【作者】 杨琳琳；

【导师】 马洪；

【作者基本信息】 华中科技大学 ， 通信与信息系统， 2007， 硕士

【摘要】 在无源定位系统中,对信号源的DOA估计是一个关键问题,它将直接关系到系统定位的准确性。DOA估计作为阵列信号处理中的一个重要研究方向,以其优异的参数估计性能、广阔的应用前景引起了人们极大的兴趣。本文针对如何减少特征子空间类估计算法的运算量和相干信号源DOA估计这两方面的问题做了一些研究工作,主要包括以下内容:关于特征子空间类估计算法的实时性研究:介绍了经典的MUSIC算法,详细地分析MUSIC算法的特点,在此基础上研究了波束空间的MUSIC算法和多项式求根MUSIC算法;介绍了针对阵列导向矩阵和数据协方差矩阵的实值化处理技术和将DFT变换应用于DOA估计的DFT算法;提出一种快速子空间DOA估计方法。用Matlab进行仿真实验表明:波束空间方法、求根处理技术、实值化处理和快速子空间DOA估计方法能有效降低特征子空间类算法的计算量,但实值化处理的分辨性能不高;DFT算法利用一次快拍数据估计信源DOA,因而计算量非常小,但分辨率较差。关于相干信号源的DOA估计算法研究:介绍了空间平滑类(SS)算法的特点和解相干性能;介绍了盲估计算法,该方法对相干信号源的生成导向矢量进行频率谱估计,间接得到信号的DOA;提出一种DOA估计新方法——DSM算法,本质上,该方法仅利用了天线阵的结构特征实现DOA的估计,而不依赖采样数据空间的特征结构,算法实现限制条件少,可广泛应用于众多不同的实际环境。用Matlab进行仿真实验表明:空间平滑算法、盲估计算法和DSM算法均能有效估计相干信号源DOA;空间平滑算法和盲估计算法性能相当,且在小信噪比条件下,两者性能略优于DSM算法;DSM算法对相干和非相干信号情况进行统一处理,在独立信号源情况下,DSM算法性能略差于MUSIC方法。本课题受到2006年航天支撑技术基金(编号20060307)和2006武汉光电国家实验室基金支持。更多还原

【Abstract】 In passive location system, the DOA estimation is an important issue which will decide whether the object could be located or not. As an important area in array signal processing, DOA estimation draws more and more attention because of its high performance and wide usage.This paper focuses on the two problems of how to reduce the computation load of eigen-subspace algorithm and the DOA algorithm for coherent signals. The main contents of this research are as follows.1) The research on the real-time realization of eigen-subspace algorithm.Based on the basic MUSIC method and its characteristic, we investigate Beam-space MUSIC method and Root-MUSIC method; give the introduction of the Unitary operation on array steer vector and data covariance matrix and the introduction of DFT method which introduces the DFT transform into the DOA estimation; propose a new fast subspace algorithm for DOA estimation. The Matlab simulation results show that the Beam-space method, the Root method, Unitary operation and fast subspace DOA method all can reduce the computation load of eigen-subspace algorithm effectively. But the performance of Unitary operation is not very good. The DFT method has a low computation complexity and a little operation time because there is only a snapshot data involved. And the performance is not very good due to the limited data.2) The research on the DOA algorithm for coherent signals.We introduce the characteristic and decorrelation performance of spatial smoothing(SS) method; introduce the Blind estimation method which makes a frequency spectrum estimation on the generalized steer vector of coherent signals and gets the DOA information indirectly; propose a new method—DSM method for DOA estimation. Essentially, DSM method only bases on the characteristic of sensor array and doesn’t rely on the eigen-structure of sample data subspace. And it can be widely used in different areas because of its few restriction. The Matlab simulation results show that the SS method, the Blind method and DSM method all can estimate the DOA of coherent signals effectively. The performance of SS method is the same as that of Blind method, and both slightly better than that of DSM method on the condition of low SNR. DSM method which offers the similar procedure for coherent and incoherent signals, has a slightly worse performance than MUSIC method under the situation of independent signals.This paper is supported by national space foundation (No.20060307) and 2006 foundation of Wuhan national research lab of photoelectricity.更多还原