Stochastic Maximum Likelihood Direction Finding in the Presence of Nonuniform Noise Fields

Ming-yan Gong, Bin Lyu

Publication date: 9 February 2023

Abstract: In this letter, we employ and design the expectation--conditional maximization either (ECME) algorithm, a generalisation of the EM algorithm, for solving the maximum likelihood direction finding problem of stochastic sources, which may be correlated, in unknown nonuniform noise. Unlike alternating maximization, the ECME algorithm updates both the source and noise covariance matrix estimates by explicit formulas and can guarantee that both estimates are positive semi-definite and definite, respectively. Thus, the ECME algorithm is computationally efficient and operationally stable. Simulation results confirm the effectiveness of the algorithm.

Has companion code repository: https://github.com/Jinyan0/mingyan.gong

This page was built for publication: Stochastic Maximum Likelihood Direction Finding in the Presence of Nonuniform Noise Fields

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6425935)