高维小样本自适应阵列信号处理研究及应用

项目名称： 高维小样本自适应阵列信号处理研究及应用

项目编号： No.61271293

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 无线电电子学、电信技术

项目作者： 冯大政

作者单位： 西安电子科技大学

项目金额： 80万元

中文摘要： 随着现代雷达、通信等技术发展，采用的天线（传感器）阵列规模越来越大、信号维数越来越高。然而，因受环境等因素的限制，采集样本数还是很少。如在典型的多输入多输出（MIMO）雷达等中，信号维数或自由度常可达到数千到数万，而采集样本只有几十到数百个，即采集样本数远小于信号维数，这导致许多阵列信号处理方法失效。因此，高维小样本自适应阵列信号处理将成为信号处理领域的研究热点，其研究对于提升机载雷达和MIMO雷达等的信号处理性能具有重要的理论和现实意义。本项目以大规模阵列信号处理为背景，着重研究高维小样本情况下的自适应波束形成、空时多维自适应处理和参数估计等的新理论、新方法。针对不同应用背景，提出快速、有效、稳健的自适应阵列信号处理算法。深入研究小样本、非均匀样本及各种非理想因素等对自适应阵列信号处理算法的影响，提出改善现有和新提算法性能的方法，为大规模自适应阵列处理的实用提供理论和方法支持。

中文关键词： 小样本；大规模阵列；自适应处理；稳健性；多输入多输出（MIMO）

英文摘要： With the development of the morden radar and communication techniques, the scale of the antenna(sensor) array and the dimension of signals become larger and larger. However, the samples which could be used is small due to the limits of environment. For example, in the typical multiple-input multiple-output(MIMO) radar, the dimension(or degree) of signals have achieved to thousands or ten thousands, while only tens to hundreds of samples are available to be used, i.e., the number of samples is markedly smaller than the dimension of signal, which leads to many methods of adaptive array processing disable. Therefore, the study of adaptive large-scale array signal processing under small sampled data will become a hot research area in signal processing and have impormant academic and practical signification for performance improvement of the airborne radar and MIMO radar. Against the background of large-scale array processing, this project mainly study on the new theories and methods of the adaptive beamforming, space-time adaptive processing and parameters estimation using high-dimensional and small-sampled data. Aimed at different applications, the fast, efficient and robust adaptive array processing algorithms will be proposed. Furthermore, the impact caused by small-sampled data, the unhomogeneous samples and va

英文关键词： small sanpled data；large-scale array；adaptive processing；robust；multiple-input multiple-output