Sidelobe reduction via adaptive FIR filtering in SAR imagery.

The paper describes a class of adaptive weighting functions that greatly reduce sidelobes, interference, and noise in Fourier transform data. By restricting the class of adaptive weighting functions, the adaptively weighted Fourier transform data can be represented as the convolution of the unweighted Fourier transform with a data adaptive FIR filter where one selects the FIR filter coefficients to maximize signal-to-interference ratio. This adaptive sidelobe reduction (ASR) procedure is analogous to Capon's (1969) minimum variance method (MVM) of adaptive spectral estimation. Unlike MVM, which provides a statistical estimate of the real-valued power spectral density, thereby estimating noise level and improving resolution, ASR provides a single-realization complex-valued estimate of the Fourier transform that suppresses sidelobes and noise. Further, the computational complexity of ASR is dramatically lower than that of MVM, which is critical for large multidimensional problems such as synthetic aperture radar (SAR) image formation. ASR performance characteristics can be varied through the choice of filter order, l(1)- or l(2)-norm filter vector constraints and a separable or nonseparable multidimensional implementation. The author compares simulated point scattering SAR imagery produced by the ASR, MVM, and MUSIC algorithms and illustrates ASR performance on three sets of collected SAR imagery.     

Spatially variant apodization for image reconstruction from partialFourier data

Sidelobe artifacts are a common problem in image reconstruction from finite-extent Fourier data. Conventional shift-invariant windows reduce sidelobe artifacts only at the expense of worsened mainlobe resolution. Spatially variant apodization (SVA) was previously introduced as a means of reducing sidelobe artifacts, while preserving mainlobe resolution. Although the algorithm has been shown to be effective in synthetic aperture radar (SAR), it is heuristically motivated and it has received somewhat limited analysis. In this paper, we show that SVA is a version of minimum-variance spectral estimation (MVSE). We then present a complete development of the four types of two-dimensional SVA for image reconstruction from partial Fourier data. We provide simulation results for various real-valued and complex-valued targets and point out some of the limitations of SVA. Performance measures are presented to help further evaluate the effectiveness of SVA.     

Using APES for interferometric SAR imaging

We present an adaptive finite impulse response (FIR) filtering approach, which is referred to as the Amplitude and Phase EStimation (APES) algorithm, for interferometric synthetic aperture radar (SAR) imaging. We compare the APES algorithm with other FIR filtering approaches including the Capon and fast Fourier transform (FFT) methods. We show via both numerical and experimental examples that the adaptive FIR filtering approaches such as Capon and APES can yield more accurate spectral estimates with much lower sidelobes and narrower spectral peaks than the FFT method. We show that although the APES algorithm yields somewhat wider spectral peaks than the Capon method, the former gives more accurate overall spectral estimates and SAR images than the latter and the FFT method.     

Enhanced resolution in Sar/ISAR imaging using iterative sidelobe apodization.

Resolution enhancement techniques in radar imaging have attracted considerable interest in recent years. In this work, we develop an iterative sidelobe apodization technique and investigate its applications to synthetic aperture radar (SAR) and inverse SAR (ISAR) image processing. A modified noninteger Nyquist spatially variant apodization (SVA) formulation is proposed, which is applicable to direct iterative image sidelobe apodization without using computationally intensive upsampling interpolation. A refined iterative sidelobe apodization procedure is then developed for image-resolution enhancement. Examples using this technique demonstrate enhanced image resolution in various applications, including airborne SAR imaging, image processing for three-dimensional interferometric ISAR imaging, and foliage-penetration ultrawideband SAR image processing.     

基于IAPES的分布式SAR高分辨成像

分布式SAR成像通常采用FFT估计信号频率参数,但其估计精度差且旁瓣高,在多目标的情况下会产生严重的相互干扰,降低成像质量。对此提出一种分布式SAR干涉幅度相位估计融合成像方法。该方法通过构造全局自适应FIR滤波器对分布式SAR信号进行分维滤波,同时应用干涉技术估计相位差完成相位校正,进而估计出带宽展宽的融合信号频谱,提高成像分辨率。而且IAPES频率估计精度高并能抑制旁瓣,从而精确估计目标的散射强度,达到改善成像质量的目的。实验仿真验证了该方法的有效性。     

An adaptive filtering approach to spectral estimation and SARimaging

We present an adaptive FIR filtering approach, which is referred to as the amplitude and phase estimation of a sinusoid (APES), for complex spectral estimation. We compare the APES algorithm with other FIR filtering approaches including the Welch (1967) and Capon (1969) methods. We also describe how to apply the FIR filtering approaches to target range signature estimation and synthetic aperture radar (SAR) imaging. We show via both numerical and experimental examples that the adaptive FIR filtering approaches such as Capon and APES can yield more accurate spectral estimates with much lower sidelobes and narrower spectral peaks than the FFT method, which is also a special case of the FIR filtering approach. We show that although the APES algorithm yields somewhat wider spectral peaks than the Capon method, the former gives more accurate overall spectral estimates and SAR images than the latter and the FFT method     

Spatially variant apodization for squinted synthetic aperture radar images.

Spatially variant apodization (SVA) is a nonlinear sidelobe reduction technique that improves sidelobe level and preserves resolution at the same time. This method implements a bidimensional finite impulse response filter with adaptive taps depending on image information. Some papers that have been previously published analyze SVA at the Nyquist rate or at higher rates focused on strip synthetic aperture radar (SAR). This paper shows that traditional SVA techniques are useless when the sensor operates with a squint angle. The reasons for this behaviour are analyzed, and a new implementation that largely improves the results is presented. The algorithm is applied to simulated SAR images in order to demonstrate the good quality achieved along with efficient computation.     

基于空间变迹滤波旁瓣抑制与有序统计恒虚警率的舰船检测算法

由于合成孔径雷达(SAR)特殊的成像机制,导致了SAR图像上出现了旁瓣效应(SVA)。针对舰船目标检测过程中,旁瓣效应改变了强反射目标的形状导致的定位困难与定位错误问题,该文提出了一种基于空间变迹滤波与有序统计恒虚警率(OS-CFAR)的舰船检测算法。该算法将空间变迹滤波算法运用到复图像数据中,针对目标检测要求的实时性问题进行算法改进,通过全局CFAR只对潜在目标点进行旁瓣抑制而忽略对舰船检测无意义的大量背景点,在抑制旁瓣的同时减少了算法运算量。然后采用非线性的OS-CAFR算法对旁瓣抑制后的图像进行目标检测,并且采用形态学膨胀运算,弥补SVA算法可能造成的像素点幅值错误降低的问题。最后利用高分三号(GF-3)的实测数据进行验证,通过对比有无使用该文算法的结果的图像对比度与检查目标个数,体现了算法的有效性。      

改进的合成孔径雷达旁瓣抑制空间变迹算法

针对现有的改进空间变迹(SVA)算法存在运算量大、不能有效抑制合成孔径雷达(SAR)图像旁瓣或者损失主瓣能量等问题,提出一种新的改进SVA算法。分析了非整数倍带宽采样对理想频域窗函数所对应的脉冲响应函数的影响,根据旁瓣抑制要求,构建一个新的脉冲响应函数,同时得到其所对应的频域窗函数,并给出相应的约束条件,通过比较最大和最小加权的SAR数据来实现旁瓣抑制。该算法在保持主瓣能量的前提下能够快速有效地抑制旁瓣,仿真实验和实测数据处理验证了该算法的有效性。     

基于多视角快拍InSAR干涉技术的前视SAR三维成像

该文提出了一种基于多视角快拍InSAR干涉技术的前视SAR 3维成像方法。方位维依靠安置实际线性阵列以实现方位维高分辨,对应雷达发射的一次脉冲实现一次快拍2维高分辨成像;利用多次快拍不同视角获得的干涉相干相位,通过多基线InSAR联合像素处理方法,估计场景的高程信息。该文的3维成像方法对应回波数据录取时间短,数据量和运算量比较小;同时,多基线InSAR联合像素处理方法利用信号空间与噪声空间的正交性,能够有效提高信噪比,保证较高的测高精度。仿真结果验证了该文分析的正确性和算法的有效性。     

Tree height influence on ERS interferometric phase in boreal forest

The European Remote Sensing 1/2 (ERS-1/2) "tandem" coherence has been shown to provide estimates of stem volume in boreal forest in agreement with in situ data. Tree height estimation from ERS interferometric phase represents a further step in the investigations concerning the retrieval of biophysical parameters using repeat-pass synthetic aperture radar (SAR) interferometry. At two test sites located in Sweden and Finland, sets of respectively nine and eight ERS "tandem" interferograms were available. Images acquired under stable winter weather conditions and during nighttime were found to be less affected by atmospheric artifacts. Reduction of atmospheric artifacts in interferograms was performed with a phase screen estimated over a dense grid of open areas. Nonetheless, at each test site, only a limited set of pairs was useful for tree height investigations. Under stable winter conditions, the interferometric tree height obtained from an inversion of the differential interferometric phase at stand level was found to be much lower than the true tree height. Spread and uncertainty in the interferometric tree height measurements were caused by phase noise and residual atmospheric artifacts. Using the semiempirical interferometric water cloud model (IWCM), the modeled interferometric tree height was generally in reasonable agreement with the measurements, showing the need of a phase term in interferometric modeling of forests. The inversion of the IWCM for tree height retrieval showed the strong effect of phase noise and atmospheric artifacts on the estimates. Hence, tree height retrieval from ERS repeat-pass SAR interferometry seems to have limited forestry applications. The results also indicate under what conditions the forest influence is small on digital elevation models derived from repeat-pass interferometry.     

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.     

Ocean wave imaging using an airborne single pass across-trackinterferometric SAR

An airborne single pass across-track interferometric synthetic aperture radar (InSAR) is used to image ocean waves. A theoretical model explaining the imaging mechanisms is developed, and simulations of the interferogram as well as the conventional SAR intensity image are presented for given ocean wave spectra. Distortions of digital elevation models (DEM) derived from InSAR data are explained by the motion of the sea surface. A Monte Carlo method based on forward simulations is used to estimate variance spectra of the distorted elevation models. It is shown that a straightforward estimation of wave height using the distorted InSAR elevation model is in good agreement with true wave height for low amplitude swell with about 10% error depending on propagation direction and coherence time. However, severe underestimation of wave height is found for wind seas propagating in flight direction. Forward simulations show that the distorted InSAR DEM is less dependent an the model chosen for the real aperture radar mechanism than conventional SAR images. Data acquired during an experiment over the North Sea by a high precision InSAR system are compared with simulations     

Ocean wave extraction from RADARSAT synthetic aperture radarinter-look image cross-spectra

This study is concerned with the extraction of directional ocean wave spectra from synthetic aperture radar (SAR) image spectra. The statistical estimation problem underlying the wave-SAR inverse problem is examined in detail in order to properly quantify the wave information content of SAR. As a concrete focus, a data set is considered comprising six RADARSAT SAR images co-located with a directional wave buoy off the east coast of Canada. These SAR data are transformed into inter-look image cross-spectra based on two looks at the same ocean scene separated by 0.4 s. The general problem of wave extraction from SAR is cast in terms of a statistical estimation problem that includes the observed SAR spectra, the wave-SAR transform, and prior spectral wave information. The central role of the weighting functions (inverse of the error covariances) is demonstrated, as well as the consequence of approximate (based on the quasilinear wave-SAR transform) versus exact linearizations on the convergence properties of the algorithm. Error estimates are derived and discussed. This statistical framework is applied to the extraction of spectral wave information from observed RADARSAT SAR image cross-spectra. A modified wave-SAR transform is used to account for case-specific geophysical and imaging effects. Analysis of the residual error of simulated and observed SAR spectra motivates a canonical form for the SAR observation error covariance. Wave estimates are then extracted from the SAR spectra, including wavenumber dependent error estimates and explicit identification of spectral null spaces where the SAR contains no wave information. Band-limited SAR wave information is also combined with prior (buoy) spectral wave estimates through parameterization of the wave spectral shape and use of regularization     

联合多方位角调频率估计的星载SAR三维成像方法

星载合成孔径雷达(Synthetic Aperture Radar, SAR)通过波束的方位向扫描可以实现单次航过的多方位观测。在多方位角观测过程中,卫星弯曲轨道可等效为长3维曲线阵列,从而具备了3维成像能力。由于多方位角观测在高度维采样的稀疏性,无法直接通过3维FFT实现无模糊成像,且目标在不同方位角SAR图像的投影与高程间的传递相对复杂。针对该问题,该文提出了联合多方位角调频率估计的星载SAR3维成像方法。该方法首先给出了不同观测方位角下多普勒调频率误差与目标高程误差间的关系,利用视错位法(Map Drift, MD)估计多普勒调频率误差。然后,联合多方位角高程估计结果提升高程估计精度。最后,利用高程估计结果恢复目标3维几何信息,从而实现3维成像。仿真实验验证了该方法的高程估计精度可达米级。      

An evident sidelobe control method based on NSCT for ship target in SAR images

Evident sidelobe on faint ship target seriously affects the accuracy of the target segmentation in Synthetic Aperture Radar (SAR) images. To avoid this problem, a novel sidelobe control method based on NonSubsampled Contourlet Transform (NSCT) for ship targets in SAR images is presented in this paper. This method enhances the SAR images in NSCT domain based on target azimuth estimation and then inhibits the sidelobe directionally in NSCT high-pass frequency subbands. Experimental results on RADARSAT-2 images demonstrate that the proposed method can not only reduce the strong sidelobes effectively, but also enhance the intensity of the objects successfully. Therefore, it gives a good segmentation result on the dark ship images with strong sidelobe, and enhances the detection rate on these targets.     

Intensity and phase statistics of multilook polarimetric andinterferometric SAR imagery

Polarimetric and interferometric SAR data are frequently multilook processed for speckle reduction and data compression. The statistical characteristics of multilook data are quite different from those of single-look data. The authors investigate the statistics of their intensity and phase. Probability density function (PDF's) of the multilook phase difference, magnitude of complex product, and intensity and amplitude ratios between two components of the scattering matrix are derived, and expressed in closed forms. The PDF's depend on the complex correlation coefficient and the number of looks. Comparisons of these theoretically derived PDF's are made to measurements from NASA/JPL AIRSAR data. The results of this paper can be applied to feature classification using polarimetric SAR and to the estimation of decorrelation effects of the interferometric SAR     

合成孔径雷达干涉测量中的最优基线模型

基线是干涉合成孔径雷达(InSAR)工作原理中的关键参数，它使得图像对之间有了相干性，同时也是导致图像对相干性损失的一个根源。在数字高程模型(DEM)允许误差的条件下，一定存在最优基线使得DEM精度最佳。最优基线使得InSAR工作在最佳状态，准确地估计它可以大大提高地形高度的测量精度。文中首先根据InSAR测高成像几何关系和回波的信号谱分析了基线的存在引起的两方面影响，从而论证了最优基线的存在性。在此基础之上，从目标高度估计方差着手，对于平坦地区或坡度一定的地形，建立了合成孔径雷达干涉测量中的最优基线模型，并利用ERS-1／2干涉数据实验论证了该模型，最后讨论了一些系统参数和几何参数对最优基线的影响。