Multichannel whitening of SAR imagery

The presence of speckle in synthetic aperture radar (SAR) imagery makes image interpretation more difficult and worsens the performance of algorithms designed to detect objects in the imagery. Image processing techniques to reduce speckle usually do so at the expense of spatial resolution. Multichannel whitening is one image processing technique that reduces image speckle while maintaining spatial resolution. Multichannel whitening is applied to imagery recorded during a foliage penetration experiment undertaken by MIT Lincoln Laboratory using the NASA/JPL UHF, L-, C-band fully polarimetric SAR in July 1990. In this experiment, a 50 km² forested area near Portage, Maine was imaged. Twenty-seven 8 ft trihedral corner reflectors were arrayed throughout the imaged area beneath the foliage in order to measure foliage attenuation. The detection performance for corner reflectors under foliage is compared for the raw data and whitened data, and the predictions of a product model for the degree of speckle reduction are compared with the data     

Optimal speckle reduction in polarimetric SAR imagery

Speckle is a major cause of degradation in synthetic aperture radar (SAR) imagery. With the availability of fully polarimetric SAR data, it is possible to use the three complex elements (HH, HV, VV) of the polarimetric scattering matrix to reduce speckle. The optimal method for combining the elements of the scattering matrix to minimize image speckle is derived, and the solution is shown to be a polarimetric whitening filter (PWF). A simulation of spatially correlated, K-distributed, fully polarimetric clutter is then used to compare the PWF with other, suboptimal speckle-reduction methods. Target detection performance of the PWF, span, and single-channel |HH|² detectors is compared with that of the optimal polarimetric detector (OPD). A novel, constant-false-alarm-rate (CFAR) detector (the adaptive PWF) is as a simple alternative to the OPD for detecting targets in clutter. This algorithm estimates the polarization covariance of the clutter, uses the covariance to construct the minimum-speckle image, and then tests for the presence of a target. An exact theoretical analysis of the adaptive PWF is presented; the algorithm is shown to have detection performance comparable with that of the OPD     

Nonlinear apodization for sidelobe control in SAR imagery

Synthetic aperture radar (SAR) imagery often requires sidelobe control, or apodization, via weighting of the frequency domain aperture. This is of particular importance when imaging scenes containing objects such as ships or buildings having very large radar cross sections. Sidelobe improvement using spectral weighting is invariably at the expense of mainlobe resolution presented here is a class of nonlinear operators which significantly reduce sidelobe levels without degrading mainlobe resolution implementation is via sequential nonlinear operations applied to complex-valued (undetected) SAR imagery. SAR imaging is used to motivate the concepts developed in this work. However, these nonlinear apodization techniques have potentially broad and far-ranging applications in antenna design, sonar, digital filtering etc., i.e., whenever data can be represented as the Fourier transform of a finite-aperture signal     

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.     

Doppler aliasing reduction in SAR imagery using stepped-frequency waveforms

A new technique for eliminating Doppler aliasing artifacts in synthetic aperture radar (SAR) imagery is presented. The technique uses continuous transmission of stepped-frequency (SF) waveforms to generate a simple, but effective, approximation of a two-dimensional |sinc|² ambiguity function. This approach ensures aliasing artifacts are placed at nulls in a Doppler filter, effectively removing them from the imagery. Various methods of generating SF waveforms are introduced and their performance is quantified. Finally, simulated SAR imagery shows elimination of more than 99% of the aliased energy     

Foliage attenuation and backscatter analysis of SAR imagery

The ability of a synthetic aperture radar (SAR) to detect targets under foliage is in part determined by the attenuation suffered by radiation propagating through the foliage and the backscatter from the foliage. MIT Lincoln Laboratory made measurements of foliage attenuation and backscatter using the NASA/JPL-UHF, L-, C-band fully-polarimetric SAR in July 1990. In this experiment, a 48 km² forested area near Portage, Maine was imaged. Twenty-seven 8 ft trihedral corner reflectors were arrayed throughout the imaged area in order to measure foliage attenuation. Ground truth was recorded at the time of the experiment in order to correlate the attenuation and backscatter results with foliage biophysical properties. The probability densities for foliage attenuation and for backscatter are determined as functions of frequency, polarization, and depression angle     

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     

A chirp scaling approach for processing squint mode SAR data

Image formation from squint mode synthetic aperture radar (SAR) is limited by image degradations caused by neglecting the range-variant filtering required by secondary range compression (SRC). Introduced here is a nonlinear FM chirp scaling, an extension of the chirp scaling algorithm, as an efficient and accurate approach to range variant SRC. Two methods of implementing the approach are described. The nonlinear FM filtering method is more accurate but adds a filtering step to the chirp scaling algorithm, although the extra computation is less than that of a time domain residual compression filter. The nonlinear FM pulse method consists of changing the phase modulation of the transmitted pulse, thus avoiding an increase in computation. Simulations show both methods significantly improve resolution width and sidelobe level, compared with existing SAR processors for squint angles above 10 deg for L-band and 20 deg for C-band     

Bayesian edge detector for SAR imagery using discontinuity-adaptive Markov random feld modeling

Synthetic aperture radar（SAR）image is severely affected by multiplicative speckle noise,which greatly complicates the edge detection.In this paper,by incorporating the discontinuityadaptive Markov random feld（DAMRF）and maximum a posteriori（MAP）estimation criterion into edge detection,a Bayesian edge detector for SAR imagery is accordingly developed.In the proposed detector,the DAMRF is used as the a priori distribution of the local mean reflectivity,and a maximum a posteriori estimation of it is thus obtained by maximizing the posteriori energy using gradient-descent method.Four normalized ratios constructed in different directions are computed,based on which two edge strength maps（ESMs）are formed.The fnal edge detection result is achieved by fusing the results of two thresholded ESMs.The experimental results with synthetic and real SAR images show that the proposed detector could effciently detect edges in SAR images,and achieve better performance than two popular detectors in terms of Pratt＇s fgure of merit and visual evaluation in most cases.     

A wavelet multiresolution analysis for spatio-temporal signals

The wavelet filters of the conventional 3D multiresolution analysis possess homogeneous spatial and temporal frequency characteristics which limits one's ability to match filter frequency characteristics to signal frequency behavior. Also, the conventional 3D multiresolution analysis employs an oct-tree decomposition structure which restricts the analysis of signal details to identical resolutions in space and time. This paper presents a 3D wavelet multiresolution analysis constructed from nonhomogeneous spatial and temporal filters, and an orthogonal sub-band coding scheme that decouples the spatial and temporal decomposition processes     

一种用于条带模式SAR成像的自聚焦算法

 针对现有条带模式合成孔径雷达（SAR）成像的自聚焦算法中,相位的拼接会引起误差的严重积累,本文结合相位梯度自聚焦（PGA）算法和子孔径偏移（MD）算法,提出了一种新的用于条带模式SAR成像的自聚焦算法（PGA-MD）。该算法先利用PGA算法有效估计各子孔径相位误差函数,再利用相邻子图间方位向偏移量和线性相位之间的关系,通过MD算法精确估计相邻子图间方位向偏移量,然后计算线性相位差,并基于—阶导数实现子孔径相位误差函数拼接。理论分析以及实测数据处理结果对比均表明PGA-MD算法可以有效提高对条带SAR图像的自聚焦效果。     

A Generalized Approach to Multiresolution Complex SAR Signal Processing

Multiresolution synthetic aperture radar (SAR) image formation has been proven to be beneficial in a variety of applications such as improved imaging and target detection as well as speckle reduction. SAR signal processing traditionally carried out in the Fourier domain has inherent limitations in the context of image formation at hierarchical scales. We present a generalized approach to the formation of multiresolution SAR images using biorthogonal shift-invariant discrete wavelet transform (SIDWT) in both range and azimuth directions. Particularly in azimuth, the inherent subband decomposition property of wavelet packet transform is introduced to produce multiscale complex matched filtering without involving any approximations. This generalized approach also includes the formulation of multilook processing within the discrete wavelet transform (DWT) paradigm. The efficiency of the algorithm in parallel form of execution to generate hierarchical scale SAR images is shown. Analytical results and sample imagery of diffuse backscatter are presented to validate the method.     

一种横向机动弹道下SAR成像算法

针对横向机动弹道下SAR成像回波方位向和距离向严重耦合、弹载SAR平台实时性要求高的特点,提出了一种基于频谱分析的扩展SAR成像算法。首先,以初始距离相同的目标作为成像处理对象,建立了横向机动下弹载SAR成像模型,分析了回波相位和瞬时距离的泰勒展开;然后,采用包含水平面速度和偏航加速度参数的相位因子依次进行距离徙动校正、二次相位补偿和多普勒中心频率补偿,实现了SAR图像的精确聚焦。该算法处理流程简单、实时性高,适合横向机动弹道下的中等分辨率的大斜视成像,给出了算法流程,仿真验证了算法有效性。     

游走在心象之间

晴秋人精致,在现如今物质与浮躁的上海不多见。她像三十年代上海知性女人气质得体、典雅。晴秋又是游走于自我色彩中的精灵,一个忠于自己灵魂的画家。她的作品没有沾染浮华之气,在喧嚣市侩的夹缝中还保持着独立的自我品格,她的作品始终流露着她对绘画的那份原始的热情。置身于当今多元陈杂的图像时代,人们总期望着通过画家的作品,去梳理并揣摩他的创作心态,感觉和感受他精神层面的意绪,从而复原出画家的理想、追求、观念和价值。"画如其人",意为作品和作者在气质上的一致,透     

基于图像域分块的条带SAR 自聚焦算法

文章针对条带合成孔径雷达,提出一种基于图像域分块的自聚焦算法。该算法在图像域进行方位向分子 块,采用图像偏移(MD)算法减小相位误差梯度的拼接误差,实现条带SAR图像的自聚焦处理。给出了算法流程, 讨论了算法的主要步骤及原理,并利用实测数据对算法进行了验证。实测数据处理结果表明该算法能有效改善条 带SAR图像质量。     

一种复合的SAR压制干扰方法研究

覆盖式干扰是一种对合成孔径雷达有效的干扰样式,有效覆盖面积是评价覆盖干扰效果的重要指标之一,如何有效地对干扰范围进行扩展是研究的热点问题,具有较高的研究价值。在介绍3种不同干扰方法的原理与干扰效果之后,对方法进行了结合,提出了1种可以有效扩展干扰区域范围的干扰模型。方法以二维锯齿调频干扰为基础,利用频移干扰扩展距离向干扰区域,利用方位向间歇采样技术扩展方位向干扰区域。不仅原理简单,更加利于工程实现。最后,利用单一点目标对方法进行了验证,仿真实验的结果证实了方法的准确性与可靠性。     

一种高光谱图像的双压缩感知模型

高光谱图像因其海量数据性,给存储、传输及后续分析处理带来了挑战。压缩感知理论提供了一种全新的信号采集框架。针对高光谱数据的三维特性,提出一种双压缩感知的采样与重构模型。该模型在采样阶段兼顾高光谱数据的空间和谱间稀疏特性,构造了能同时实现空间和谱间压缩采样的感知矩阵;重构阶段不同于传统的压缩感知重构方法直接重构高光谱数据,而是将高光谱数据分离成端元和丰度分别进行重构,然后利用重构的端元和丰度信息合成高光谱数据。实验结果表明,所提双压缩感知在低采样率下重构精度较三维压缩采样提高了10 dB以上,更为显著的是运算速度提升了3个数量级,同时该方法还便于获得端元和丰度信息。     

SAR极坐标格式成像算法对运动目标响应特性

运动目标的合成孔径雷达（SAR）成像特征是SAR地面运动目标指示（SAR/GMTI）系统进行运动目标检测、成像和重定位的基础。为此,从信号二维解耦合校正距离徙动角度推导和分析了极坐标格式算法（PFA）对运动目标的响应特性,揭示了极坐标格式转换过程中的距离插值和方位插值对运动目标距离徙动的校正原理。理论分析表明：PFA在完成对静止目标成像的同时,还能够自动校正所有运动目标的线性距离徒动,且校正过程无需目标运动信息,因此对于径向运动目标,在忽略波前弯曲条件下PFA也能够对其进行完全聚焦。最后,通过仿真数据处理对理论分析结果进行了验证,表明PFA作为一种运动目标成像预处理方法具有很大的应用前景。     

A sequential detection approach to target tracking

Sequential hypothesis testing is investigated for multiframe detection and tracking of low-observable maneuvering point-source targets in a digital image sequence. The proposed multiple multistage hypothesis test tracking (MMHTT) algorithm extends tracks formed from sequentially detected target trajectory segments using a multiple hypothesis tracking strategy. The MMHTT algorithm does not require a probabilistic larger maneuver model. Computational efficiency is achieved by using a truncated sequential probability ratio test (SPRT) to prune a dense tree of candidate target trajectories and score the detected trajectory segments. An analytical performance evaluation is presented and confirmed by experimental results from an optical satellite tracking application