenge due to the inherent difficulty of focusing moving targets. As a result, ATR of moving targets has recently received increased interest. High Range Resolution (HRR) radar mode offers an approach for recognizing moving targets by forming focused HRR profiles with significantly enhanced target-to-(clutter+noise) (T/(C+N)) via Doppler filtering and/or clutter cancellation. A goal of HRR ATR transition is the implementation and evaluation of algorithms exhibiting robustness under extended operating conditions (EOC). The public domain Moving and Stationary Target Acquisition and Recognition (MSTAR) data set was used to study 1D template-based ATR development and performance. Due to the unavailability of a statistically significant moving ground target data set, this approach was taken as an interim step in assessing the separability of ground targets when using range only discriminants. This report summarizes the data and algorithm methodology, simulated performance results, and recommendations     

Analysis of foliage-induced synthetic pattern distortions

Phase and amplitude fluctuations induced by wave propagation through foliage limit the ability of a synthetic aperture radar (SAR) system to image a target under foliage. One-way measurements of these fluctuations were done at C-, L-, UHF band during the July 1990 Foliage Penetration Experiment using single frequency CW signal sources and the NASA/JPL SAR receiver. The phase and amplitude data are coherently integrated to create the synthetic azimuthal patterns that would result when attempting to image a point target obscured by foliage. The effect of synthetic aperture length frequency, and polarization on the attenuation and azimuthal response of foliage obscured targets is investigated     

Sum-difference Reduced-dimensional Processing in SAR Image Domain and Statistical Analysis for Ground Moving Target Indication

In this article, a new reduced-dimensional adaptive processing algorithm based on joint pixels sum-difference data for clutter rejection is proposed. The sum-difference data are obtained by orthogonal projection of the joint pixels data of different synthetic aperture radar (SAR) images generated by a multi-satellite radar system. In the sense of statistical expectation, the sum-differ- ence data contain the common and different information of the SAR images. Therefore, the objective of clutter cancellation can be achieved by adaptive processing. Moreover, based on the residual image after clutter rejection, statistical analysis of constant false-alarm rate (CFAR) detection of moving targets is also presented. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm even with heterogeneous clutter and image co-registration error.     

FrFT-CSWSF:Estimating cross-range velocities of ground moving targets using multistatic synthetic aperture radar

Estimating cross-range velocity is a challenging task for space-borne synthetic aperture radar（SAR）, which is important for ground moving target indication（GMTI）. Because the velocity of a target is very small compared with that of the satellite, it is difficult to correctly estimate it using a conventional monostatic platform algorithm. To overcome this problem, a novel method employing multistatic SAR is presented in this letter. The proposed hybrid method, which is based on an extended space-time model（ESTIM） of the azimuth signal, has two steps： first, a set of finite impulse response（FIR） filter banks based on a fractional Fourier transform（FrFT） is used to separate multiple targets within a range gate; second, a cross-correlation spectrum weighted subspace fitting（CSWSF） algorithm is applied to each of the separated signals in order to estimate their respective parameters. As verified through computer simulation with the constellations of Cartwheel, Pendulum and Helix, this proposed time-frequency-subspace method effectively improves the estimation precision of the cross-range velocities of multiple targets.     

Coherent spatial filtering for SAR detection of stationary targets

Analysis of UHF synthetic aperture radar (SAR) images has revealed a spatially correlated phase structure over a resolved target such as a long wire or a large truck. This phase variation, approximated by a simple, range-dependent factor 4πr/λ, results in a line-shaped image spatial spectrum. Such image phase and spectral features can be exploited by coherent spatial filtering to improve target-to-clutter ratios of large targets and stationary target detectability in a strong clutter environment     

INS/SAR组合定位技术研究

主要研究了INS/SAR组合对运动目标的定位算法。首先,建立了INS/SAR组合定位系统数学模型;其次,基于卡尔曼滤波方法和alpha-beta滤波方法完成了INS/SAR组合定位算法设计;最后,考虑组合导航系统误差及导引头测量误差,对定位算法进行了数字仿真及性能分析。仿真结果表明,所设计的INS/SAR组合定位算法在远距对运动目标具有较高的定位精度。     

Data fusion for ground moving target tracking

The aim of ground surveillance is the large scale, continuous and near real time determination of a dynamical ground picture. This task comprises detection and tracking of moving single targets and convoys, mobile weapon systems, and military equipment. The sensors of choice are airborne Ground Moving Target Indicator (GMTI) radar and synthetic aperture radar (SAR). As ground target tracking often suffers from dense target situations, high clutter, and low visibility, the integration and fusion of external background information is essential for providing precise and continuous tracks. We present Multi Hypotheses techniques for tracking several targets in complex ground situations with clutter. Methods to incorporate topographic information, in particular digital road maps, are described and demonstrated.