关键词: 最小互熵谱分析, 多重信号分类算法, 波达方向估计

Abstract: DOA estimation is very important in array signal processing, while traditional algorithms such as Multiple Signal Classification algorithm （MUSIC） requires eigenvalue decomposition of covariance matrix and spatial spectral peak in the whole search, which is difficult and time-consuming. In particular, there exists robustness problem in two-dimensional DOA estimation algorithm. This paper presents a DOA estimation algorithm based on minimum cross-entropy spectral analysis, which requires only one array of sampling （snapshot） data with fewer elements. And it still can obtain high-resolution spectral analysis. Based on cepstrum method and inverse FFT transform it can improve the convergence speed. Numerical simulation results show that compared to the conventional spatial spectrum estimation methods this algorithm has a higher resolution and a smaller amount of computation, being capable of real-time array signal processing. The algorithm does not depend on the number of pre-estimate of the source, results in good tolerance, high resolution and low side lobe level.

Key words: minimum-cross entropy spectral analysis, Multiple Signal Classification algorithm（MUSIC）, Directional Of Arrival（DOA） estimation