一种基于波程差补偿的InISAR图像配准方法

逆合成孔径雷达(ISAR)图像配准是干涉逆合成孔径雷达(InISAR)成像领域一个关键的课题,可以实现同一散射点在不同ISAR图像中的对齐,以便于后续的ISAR图像干涉处理。该文分析了ISAR图像失配准的原因,即散射点到不同天线之间的波程差,并据此提出一种基于波程差补偿的方法来实现不同天线ISAR图像之间的精确配准。首先通过调频傅里叶变换估计目标相对于雷达的转速;进一步根据波程差与目标转动角速度的关系构建补偿相位消除散射点到不同天线间的波程差,并通过2维傅里叶变换获得配准之后的ISAR图像。最后利用干涉处理获得目标真实的3维结构。该文方法可以在回波域通过波程差补偿实现ISAR图像配准,配准之后的各散射点在图像中的位置相同;而经过相关法配准之后的ISAR图像中的各散射点之间有一个像素单元的错位,即该方法的配准效果更精确。此外,基于相关法的图像配准方法耗时达到万秒级,而基于该方法的ISAR图像配准时间仅为秒级,即该方法计算效率更高。最终的InISAR 3维成像结果中,该方法的散射点坐标重构误差为0.3034,而基于相关法的成像结果的误差(45.8529)远大于此。因此,基于所提出方法的InISAR 3维成像结果精度更高。      

Differential tomography: a new framework for SAR interferometry

A new interferometric mode crossing the differential synthetic aperture radar (SAR) interferometry and multibaseline SAR tomography concepts, that can be termed differential SAR tomography, is proposed. Its potentials, coming from the joint elevation-velocity resolution capability of multiple scatterers, are discussed. Processing is cast in a bidimensional baseline-time spectral analysis framework, with sparse sampling. The use of a modern data-dependent bidimensional spectral estimator is proposed for joint baseline-time processing. Simulated results are reported for different baseline-time acquisition patterns and two motion conditions of layover scatterers, showing that this new challenging interferometric technique is promising.     

Opposite side ERS-1 SAR stereo mapping over rolling topography

Opposite-side radar stereo images have been considered unsuitable for stereo viewing due to illumination differences which limit the ability to identify the same features in the image pair. In some contexts, like a rolling topography (slope less than 10°), the shadow, layover, and foreshortening effects, specific to radar images, will not be overwhelming with an opposite-side stereo pair. This paper reports on some issues of stereo viewing and plotting, as well as on quantitative results of mapping and features extraction from ascending and descending orbit ERS-1 SAR stereo images. Planimetric accuracy of 17 m and altimetric accuracy of 23.9 m have been achieved for lake shorelines and DEM extractions, respectively. Impacts of different parameters on the accuracy are also evaluated     

Detection and Analysis of Anisotropic Scattering in SAR Data

Scattering from man-made objects in SAR imagery exhibits aspect and frequency dependencies which are not well modeled by standard SAR imaging techniques. If ignored, these deviations will reduce recognition performance due to the model mismatch, but when appropriately accounted for, these deviations from the ideal point scattering model can be exploited as attributes to better distinguish scatterers and their respective targets. With this premise in mind, we have developed an efficient modeling framework that incorporates scatterer anisotropy. One of the products of our analysis is the assignment of an anisotropy label to each scatterer conveying the degree of anisotropy. Anisotropic behavior is commonly predicted for geometric scatterers (scatterers with a simple geometric structure), but it may also arise from volumetric scatterers (random arrangements of interfering point scatterers). Analysis of anisotropy arising from these two modalities shows a clear source-dependent relationship between the anisotropy classification and parameters of the scatterer. In particular, the degree of anisotropy is closely related to the size of the scatterer, and increasing the aperture size reduces the incidence of volumetric anisotropy but preserves the detection rate for geometric anisotropy. This result helps to address the question in the SAR community regarding the utility of wide-aperture SAR data for ATR since wide-aperture data reveals geometric anisotropy while resolving volumetric anisotropy into individual isotropic scatterers.     

基于部件级三维参数化电磁模型的SAR目标物理可解释识别方法

该文通过部件级三维参数化电磁模型(3D-PEPM)描述了复杂目标的电磁散射现象,并基于此模型提出了一种新的合成孔径雷达(SAR)目标识别方法。该方法首先根据雷达参数将3D-PEPM中各个散射体的散射响应投影到二维图像平面,预测每个散射体的位置和形状,然后根据3D-PEPM提供的先验信息评估3D-PEPM与SAR数据之间的相似程度,最后利用一种视角调整方法对整个过程进行优化,产生3D-PEPM和SAR数据之间的最终匹配分数,并根据该匹配分数完成识别决策。这种识别方法明确标识了SAR数据和3D-PEPM散射体之间的对应关系,具有清晰的物理可解释性,能够有效处理各种扩展条件下的SAR目标识别问题,仿真实验验证了该方法的有效性。      

Analysis of topographic decorrelation in SAR interferometry usingratio coherence imagery

Topographic decorrelation due to the local surface slope has been an obstacle to interferometric synthetic aperture radar (InSAR) applications. A modified spatial decorrelation function is derived as a function of the baseline and topography. This function explains the origin of the total topographic decorrelation phenomenon on the slopes directly facing radar illumination and layover, which may mislead InSAR coherence image interpretation. The authors define critical terrain slope (or critical incidence angle) as the angle for which two SAR signals completely decorrelate regardless of surface stability. It is found that the width of the critical terrain slope increases with the increase of the component of the baseline perpendicular to the radar look direction. A new analytical method, the ratio coherence imagery, is then introduced to highlight total topographic decorrelation against the temporal decorrelation features. The applications of this methodology are demonstrated in selected locations in the Sahara Desert, Algeria, and Almerı´a, Spain, using ERS-1 and ERS-2 SAR data     

The generation of SAR layover and shadow maps from digitalelevation models

As almost fully automated techniques as well as expert systems obtain more and more importance in the geocoding of synthetic aperture radar (SAR) images, the solution to the problem of the identification of homologue points between the SAR image and reference system moves into the fields of pattern recognition and feature matching. Shadow regions, which appear as dark regions in the SAR image, are independent from the backscattering of the imaged terrain. Due to the multiplicity of signals, layover regions appear brighter than the surrounding regions. Hence, the phenomena of layover and shadow are stressed in the present paper. The reasons for their occurrence are studied through the digital elevation model representing the Earth's surface. An algorithm to define layover and shadow regions directly in the geometry of the digital elevation model is presented. The results are given in a so-called layover and shadow map     

Terrain height measurement accuracy of interferometric syntheticaperture radars

Presents a simple expression for the accuracy with which an interferometer synthetic-aperture radar (IFSAR) can measure terrain elevation. The expression, derived analytically and confirmed by Monte Carlo simulation, accounts for thermal noise, resolution cell size, terrain slope and roughness, volume scattering above the terrain, radar-terrain geometry, interferometer baseline, and radar frequency. This paper takes a “glint” approach to assessing the impact of scatterers distributed in angle. The results show that there is a residual uncertainty in the height of a pixel due to its angular extent, even when the signal-to-noise ratio is very large. The analysis identifies an optimum range resolution for minimizing the height uncertainty for a particular terrain slope     

Terrain elevation mapping results from airborne spotlight-mode coherent cross-track SAR stereo

Coherent cross-track synthetic aperture radar (SAR) stereo is shown to produce high-resolution three-dimensional maps of the Earth surface. This mode utilizes image pairs with common synthetic apertures but different squint angles allowing automated stereo correspondence and disparity estimation using complex correlation calculations. This paper presents two Ku-band, coherent cross-track stereo collects over rolling and rugged terrain. The first collect generates a digital elevation map (DEM) with 1-m posts over rolling terrain using complex SAR imagery with spatial resolution of 0.125 m and a stereo convergence angle of 13.8/spl deg/. The second collect produces multiple DEMs with 3-m posts over rugged terrain utilizing complex SAR imagery with spatial resolutions better than 0.5 m and stereo convergence angles greater than 40/spl deg/. The resulting DEMs are compared to ground-truth DEMs and relative height root-mean-square, linear error 90-percent confidence, and maximum height error are reported.     

Reflectivity estimation for multibaseline interferometric radar imaging of layover extended sources

In recent years, there has been great interest in exploiting the advanced multibaseline operation of synthetic aperture radar interferometry (InSAR) for solving layover effects from complex orography, which can degrade both SAR and InSAR imagery of terrain radar reflectivity and height. In this work, the problem of retrieving radar reflectivity of layover areas is addressed. It is formulated as the problem of estimating a multicomponent sinusoidal signal corrupted by multiplicative complex correlated noise and additive white Gaussian noise. Application of nonparametric [e.g., Capon, amplitude and phase estimation filter (APES)], parametric [least squares, modern parametric RELAXation spectral estimator (RELAX)], and hybrid spectral estimators for amplitude estimation is investigated for a multilook scenario. In particular, the multilook extensions of RELAX and APES are applied to the interferometric problem. Performance analysis is investigated through a Cramer-Rao lower bound calculation and Monte Carlo simulation. The method of least squares, coupled with Capon's approach to spatial frequency estimation, multilook APES, and multilook RELAX turn out to provide accurate reflectivity estimates for undistorted multibaseline image formation of layover areas.     

Considerations for SAR image quantification unique to orbitalsystems

A discussion is presented of quantitative expressions required for the response of a synthetic aperture radar (SAR) to both point and distributed scatterers for purposes such as calibration and polarimetry. Image gains depend on the viewing geometry, which is unlike the flat Earth case, which often is assumed to apply in an orbital geometry. Image signal-to-noise ratio is dependent on footprint velocity, but the mean clutter-to-noise ratio for distributed scatterers is dependent on spacecraft velocity. When imagery of a distributed scene observed by an orbital SAR is to be calibrated by comparison to the impulse response of a reference point scatterer, for example, the velocity ratio enters the expression for peak power, but does not enter when an integral is used over the impulse response. The author also looks at the processing gain resulting from overlapping image pixels in azimuth through sampling of the pulse repetition frequency     

The Prediction of Geometric Distortions in Airborne Synthetic Aperture Radar Imagery from Autofocus Measurements

The synthetic aperture radar (SAR) is an imaging system that achieves high azimuthal resolution by tracking individual point scatterers using their phase histories, with the expected phase history of a particular point scatterer being derived from the assumed motion of the airborne SAR platform. Normally, it is assumed that the platform travels along a straight line path and that the radar pulses are emitted at equal spatial intervals. However, the aircraft carrying the SAR will be susceptible to extraneous across tracl motions and errors in the pulse spacing also may occur. These errors manifest themselves. as two forms of image degradation in the final image. Firstly, the image will be defocused due to an error in the expected quadratic phase history, and secondly, the image will contain geometric distortions due to an error in the linear phase history. An autofocus technique can be used to focus the image and produce a measure of the quadratic phase error that in turn can be used to estimate the geometric distortions that will be present in the final image. These distortions can be independently measured by direct comparison with a map of the imaged area. This paper describes the application of these methods to some real SAR data and discusses the results of the comparison of the measurements of autofocus and geometric distortions in terms of both the likely platform motions present and the viability of predicting geometric distortion using the autofocus measurements.     

A quasi-parametric algorithm for synthetic aperture radar target feature extraction and imaging with angle diversity

We present synthetic aperture radar (SAR) target feature extraction and imaging techniques with angle divesity. We first establish a flexible data model that describes each target scatterer as a two-dimensional (2D) complex sequence with arbitrary amplitude and constant phase in range and cross-range. A new algorithm, referred to as the QUasiparametric ALgorithm for target feature Extraction (QUALE), is then presented for SAR target feature extraction via data fusion through angle diversity based on the flexible data model. QUALE first estimates the model parameters, which include, for each scatterer, a 2D arbitrary real-valued amplitude sequence, a constant phase, and scatterer locations in range and cross-reange. QUALE then averages the estimated 2D real-valued amplitude sequence over range by making the assumption that the scatterer radar cross section is approximately consant. QUALE next models the so-obtained 1D sequence with a simple sinc function by assuming that the scatterer is approximately a dihedral (a trihedral is approximated as a very short dihedral) and estimates the relevant sinc function parameters by minimizing a nonlinear least-squares fitting function. Finally, the approximate 2D SAR image is reconstructed by using the estimated features. Numerical examples are given to demonstrate the perfomance of the proposed algorithm.This work was supported in part by AFRL/SNAT, Air Force Research Laboratory, Air Force Materiel Command, USAF, under grant no. F33615-99-1-1507, and the National Science Foundation Grant MIP-9457388. The U.S. Goverment is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon.     

基于目标检测的SAR图像匹配算法

该文提出一种基于目标检测的SAR图像匹配算法。针对SAR图像的特点,该算法先检测SAR图像的强散射目标,接着计算各强散射目标的质心,对主、辅图像的质心点集合进行Delaunay三角剖分,以三角剖分后的对应相似三角形的质心、内心、外心为匹配点进行匹配,最后用ERS-I,ERS-II卫星的SAR图像进行实验,通过与相干系数法进行比较,实验结果证实了方法的有效性。     

Shift–Scale Complex Correlation for Wide-Angle Coherent Cross-Track SAR Stereo Processing

Automated synthetic aperture radar (SAR) stereo correspondence becomes increasingly difficult when imaging high-relief terrain utilizing large stereo crossing-angle geometries because high-relief SAR image features can undergo significant spatial distortions, causing a failure of traditional correlation matching. This paper presents eight coherent spotlight-mode cross-track stereo pairs with stereo crossing angles averaging 93.7deg collected over a terrain with slopes greater than 20deg. These stereo pairs suffer from terrain-induced distortions, resulting in a decrease in complex correlation (coherence) when utilizing scanning-window correlation calculations. The search to maximize complex correlation is changed from a shift-only (disparity) search to a shift-and-scale search using the downhill simplex method. This approach is tested against complex imagery with simulated distortions and then employed on the eight wide-angle stereo collects. The resulting digital terrain maps (DTMs) are compared to ground truth. Using a shift-and-scale correlation approach to estimate disparity, the relative height errors decrease, and the number of reliable DTM posts increase     

A simple model for SAR azimuth speckle, focusing, and interferometric decorrelation

The phenomenon of speckle in synthetic aperture radar (SAR) images is well known as a characteristic grainy appearance of radar images. Speckle is frequently a significant obstacle to visual interpretations of radar data or target identification. In addition, it is usually the dominant noise source in SAR interferometry, since it is responsible for image decorrelation that degrades interferometric fringes, places severe constraints on orbits, and limits the accuracy of height measurements. This communication deals with the geometric sources of speckle. This conventional picture is extended to the case of vertically separated scatterers, and the formulation that results is applied to the structurally similar topics of azimuth focusing, interferometric decorrelation from defocusing, and atmospheric phase delays.     

The Recognition of Extended Targets: SAR Images for Level And Hilly Terrain

An experiment was performed using radar image simulation techniques to determine what a SAR image would look like for a collection of area extensive targets, first with flat underlying terrain and second, in the presence of moderate relief. Although compression, layover, and shadow are well known from the one-dimensional geometry analyses, it has not been previously demonstrated in a pictorial fashion what happens to the appearance of the same controlled reflectivity pattern, for level and hilly ground. It is not surprising to radargrammetrists that even modest elevation changes seriously affect the detection and recognition of boundaries and shapes. The image results clearly demonstrate these effects, and are valuable for many researchers who have previously used, or are just beginning to apply SAR imagery to crops and soils, minerals, and water resources assessment, etc. This research was performed during the course of an investigation to establish the performance of the Seasat-A SAR, in terms of user-oriented features, thus the radar system model and geometry are pertinent to that sensor, although the results can be applied to radar imaging in general. A review of range perspective imaging is included, since information extraction from radar imagery necessitates the knowledge of geometry/propagation effects.     

一种新的机载SAR图像几何校正和定位算法

机载合成孔径雷达常采用时域子孔径成像,所得到的图像是地面散射单元到成像平面的一种空变映射.通过联立求解等距离方程和等多普勒方程得到了这种映射的解析表达式,提出了一种新的图像无参考点几何校正和像素点定位的距离一多普勒算法,并用点阵仿真和外场试验验证了算法的有效性.     

Radar polarimetry: analysis tools and applications

The authors have developed several techniques to analyze polarimetric radar data from the NASA/JPL airborne SAR for Earth science applications. The techniques determine the heterogeneity of scatterers with subregions, optimize the return power from these areas, and identify probable scattering mechanisms for each pixel in a radar image. These techniques are applied to the discrimination and characterization of geologic surfaces and vegetation cover, and it is found that their utility varies depending on the terrain type. It is concluded that there are several classes of problems amenable to single-frequency polarimetric data analysis, including characterization of surface roughness and vegetation structure, and estimation of vegetation density. Polarimetric radar remote sensing can thus be a useful tool for monitoring a set of Earth science parameters