Study Of High Resolution DOA Estimation Algorithm

DOA estimation is an important research direction of modern array signal processing, and has been widely applied in the field of radar, sonar, biomedical, communications, etc, thus the study of DOA estimation method has more important theoretical and practical values. In this thesis, we study the parameter estimation method of DOA, frequency and range under the Gaussian white noise, the main work is summarized as follows:1. In chapter2, some of the basics involved in this article are given. An overview of linear prediction algorithm (LP), Root-MUSIC algorithm, PUMA algorithm, Least Squares estimation and Weighted Least Squares estimation are discussed, and the basic principles and procedure of these algorithms are also described.2. In chapter3, a new method for two-dimensional (2-D) DOA estimation of based on the expansion of available PUMA algorithm with single snapshot in URA (Uniform Rectangular Array) is proposed. Compared with the conventional2-D ESPRIT algorithm, the proposed algorithm has higher accuracy and closer to the corresponding CRLB at higher SNR. The proposed algorithm has lower computational complexity, and can be automatically paired without increasing the computational burden.3. In chapter4, a simple DOA estimation method based on Root-MUSIC with NLA (Nonuniform Linear Array) is proposed. The comparison of performance in the case of the same aperture and the same array element with ULA (uniform linear array) are given. Simulation results also show that the proposed algorithm has more effective than that with ULA.4. In chapter5, a simple algorithm for multiple near-field source localization with UCA (uniform circular array) is proposed. The key idea of the proposed method is to construct two correlation functions. The one uses the centrosymmetric property of UCA to construct a special correction matrix, each column vector with a different delay, and the matrix contains information of azimuth/elevation angle only. The other is an ordinary correlation function which only contains the information of the range. Simulation results show that the proposed algorithm is effective, and the parameters of multiple sources can be matched automatically.5. Finally, a conclusion is drawn in chapter6.