Abstract

This paper proposes a novel time}frequency maximum likelihood (t}f ML) method for direction-of-arrival (DOA) estimation for nonstationary signals impinging on a multi-sensor array receiver, and compares this method with conventional maximum likelihood DOA estimation techniques. Time}frequency distributions localize the signal power in the time}frequency domain, and as such enhance the e!ective SNR, leading to improved DOA estimation. The localization of signals with di!erent time}frequency signatures permits the division of the time}frequency domain into smaller regions, each containing fewer signals than those incident on the array. The reduction of the number of signals within di!erent time}frequency regions not only reduces the required number of sensors, but also decreases the computational load in multidimensional optimizations. Compared to the recently proposed time}frequency MUSIC (t}f MUSIC), the proposed t}f ML method can be applied to coherent environments, without the need to perform any type of preprocessing that is subject to both array geometry and array aperture. # 2000 The Franklin Institute. Published by Elsevier Science Ltd. All rights reserved. Keywords: Time}frequency distribution; Direction "nding; Maximum likelihood; Spatial time}frequency distribution; Array processing 1.

Citations