Time–frequency maximum likelihood methods for direction finding

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 effective SNR, leading to improved DOA estimation. The localization of signals with different 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 different 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.