GMTI along-track interferometry experiment

Synthetic aperture radar (SAR) along track interferometry (ATI) has been used extensively to measure ocean surface currents. Given its ability to measure small velocities (/spl sim/ 10 cm/s) of relatively radar-dark water surfaces, there is great potential that this technique can be adapted for ground moving target indication (GMTI) applications, particularly as a method for detecting very slow targets with small radar cross-sections. In this paper we describe preliminary results from an ATI GMTI experiment. The SAR data described herein were collected by the dual-frequency NASA/JPL airborne radar in its standard dual-baseline ATI mode. The radar system imaged a variety of control targets including a pickup truck, sport utility vehicles, passenger cars, a bicycle, and pedestrians over multiple flight passes. The control targets had horizontal velocities of less than 5 m/s. The cross-sections of the targets were not purposely enhanced, although the targets' reflectivities may have been affected by the existence of the GPS equipment used to record the targets' positions. Single-look and multiple-look interferograms processed to the full azimuth resolution were analyzed. In the data processed to date, all of the targets were observed by visual inspection in at least one of the four combinations of dual-frequency, dual-baseline interferometric data. This extremely promising result demonstrates the potential of ATI for GMTI applications.     

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.     

基于时频分析的双通道SAR自旋目标检测

强地杂波背景给微动目标检测带来很大困难,为此在详细分析距离向压缩数据域自旋目标回波特性基础上,提出了基于双通道合成孔径雷达相位中心偏置天线(SAR/DPCA)和沿航迹干涉(ATI)杂波抑制的两类自旋目标检测方法,并作比较分析.在DPCA模式下,微多普勒频率沿频率(m-D)轴有一整体平移量,其与目标自旋中心的方位向坐标成...     

一种全自动的检测方法用于SAR-ATI的GMTI

针对星载SAR-ATI处理的中间结果,提出了一种称为"两步-类高斯拟合"完全自适应的检测方法。该方法可以完全自动地实现杂波和噪声中的运动目标检测,避免了传统方法作联合高斯数据的假定,无须推导SAR-ATI干涉图的理论概率密度函数。此外,该方法还可以大大降低系统的虚警概率并用仿真研究了最小可检测速度。     

Performance improvement for constellation SAR using signal processing techniques

A new concept of spaceborne synthetic aperture radar (SAR) implementation has recently been proposed - the constellation of small spaceborne SAR systems. In this implementation, several formation-flying small satellites cooperate to perform multiple space missions. We investigate the possibility to produce high-resolution wide-area SAR images and fine ground moving-target indicator (GMTI) performance with constellation of small spaceborne SAR systems. In particular, we focus on the problems introduced by this particular SAR system, such as Doppler ambiguities, high sparseness of the satellite array, and array element errors. A space-time adaptive processing (STAP) approach combined with conventional SAR imaging algorithms is proposed which can solve these problems to some extent. The main idea of the approach is to use a STAP-based method to properly overcome the aliasing effect caused by the lower pulse-repetition frequency (PRF) and thereby retrieve the unambiguous azimuth wide (full) spectrum signals from the received echoes. Following this operation, conventional SAR data processing tools can be applied to focus the SAR images fully. The proposed approach can simultaneously achieve both high-resolution SAR mapping of wide ground scenes and GMTI with high efficiency. To obtain array element errors, an array auto-calibration technique is proposed to estimate them based on the angular and Doppler ambiguity analysis of the clutter echo. The optimizing of satellite formations is also analyzed, and a platform velocity/PRF criterion for array configurations is presented. An approach is given to make it possible that almost any given sparse array configuration can satisfy the criterion by slightly adjusting the PRF. Simulated results are presented to verify the effectiveness of the proposed approaches.     

Airborne array aperture UWB UHF radar-motivation and systemconsiderations

This paper discusses the necessity, feasibility, and technology of FOPEN GMTI. It argues that this functionality may be one mode in a multi-function UWB UHF system, which jointly possesses the capabilities for air target MTI and high resolution FOPEN SAR. The radar platform may be a UAV or an aircraft, whereas, we propose to use the push boom type of antenna mounting previously adopted with the advantage for the CARABAS II UWB VHF SAR. Presently, the push booms will hold a set of UWB UHF antenna elements. This paper relates GMTI to SAR, extended from imaging stationary ground to the 4-parameter set of targets in linear and uniform motion relative to ground. It is recognised that this extended imaging problem depends on one new parameter, i.e., the SAR focusing velocity. The required signal processing may be tackled in an efficient manner by a hierarchical scheme based on iteratively merging subapertures and increasing the resolution. Rejection of stationary clutter and detection occurs on all levels of increasing resolution. This paper also provides a brief presentation of the Swedish FOA efforts to produce an experimental demonstrator of this multi-function radar system     

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.     

Extended PGA for range migration algorithms

The phase gradient autofocus (PGA) algorithm is extended to work for synthetic aperture radar (SAR) spotlight images processed with range migration (w-k) algorithms. Several pre-processing steps are proposed for aligning the range-compressed phase-history data needed for successful autofocusing of the data. The proposed algorithm gave good results for both data with large point targets and data without point targets.     

Multibaseline ATI-SAR for robust ocean surface velocity estimation

An open problem of along-track interferometry (ATI) for synthetic aperture radar (SAR) sensing of ocean surface currents is the need of ancillary wind information for inversion of Doppler centroid measurements, that have to be compensated for the propagation velocity of advancing and/or receding Bragg scatterers. We propose three classes of estimators which exploit multibaseline (MB) ATI acquisition and Doppler resolution for robust data inversion under different degrees of a priori information about the wind direction and the value of the characteristic Bragg frequency. Performance analysis and comparison with conventional ATI show that the proposed MB estimators can produce accurate velocity estimates in the absence of detailed ancillary data.     

On the resolvability of sinusoidal parameter estimates [andapplication to SAR target features]

The resolvability of 2-D (two-dimensional) sinusoidal parameter estimates is studied. These sinusoids describe the target features in SAR (synthetic aperture radar) applications. We analyze the resolvability by considering the frequency estimates of the sinusoids. Our results may be used by target classification algorithms to better classify radar targets in SAR applications     

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。     

Foliage penetration experiment

This series papers describes analyses of a foliage penetration experiment undertaken by MIT Lincoln Laboratory to assess the ability of synthetic aperture radar (SAR) to detect targets under trees. Data were taken using the NASA/JPL UHF, L-, C-band fully polarimetric SAR over a forested area in Maine in July 1990. Future experiments are planned to measure the polarimetric properties of clutter and targets using the latest ultrawideband sensors with submeter resolutions and fully polarimetric data collection capabilities     

Optimal polarimetric processing for enhanced target detection

The results of a study of several polarimetric target detection algorithms are summarized. The algorithms were tested using real target-in-clutter data collected by the Lincoln Laboratory 35 GHz synthetic aperture radar (SAR) sensor. Fully polarimetric measurements (HH, HV, VV) are processed into intensity imagery using adaptive and nonadaptive polarimetric whitening filters (PWFs). Then a two-parameter constant false alarm rate (CFAR) detector is run over the imagery to detect the targets. Nonadaptive PWF processed imagery is shown to provide better protection performance than either adaptive PWF processed imagery or single-polarimetric-channel HH imagery. In addition, nonadaptive PWF processed imagery is shown to be visually clearer than adaptive processed imagery     

Detecting moving targets in SAR imagery by focusing

A new method for detecting moving targets in a synthetic aperture radar (SAR) image is presented. It involves segmenting a complex-valued SAR image into patches, focusing each patch separately, and measuring the sharpness increase in the focused patch. The algorithm is sensitive to azimuth velocities and is exquisitely sensitive to radial accelerations of the target, allowing it to detect motion in any direction. It is complementary to conventional Doppler-sensing moving target indicators, which can sense only the radial velocity of rapidly moving targets.     

Calibration of complex polarimetric SAR imagery using backscattercorrelations

A technique for calibration of multipolarization synthetic-aperture radar (SAR) imagery is described. If scatterer reciprocity and lack of correlation between co- and cross-polarized radar echoes (for azimuthally symmetric distributed targets) are assumed, the effects of signal leakage between the radar data channels can be removed without the use of known ground targets. If known targets are available, all data channels can be calibrated relative to one another and radiometrically as well. The method is verified with simulation and application to airborne SAR data     

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.     

Multifrequency Imaging of Radar Turntable Data

In recent years synthetic-aperture radars (SAR) have proven to be very useful two-dimensional imaging tools in various fields. Based on the synthetic-aperture concepts, different imaging modes are possibe with various operating characteristics. We describe a special case where circular-projection radar data are coherently processed to yield both azimuth and range resoultion. Experiments are performed using data obtained from the radar target scatter site (RAT SCAT) radar cross-section facility. Fairly good results are obtained which illustrate the versatility of coherent syntheticaperture processing of pulse-to-pulse high-range-resolution radar returns. A discrete multifrequency stepped and pulsed waveform is the basic transmitted signal from which range-Doppler images are generated. The RAT SCAT turntable facility allows interesting model targets to be illuminated from which radar images can then be computed. One such application of the processing is described.     

Detection of small objects in clutter using a GA-RBF neural network

Detection of small objects in a radar or satellite image is an important problem with many applications. Due to a recent discovery that sea clutter, the electromagnetic wave backscatter from a sea surface, is chaotic rather than purely random, computational intelligence techniques such as neural networks have been applied to reconstruct the chaotic dynamic of sea clutter. The reconstructed sea clutter dynamical system which usually takes the form of a nonlinear predictor does not only provide a model of the sea scattering phenomenon, but it can also be used to detect the existence of small targets such as fishing boats and small fragments of icebergs by observing abrupt changes in the prediction error. We applied a genetic algorithm (GA) to obtain an optimal reconstruction of sea clutter dynamic based on a radial basis function (RBF) neural network. This GA-RBF uses a hybrid approach that employes a GA to search for the optimum values of the following RBF parameters: centers, variance, and number of hidden nodes, and uses the least square method to determine the weights. It is shown here that if the functional form of an unknown nonlinear dynamical system can be represented exactly using an RBF net (i.e., no approximation error), this GA-RBF approach can reconstruct the exact dynamic from its time series measurements. In addition to the improved accuracy in modeling sea clutter dynamic, the GA-RBF is also shown to enhance the detectability of small objects embedded in the sea. Using real-life radar data that are collected in the east coast of Canada by two different radar systems: a ground-based radar and a satellite equipped with synthetic aperture radar (SAR), we show that the GA-RBF network is a reliable detector for small surface targets in various sea conditions and is practical for real-life search and rescue, navigation, and surveillance applications     

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     

FOPEN SAR imaging using UWB step-frequency and random noisewaveforms

The detection and identification of targets obscured by foliage have been topics of great interest. Several synthetic aperture radar (SAR) experiments have demonstrated promising images of terrain and man-made objects obscured by dense foliage, by using either linear frequency modulation (LFM) or step-frequency waveforms. We present here the methodology and results of a comparative study on foliage penetration (FOPEN) SAR imaging using ultrawideband (UWB) step-frequency and random noise waveforms. A statistical-physical foliage transmission model is developed for simulation applications. The foliage obscuring pattern is analyzed by means of the technique of paired echoes. The results of the comparative study demonstrates the ability of a UHF band UWB random noise radar to be used as a FOPEN SAR. Advantages of the random noise radar system include covert detection and immunity to radio frequency interference (RFI)