大气折射率波动引起的SAR成像误差分析

合成孔径雷达(SAR)成像中通常默认大气折射率为1,即电磁(EM)波速率等于自由空间光速且忽略大气吸收特性,但实际存在的吸收会减弱入射功率,电磁波速率的变化会引起相位误差,从而影响图像重建.该文定量分析电磁波速率波动和大气吸收对雷达图像的影响,理论推导得出大气吸收会导致振幅误差,表现为散射点在图像中的重建幅度误差;电磁波速率波动会导致相位误差,表现为散射点在图像中的重建位置误差.仿真实验验证了误差分析的正确性.该分析进一步完备了SAR成像误差分析,有助于SAR图像正确解译.     

合成孔径雷达参数化成像技术进展

传统合成孔径雷达(SAR)成像可视为点目标散射模型约束下数据空间到图像空间的映射。然而,真实目标多为延展目标,与传统线性成像处理中的点目标散射模型存在失配,会导致SAR图像表征失真。常见的现象是使延展目标多呈现为孤立强点,阻碍了基于SAR图像的目标辨识等应用。SAR参数化成像技术是为解决上述模型失配问题而诞生的一种非线性成像方法,特点是兼顾点目标和延展目标的散射模型。具体来说,是通过利用不同类别目标的回波或图像的相位与幅度特征对观测角度的敏感性,辨识目标类型,反演目标散射参数,进而根据目标散射的参数化模型,重建目标图像的技术。在对延展目标成像时,可获得比传统线性成像方法更好的图像质量。该文主要介绍了线型延展目标的参数化成像技术,对应真实场景中的孤立强点和连续边缘,深入讨论了基于回波域、图像域的参数化成像技术和试验结果,展望了未来SAR参数化成像技术的发展趋势。      

一种改进的星载SAR图像控制点几何校正模型

星载合成孔径雷达(SAR)用电磁波获取地球表面的电子图像。由于是侧视成像,SAR图像固有地含有定位误差,这些误差来源于SAR成像几何、成像模式、散射特性以及图像形成过程。因此,在SAR图像使用中必须考虑这些误差并予以校正。利用先验控制点信息可提高星载SAR图像定位精确度,校正几何畸变。分析了星载SAR图像定位的系统误差传递规律,通过将误差传递特性相似的系统误差源进行等效合并,提出了一种改进的系统误差校正模型,蒙特卡洛(Monte-Carlo)仿真实验验证了新模型具有更高的系统误差校正精确度。     

一种新的SAR超分辨成像方法

提出了一种新的合成孔径雷达(SAR)超分辨成像方法。首先在图像域获得散射中心特征参数的初始估计，然后在相位历史域利用非线性回归模型的参数估计方法获得散射中心特征参数的高精度估计，最后依据相位历史域SAR点散射模型，生成更大尺度的相位历史数据，对得到的相位历史数据成像即得到了更高分辨率的SAR图像。仿真计算结果表明，该方法能够快速稳定实现，同时具有良好的超分辨性能。     

时变大气层效应对地球同步轨道SAR成像影响的分析与补偿

大气层效应会导致穿过其中的星载SAR信号产生相位误差,并进而可能造成星载SAR成像结果出现散焦现象。大气层效应包括背景电离层效应、电离层多重散射效应以及对流层效应,由于GEO SAR合成孔径时间可达几百秒量级,因此在其成像积累时间内大气层效应会随时间变化,因此必须考虑时变大气层效应对GEO SAR成像的影响,同时亟需研究时变大气层效应对GEO SAR成像影响的补偿方法。本文详细分析了时变大气层效应对SAR信号的影响机理,建立了时变大气层效应影响下的高精度GEO SAR回波信号模型,分析了时变大气层效应对GEO SAR成像的影响,并基于方位向子孔径划分,通过提取时变大气层相位误差,对大气层效应造成的GEO SAR图像散焦现象进行了补偿。      

射频干扰对机载P波段重复轨道InSAR系统的影响分析

工作在低频段的SAR容易受到射频干扰(Radio Frequency Interference,RFI)的影响,而导致SAR图像质量的恶化。对于重复轨道InSAR来说,RFI的存在还会影响其干涉相位。针对此问题,该文将实测RFI信号加入仿真的典型圆锥场景回波,进行成像和干涉处理,给出了干扰前后的成像和干涉处理结果,分析了实测RFI对SAR图像幅度、相位和重复轨道干涉处理的影响。最后使用频域陷波方法对机载P波段重复轨道InSAR实际数据中的RFI信号进行干扰抑制,给出了干扰抑制前后的重复轨道干涉处理结果,验证了仿真分析的正确性,表明了该文干扰抑制方法对减小由RFI引入干涉相位误差的有效性。     

典型线面目标合成孔径雷达参数化成像

在复杂场景(特别是城区场景)合成孔径雷达(SAR)遥感成像中,存在大量线、面目标,如城区中的道路和建筑物边缘等目标,这些线面目标微波散射信号方向性强。传统SAR从单一视角获取场景的散射信息,且传统成像算法均基于点目标模型,使得传统SAR图像中线面目标主要特征表现为一系列的强散射点,而非线散射特征和面散射特征,最终造成SAR图像中目标不连续,SAR图像解译困难。因此,该文通过建立典型线段、三角面元目标的参数化回波模型,对线面目标SAR成像机理进行了深入细致的研究;并基于提出的参数化模型对线面目标进行参数化成像,即首先基于贝叶斯理论和所提的参数化模型对典型的线面目标进行分类判决,随后采用再成像的方式获得有效表征线、面目标散射特征的SAR图像,为线、面目标SAR图像解译提供有效支撑。最后,数值仿真实验成功验证了所提算法的有效性和正确性。      

面向目标特性精细提取的SAR数据融合成像处理方法

针对当前高分辨率星载SAR数据处理忽略目标相关散射特性随方位角变化而导致目标轮廓细节难以精细提取的问题,该文提出了一种面向目标特性精细提取的融合成像处理方法。首先,分析高分辨率条件下影响目标特性提取和SAR图像质量的因素,如轨道非线性、停-走模型、大气延时、高阶残留相位误差等,并提出针对性的补偿方法。在此基础上,建立基于目标时空谱特性的回波数学信号模型,解析目标散射特性时-空-频的变化规律,提出针对高分辨率、超大方位观测角范围的融合成像处理策略和方法,在距离-多普勒域、图像域通过融合处理提升SAR图像的品质。最后,通过对典型军事目标的仿真和成像处理,验证所提方法的有效性。      

FMCW SAR相位梯度自聚焦算法研究

调频连续波合成孔径雷达(FMCW SAR)是一种新近提出来的成像雷达体制,它结合调频连续波与合成孔径成像技术,具有体积小、重量轻、成本低、分辨率高等一系列优点.在SAR成像中,相位误差是成像质量下降的主要原因.针对FMCW SAR的特点,分析了二阶相位误差对成像质量的影响,然后以二阶相位误差为例建立了存在相位误差的FMCW SAR信号模型,研究了适合于FMCW SAR的相位梯度自聚焦算法,仿真结果表明该算法能够校正相位误差的影响,提高了成像精度.     

对流层对地球同步轨道SAR成像的影响研究

地球同步轨道SAR（GEO SAR）具有超长孔径时间和大覆盖范围的特性,使得传统低轨SAR成像中采用的对流层冻结模型假设失效。因此,需要考虑时变条件下的对流层效应对GEO SAR成像的影响。本文根据对流层中电磁波的传播规律,利用射线描迹法,分析了GEO SAR中相位误差的特点;并通过建立时变对流层影响下的GEO SAR回波信号模型,研究了对流层引起的GEO SAR图像偏移及图像散焦现象,并分析总结了相关影响的边界条件。最后,基于仿真数据,分析了对流层效应对GEOSAR成像的影响。      

Sparse representation-based algorithm for joint SAR image formation and autofocus

Inaccuracies in the observation model of the synthetic aperture radar (SAR) due to inaccuracies of the velocity and position of the platform or atmospheric turbulence cause degradations in reconstructed images which necessitate the use of autofocus algorithms. In this paper we propose a novel signal processing algorithm for joint SAR image formation and autofocus in a synthesis dictionary based sparse representation framework. Proposed algorithm can be applied broadly to scenes that exhibit sparsity with respect to any dictionary. This is done by extending our previously developed sparse representation-based SAR imaging framework to joint SAR image formation and autofocus. To this end, the phase error vector is separated from the unknown phase of the complex-valued back-scattered field. Phase error vector is estimated using a MAP estimator and compensated through an iterative algorithm to produce focused images. We demonstrate the effectiveness of the proposed approach on synthetic and real imagery.     

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 sparsity-driven approach for joint SAR imaging and phase error correction

Image formation algorithms in a variety of applications have explicit or implicit dependence on a mathematical model of the observation process. Inaccuracies in the observation model may cause various degradations and artifacts in the reconstructed images. The application of interest in this paper is synthetic aperture radar (SAR) imaging, which particularly suffers from motion-induced model errors. These types of errors result in phase errors in SAR data, which cause defocusing of the reconstructed images. Particularly focusing on imaging of fields that admit a sparse representation, we propose a sparsity-driven method for joint SAR imaging and phase error correction. Phase error correction is performed during the image formation process. The problem is set up as an optimization problem in a nonquadratic regularization-based framework. The method involves an iterative algorithm, where each iteration of which consists of consecutive steps of image formation and model error correction. Experimental results show the effectiveness of the approach for various types of phase errors, as well as the improvements that it provides over existing techniques for model error compensation in SAR.     

Blind-velocity SAR/ISAR imaging of a moving target in a stationarybackground

A synthetic aperture radio/inverse synthetic aperture radar (SAR/ISAR) coherent system model and inversion to image a target moving with an unknown constant velocity in a stationary background are presented. The approach is based on a recently developed system modelling and inversion principle for SAR/ISAR imaging that utilizes the spatial Fourier decomposition of SAR data in the synthetic aperture domain to convert the SAR system model's nonlinear phase functions into linear phase functions suitable for a computationally manageable inversion. It is shown that SAR/ISAR imaging of a moving target can be converted into imaging the target in a stationary squint-mode SAR problem where the parameters of the squint-mode geometry depend on the target's velocity. A method for estimating the moving target's velocity that utilizes a spatial Doppler analysis of the SAR data within overlapping subapertures is presented. The spatial Doppler technique does not require the radar signal to be narrowband, so the reconstructed image's resolution is not sacrificed to improve the target's velocity estimator.     

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。      

ERS-1 SAR images of atmospheric gravity waves

ERS-1 synthetic aperture radar (SAR) images of atmospheric gravity waves over the ocean are discussed. Several case studies are presented in detail. It is shown that the well-organized long wavelength (1 to 10 km) wave phenomena which often are seen in SAR images over the ocean may be atmospheric gravity waves. The waves appear in the SAR images because they modulate the surface wind speed which in turn modulates the surface roughness and the radar cross section. The wavelength may be measured directly from the SAR image, and the mean wind speed and wind speed modulation near the ocean surface may be estimated from the observed radar cross section modulation using a wind retrieval model. The atmospheric gravity waves usually were generated by the approach or passing of a meteorological front. Atmospheric soundings and a two-layer model for the lower troposphere indicate that, in general, the observed atmospheric wave phenomena could have been supported by accompanying temperature inversion layers and wind shears     

Simulation of ocean waves imaging by an along-track interferometricsynthetic aperture radar

A two-dimensional (2D) model for describing the imaging of ocean waves by an along-track interferometric synthetic aperture radar (AT-INSAR) is derived. It includes the modulation of the normalized radar cross section by the long waves, velocity bunching, and azimuthal image smear due to orbital acceleration associated with long waves and due to the orbital velocity spread within the AT-INSAR resolution cell (parameterized by the scene coherence time). By applying the Monte-Carlo method, AT-INSAR amplitude and phase image spectra are calculated for different sea states and radar configurations. The Monte-Carlo simulations show that velocity bunching affects the AT-INSAR imaging mechanism of ocean waves, and that a unimodal ocean wave spectrum may be mapped into a bimodal AT-INSAR phase image spectrum due to an interference between the velocity term and the velocity bunching term in the AT-INSAR imaging model. It is shown that the AT-INSAR imaging mechanism of ocean waves depends on the ratio of the scene coherence time and the time separation between the observations by the two antennas. If this ratio is larger than one, the AT-INSAR phase image spectra are distorted. Furthermore, the simulations show that the AT-INSAR phase image spectrum is quite insensitive to the ocean wave-radar modulation transfer function. Comparing AT-INSAR with conventional SAR imaging of ocean waves, the authors find that the azimuthal cut-off in AT-INSAR phase image spectra is shifted toward higher wavenumbers than in conventional SAR image spectra. This implies that AT-INSAR can resolve shorter azimuthal wavenumbers than conventional SAR. Thus the authors conclude that AT-INSAR phase images are better suited for measuring ocean waves spectra than conventional SAR images     

激光反射层析成像相位恢复算法研究

针对激光反射层析成像中目标随机抖动与径向运动造成的投影中心失配问题,提出采用相位恢复算法对重构图像进行相位恢复重建,通过反复光强迭代消除目标随机运动造成的相位误差,达到减少重构误差、恢复目标图像的目的。为改进G-S算法收敛速度与恢复精度,提出频域模值加权方法进行投影数据相位迭代恢复,仿真实验表明,将算法收敛速度与收敛精度提高了1.2倍以上。通过对三组仿真实验处理,重构图像的平均相对均方误差由2.487 5下降到0.792 7,有效地恢复了目标图像轮廓。外场实验表明,该算法能够有效消除重构图像伪迹,改善激光反射层析成像系统成像质量。     

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.     

大气折射效应对LEO-SAR成像质量的影响

大气折射会对无线电波造成射线弯曲和时延色散。对工作在微波频段的LEO-SAR而言,弯曲效应会导致雷达图像在距离上的偏移,而色散效应导致的二次相位误差会对接收信号造成脉冲展宽,使雷达图像分辨率降低,产生畸变。通过对这两种传播效应进行建模分析,选择电离层、对流层环境折射效应均较强的三亚地区进行折射指数剖面建模,仿真计算了该大气环境下,不同频段和轨道高度上LEO-SAR目标成像的距离向漂移和分辨率的变化,分析了大气折射引起的射线弯曲和时延色散特性对LEO-SAR成像质量的影响,为不同类型的LEO-SAR提供准确合理的折射误差修正补偿。