On DoA Estimation for Rotating Arrays Using Stochastic Maximum Likelihood Approach

• Published in: IEEE transactions on signal processing Vol. 68; pp. 5219 - 5229
• Main Authors: Meller, Michal, Stawiarski, Kamil
• Format: Journal Article
• Language: English
• Published: New York IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Array signal processing; Arrays; Computer simulation; Correlation; Correlation coefficients; Direction of arrival estimation; Lower bounds; Maximum likelihood estimation; Maximum likelihood estimators; Monte Carlo simulation; Radar; rotating array; Rotation; stochastic maximum likelihood method; Stochastic processes
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2020.3022207

The flexibility needed to construct DoA estimators that can be used with rotating arrays subject to rapid variations of the signal frequency is offered by the stochastic maximum likelihood approach. Using a combination of analytic methods and Monte Carlo simulations, we show that for low and moderate source correlations the stochastic maximum likelihood estimator that assumes noncorrelated sources has accuracy comparable to the estimator that includes the correlation coefficient as one of the parameters. We propose several fast approximations of the stochastic maximum likelihood estimator and compare their accuracy with the Crámer-Rao lower bound. We also discuss the model order selection problem for the binary- and multiple-hypotheses cases.