复杂航迹和起伏地形条件下机载聚束SAR 空变运动补偿

 运动补偿是雷达平台机动飞行条件下合成孔径雷达(SAR)实现精确聚焦成像的前提,而如何精确实现运动误差的空变补偿(误差补偿随目标距离、方位和高度位置的变化而变化)目前还存在很大的挑战。本文提出了一种新的三阶运动补偿方法,能够有效解决复杂雷达航迹和地形起伏条件下运动误差的空变补偿问题。该方法首先以场景中心为参考进行空不变运动补偿,然后以多个子场景中心为参考进行空变运动补偿,最后再利用极坐标格式算法(PFA)统一补偿每个像素的空变误差。仿真数据处理结果验证了本文方法的有效性。     

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。     

基于先验误差模型的机载高分宽幅DBF-SAR自聚焦算法

高分宽幅（HRWS）数字波束形成（DBF）合成孔径雷达（SAR）利用多通道空间采样代替部分时域采样,可以有效缓解SAR成像时高分辨率与宽测绘带间的矛盾,具有重要的军用和民用价值。现有常规DBF-SAR成像算法都假设雷达传感器相对位置精确已知,实际应用中受传感器位置测量误差影响,由位置不精确导致的相位误差会严重影响DBF-SAR高精度成像能力。在极坐标格式算法（PFA）框架下,推导了DBF-SAR成像处理后,残留相位误差的解析模型,分析了该误差对成像质量的影响。依据推导的先验相位误差解析结构模型,提出了一种基于图像对比度最优化准则的自聚焦算法。新算法通过引入先验相位结构信息,极大降低了待估参数的空间维数,可以同时改善自聚焦算法的参数估计精度和计算效率。数据处理结果验证了理论分析的正确性和所提算法的有效性。     

一种超高分辨率机载聚束SAR两维自聚焦算法

受运动参数测量误差和大气扰动等因素影响,合成孔径雷达(SAR)图像通常会发生散焦,利用自聚焦对散焦的SAR图像进行后处理是一种有效的重聚焦手段。传统的自聚焦算法都只是针对方位一维相位误差的估计和补偿。随着成像分辨率的提高,自聚焦时残留距离徙动的校正成为SAR成像面临的一个新挑战。本文推导得到了极坐标格式算法处理后残留距离徙动和方位相位误差的解析表达式,分析了两者之间的内在关系,并利用该关系,提出了一种能够同时进行残留距离徙动和方位相位误差补偿的两维自聚焦算法。实测数据处理结果表明,在残留距离徙动效应不可忽略的条件下,该方法能够极大地改善原有自聚焦算法的聚焦性能。     

基于最小熵的多通道SAR系统相位误差估计与补偿

采用多通道合成的方法来增加信号带宽,是提高合成孔径雷达(SAR)系统距离分辨率的一种有效技术手段。针对多通道间相位失配的问题,建立了通道相位误差的频域多项式模型,提出了一种基于最小熵的通道相位误差估计与补偿方法。以距离向压缩脉冲图像的信息熵作为目标函数,误差多项式系数为估计变量,基于最小熵准则建立了相位误差的最优化估计模型。该方法能有效弥补内定标或外定标方法的不足,且不依赖于成像场景的地物类型,只需抽取少量回波数据作为误差估计的样本,具有耗费存储空间少、收敛速度快、不损失信噪比的优点。对不同场景的八通道实测数据进行了处理,实验结果验证了本文方法的有效性和稳健性。     

基于数值计算的机载SAR空变运动补偿算法

针对机载合成孔径雷达(SAR)高分辨率宽测绘带(HRWS)成像问题,在分析结合两步运动误差补偿的距离徙动算法基础上,提出一种基于数值计算的空变运动误差补偿算法。通过对粗聚焦图像进行分块,在子块的两维波数域进行空变运动补偿,补偿的相位包括方位相位误差、距离相位误差以及方位和距离的耦合相位,因此该算法在复杂航迹、高分辨和宽测绘带情况下仍具有较好的鲁棒性。最后对SAR仿真数据和实测数据进行处理,并与结合两步运动误差补偿的距离徙动算法进行比较,处理结果表明该算法能够更好地补偿空变运动误差。     

机载SAR反投影图像自聚焦处理方法

反投影算法(BPA)是一种经典的时间域合成孔径雷达(SAR)成像处理方法。BPA对回波数据插值累加得到图像,运动误差导致的目标散焦沿不同的倾斜角度存在,无法直接应用现有的自聚焦算法。为此,提出了一种新颖的BPA图像运动补偿方案。基于反投影数据运动相位误差和距离徙动分析,研究了修正投影栅格成像,从而去除重建图像中目标散焦方向的空变特性。在中低分辨率配置下,重建SAR图像能够直接应用相位梯度自聚焦(PGA)等进行运动补偿。点目标仿真实验和实测数据结果验证了该算法的有效性。     

一种非线性滤波器的误差分析及应用

针对一类具有未建模误差和扰动的非线性系统的状态估计问题,提出一种在线估计并补偿模型误差的非线性滤波算法,该算法利用非线性预测滤波(NPF)基于预测输出残差的方差最小的基本原则估计模型误差,冉利用扩展卡尔曼滤波(EKF)的思想对补偿后的模型进行状态估计;详细推导了状态估计误差及其方差阵的传播模型.以卫星姿态确定系统为例,...     

基于二维逆滤波的机载SAR 自聚焦算法

在聚束合成孔径雷达(SAR)自聚焦处理时,残留距离徙动(RRCM)必须在自聚焦处理之前完全去除,否则 将会严重降低自聚焦的性能。本文提出了一种基于二维逆滤波的自聚焦算法,该算法在补偿相位误差的同时也补 偿掉距离和方位的二维耦合相位,消除了RRCM对自聚焦的影响,提高了逆滤波自聚焦算法的性能。最后通过实 测数据处理验证了本文提出的二维逆滤波自聚焦算法的有效性。     

基于深度神经网络的机器人定位误差补偿方法

工业机器人由于高效率、低成本被广泛应用于智能制造业,但较低的绝对定位精度限制了其在高精度制造领域的推广应用。为提升机器人绝对定位精度并解决传统复杂的误差建模问题,提出了一种基于深度神经网络的机器人定位误差补偿方法。首先在笛卡尔空间进行拉丁超立方采样规划,获得目标点姿态对误差的影响规律;然后建立基于遗传粒子群算法优化深度神经网络(GPSO–DNN)的定位误差预测模型,实现对误差的预测和补偿;最后为验证该方法的准确性和优越性,与其他误差补偿模型进行对比。试验结果表明,基于GPSO–DNN的定位误差补偿方法的补偿精度最高,定位误差由补偿前的1.529mm减小为0.343mm,精度提高了77.57%。该方法能有效补偿机器人定位误差,大幅提高机器人的定位精度。     

An efficient 3-D near-field ISAR algorithm

This paper presents a new three-dimensional (3-D) near-field inverse synthetic aperture radar (ISAR) imaging technique. A 3-D ISAR image can be obtained by processing coherently the backscattered fields as a function of the frequency and two rotation angles about axes which are mutually orthogonal. Most of the existing ISAR algorithms are based on the Fourier transform and as such can tolerate only small amounts of wavefront curvature. Wavefront curvature must be taken into account when imaging an object in the near-field. Near-field ISAR imaging of large objects using a direct Fourier inversion may result in images which are increasingly unfocused at points which are more distant from the center of rotation. An algorithm based on an azimuth convolution between a near-field focusing function and the frequency domain backscattered fields is discussed. This convolution is efficiently implemented by using fast Fourier transform (FFT) techniques. Furthermore, in order to further alleviate the computational load of the algorithm, the discrete Fourier transform (DFT) of the focusing function is evaluated by means of the stationary phase method. Experimental results show that this technique is precise and virtually impulse invariant     

Performance analysis of wavefront curvature methods for rangeestimation of a moving source

In numerous practical situations a large array of sensors is required, especially for improving the system ability to detect and track moving sources. However, the array performance is strongly affected by the lack of stationarity of the impinging signals. The use of a large array of sensors allow us to perform the source localization by using the wavefront curvature. The analysis of the range estimates based on the wavefront curvature have been thoroughly performed by various authors but, to our knowledge, is restricted to the case of fixed sources. The study of the effects of source motion for range estimation (Section III) and source detection (Section V) constitutes an important part of this work. This study reveals that the array performance can be far from the expected values, especially for large array. Therefore, the robustness of a direct processing of the whole sensor array is very questionable. The computational burden constitutes another serious drawback of this (direct) approach. The use of partitioned processings (Sections IV and VI) seems thus quite promising even if (and perhaps because) it is not optimal so as to fulfil the computation cost and robustness requirements. The performance of such processings for estimating the range of moving sources is presented     

有限差分法的坐标变换诱导误差

有限差分法应用于具有复杂外形的网格时需要进行坐标变换,在此过程中经常会引入坐标变换诱导误差。在柱坐标系下使用均匀网格进行均匀流场计算,计算结果表明,即使物理坐标对计算坐标的变换函数连续可导、计算过程中坐标变换系数直接采用准确的解析式、网格完全正交并且充分光滑,也无法避免坐标变换诱导误差。理论分析表明,产生坐标变换诱导误差的机理是笛卡尔坐标系下的守恒型欧拉方程变换至贴体坐标系下后增加了源项。针对该问题,目前国内外学者通常采用几何守恒律,构建与差分格式相匹配的坐标变换系数计算方法来消除源项。本文介绍了从包含源项的离散等价方程基础上直接进行离散的新算法,在此基础上针对非等距网格条件下MUSCL类格式重构过程进行误差分析,理论推导表明重构中需要考虑非等距插值公式的影响系数,将变量转换至计算空间内进行MUSCL重构才能保证该过程具有均匀网格下的插值精度。通过理论分析及数值实验证明新算法对于均匀流场完全不会引入坐标变换误差。     

Polar format algorithm for bistatic SAR

Matched filtering (MF) of phase history data is a mathematically ideal but computationally expensive approach to bistatic synthetic aperture radar (SAR) image formation. Fast backprojection algorithms (BPAs) for image formation have recently been shown to give improved O(N/sup 2/ log/sub 2/N) performance. An O(N/sup 2/ log/sub 2/N) bistatic polar format algorithm (PFA) based on a bistatic far-field assumption is derived. This algorithm is a generalization of the popular PFA for monostatic SAR image formation and is highly amenable to implementation with existing monostatic image formation processors. Limits on the size of an imaged scene, analogous to those in monostatic systems, are derived for the bistatic PFA.     

Depth of Field for SAR with Aircraft Acceleration

Processing synthetic array radar (SAR) data is difficult if the depth of field is small. Aircraft acceleration can severely reduce the depth of field and thereby increase the processing. The effects of aircraft acceleration on the depth of field for three types of SAR processing are analyzed: (1) conventional processing (range-Dopper processing), (2) variable pulse-repetition frequency (PRF) (PRF changes to compensate for aircraft acceleration), and (3) polar format. Polar format is a technique for processing high resolution SAR which has a much larger depth of field in the ground plane than conventional processing. On the other hand, aircraft acceleration will limit the vertical depth of field for polar format to about the same value as for conventional processing. In addition, for polar format, the only component of aircraft acceleration that limits the vertical depth of field is the component normal to the slant plane containing the velocity and range vectors. Vector notation is used to graphically show the effects of aircraft acceleration. In addition to better insight, the vector notation gives equations for SAR compensation that do not depend on a specific coordinate system.     

极区横向地理系空间稳定型惯导算法研究

针对地心惯性系和当地地理系的空间稳定型惯导系统导航算法在极区导航失效的问题,提出了适用于空间稳定型惯导系统的极区导航算法。该算法通过伪经纬网构建了横坐标系参考框架,建立了横向地理系空间稳定型惯导系统力学编排,并在此基础上重新推导了通用的误差模型。最后,通过极点附近区域与穿越极点区域仿真分析了算法的极区有效性。仿真结果表明该算法在极点附近区域解算的伪航向角误差小于3′,伪经度误差小于4′;在穿越极点区域解算的伪纵摇角、伪横摇角误差小于0.3′,伪航向角误差小于3′,伪东向、伪北向速度误差小于1m/s,伪经度、伪纬度误差小于4.2′。该算法克服了极区导航计算溢出、误差放大等问题,提高了系统的极区导航精度,能够满足极区导航要求。     

3-D E-CSAR imaging of a T-72 tank and synthesis of its SAR reconstructions

The results of three-dimensional (3-D) imaging of a T-72 tank using its angular azimuthal (turntable) and linear elevation synthetic aperture data at X band are presented. This is achieved using an accurate and computationally efficient wavefront (Fourier-based) reconstruction algorithm for elevation and circular (E-CSAR) data. The E-CSAR 3-D images are then used to synthesize 2-D spotlight and stripmap slant plane synthetic aperture radar (SAR) images of the target at a desired range and squint angle. For this purpose, a procedure is introduced that incorporates the spatially varying azimuthal and elevation Doppler signatures of individual reflectors on the target as well as the mean range, azimuth, and elevation of the flight path. Results using the E-CSAR images of the T-72 tank are provided.