The upper bound of multi-source DOA information in sensor array and its application in performance evaluation

EURASIP journal on advances in signal processing

article

Tu, Weilin¹  Xu, Dazhuan¹  Zhou, Ying¹  Shi, Chao¹ 

[1] College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics

关键词: DOA estimation;    Information theory;    Upper bound;    Cramer-Rao bound;    Sensor arrays;   

DOI  :  10.1186/s13634-020-00700-8

来源: SpringerOpen

【 摘 要 】

Direction of arrival (DOA) estimation has been discussed extensively in the array signal processing field. In this paper, the authors focus on the multi-source DOA information which is defined as the mutual information between the DOA and the received signal contaminated by complex additive white Gaussian noise. A theoretical expression of DOA information with multiple sources is derived for the uniform linear array. At high SNRs and under the sparse-source assumption obtained is the upper bound of DOA information contained in K sparse sources which can be regarded as the sum of all single-source information minus the uncertainty of sources’ order logK!. Moreover, because of the uncertainty of multi-sources’ order, the posteriori probability distribution of DOA no longer obeys single peak Gaussian distribution so that the mean square error is unsuitable in evaluating the performance of multi-dimensional parameter estimation. Consequently, entropy error (EE) is used as a new performance evaluation metric, whose relationship with DOA information is given.

【 授权许可】

CC BY