The Research Of Joint Calibration Algorithms In DOA Estimation

Direction of arrival(DOA) is one of the important researches in array signal processing, widely used in radar, sonar, communication system, intelligent home appliances and intelligent conference system. Most of existing array calibration algorithm is aimed at a single parameter estimation. However, in the practical engineering application, a variety of errors often exist at the same time, so that the estimation performance of existing calibration algorithm will be seriously deteriorated, and even fail. Therefore, study of joint calibration algorithms has important theoretical significance and practical value, and is also a hot topic in array signal processing field in recent years. In this paper, DOA estimation with mutual coupling and channel gain/phase is mainly studied. The main research contents are as follows:Firstly, the basic knowledge of spatial spectrum estimation is introduced briefly. Classical algorithms such as MUSIC and PM are discussed, and the estimation performance of the two algorithms in different SNR, sampling number, array element number and angle-interval is analyzed and compared through simulation experiments.Secondly, the system model of array errors and the influence of array error on DOA estimation are introduced and the array error effect on DOA estimation is analyzed. Through the simulation experiments, it further illustrates the effect of channel amplitude phase error, mutual coupling and position error of array elements on the performance of DOA estimation. Then the mutual coupling self-calibration algorithm of uniform linear array is simulated and analyzed comparatively. Besides, the limitation of the algorithm’s performance is mainly studied.Finally, since it has large amount of calculation and is easy to fall into the local convergence by using traditional iterative search algorithm, joint estimation of mutual coupling and channel parameters for uniform circular array is proposed by using mutual coupling matrix’ Toeplitz properties of cyclic symmetric of the uniform circular array. The algorithm first separates two kinds of error parameters by the linear equation of DFT beam space. Then an optimization problem with constraints is constructed to estimate the two kinds of error parameters by relevant linear equation getting from angle searching. At last, the optimization problem is solved to complete the estimation of the two kinds of error parameters. Compared to traditional algorithms, this algorithm has higher estimation precision, no local convergence problem, and the computational complexity is greatly decreased.