基于基尼系数和改进压缩感知的ISAR成像新方法研究

项目名称： 基于基尼系数和改进压缩感知的ISAR成像新方法研究

项目编号： No.61301199

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 无线电电子学、电信技术

项目作者： 成萍

作者单位： 河海大学

项目金额： 25万元

中文摘要： 压缩感知（CS）提供了一种新的信号获取和重构方式，目前它在ISAR成像中已取得了一些成果，但仍存在一些问题需要解决。为了提高压缩感知ISAR成像方法的性能，拟开展以下工作：（1）目前，CS中一般采用l1、lp或l0范数来衡量信号的稀疏性，但这些范数确定稀疏的方式并不符合人们对稀疏的直觉理解。拟采用一种更加有效的稀疏测度-基尼系数提高重构性能。（2）在压缩感知ISAR成像中，连续参数的离散化会使得使用的基函数与真正的基函数不一致，此时成像性能明显下降。为了克服这个缺陷，拟研究一种能够自校正扰动的重构算法，并采用线性估计器提高强散射点幅度和相位的估计精度。（3）在基于CS的ISAR机动目标成像中，拟研究基于联合优化的方位维成像方法和基于CS修正方法的距离维成像方法。本项目的研究将完善和扩展现有的CS理论，为CS方法用于ISAR实际成像提供理论和技术基础，对推动CS的应用具有重要的意义。

中文关键词： 压缩感知；ISAR成像；稀疏测度；偏离栅格；机动目标

英文摘要： Compressed sensing(CS) supplies a new signal acquisition and reconstruction method.Although ISAR imaging based on CS has obtained some achievements at present, there are some problems to be solved. To improve the performance of compressed sensing ISAR imaging method, the project intends to carry out the the following work: (1) At present, l1, lp or l0 norm are popularly used in CS to measure the sparsity of signal. But these norms quantify sparsity in a way that runs counter to an intuitive understanding of sparsity. Gini index, as a more effective measure of sparsity, is to be explored to improve reconstruction performance. (2) In compressed sensing ISAR imaging, discretization of continuous parameters can make that these is mismatch between the used basis and actual basis, and then the performance of imaging degenerates greatly. To overcome the shortcoming, a reconstruction algorithm which can self correct perturbation is to be studied and a linear estimator is to be employed to improve the estimate accuracy of strong scattering points' amplitude and phase. (3) In CS based ISAR maneuvering target imaging, an imaging method in direction based on joint optimization and an imaging method in range based on modified-CS method will be studied. The research of the project will improve and extend existing CS theory, s

英文关键词： compressed sensing；ISAR imaging；sparsity measure；off grid；maneuvering targets