Study Of Array Direction-finding Techniques In Low SNR Environment

Array signal processing make good use of the spatial signals with array antenna, receive more information of the signal than just one antenna, which is good for getting the information of time difference phase difference and direction arrival, so it has been widely use in communication, radar and electronic war etc. Spatial spectrum estimation is an important area in array signal processing, it overcome the problem of "Rayleigh limit" in the conventional beam-forming method and have the excellent merits, such as ability to estimate multiple sources at the same time, high resolution ability and so on. But, most of the spatial spectrum estimation methods seriously deteriorate in low SNR environment, so it become very important to study on the direction of arrival with low SNR condition.The dissertation focuses on array DOA estimation in the low SNR environment, the main work of this dissertation is on several methods which can improve the performance:(1)Beamspace high resolution method(2)DOA estimation based on higher order statistics(3)DOA estimation using cyclo-stationary signals, and gives some simulation results using MATLAB tools with performance analysis. Research show that, for a uniform linear array, the structure of correlation matrix of array output is Toeplitz. Based on this property of correlation matrix, DOA estimation performance can be improved a lot in low SNR environment. Beamspace high resolution methods which combine the conventional beamforming method with the subspace techniques have good performance such as low computation and high resolution in low SNR, Furthermore, they can reduce sensitivity to sensor perturbations. The methods using the high order statistics and cyclo-stationary characteristics are largely improve the performance in low SNR environment, but they need large computation. The paper also discuss the application of these method and the main technique problem at present, which can give some help in practice.