We present a novel max-search approach for maximum likelihood (ML) DOA estimation with
unknown number of signals. Conventional methods such as the information theoretic
criterion based approach and the multiple hypothesis test procedure estimate the model order
and parameters of interest simultaneously. These methods are usually computationally expensive
since ML estimates are required for a series of nested models. In this paper, we propose a
computationally efficient solution to avoid this full search procedure. Our method computes ML
estimates for the maximally hypothesized model, and selects relevant estimates associated with
true parameters by thresholding likelihood ratios. Furthermore, we derive an upper bound and
a lower bound on the error covariance matrix. Numerical results show that despite model order
uncertainty, the max-search procedure yields comparable estimation accuracy as standard approaches
at a much reduced computationalcost.
Pei-Jung Chung received Dr.-Ing. degree in 2002 from Ruhr-University Bochum, Germany with distinction.
From 1998 to 2002 she was with Signal Theory Group, Ruhr-University Bochum, Germany. From 2002 to 2004
she held a post-doctoral position at Carnegie Mellon University and University of Michigan, Ann Arbor,
USA, respectively. From 2004 to 2006 she was Assistant Professor with National Chiao Tung University,
Hsin Chu, Taiwan. In 2006 she joined the Institute for Digital Communications, School of Engineering,
the University of Edinburgh, UK as Lecturer.
Dr Chung has served in technical program committees of major conferences. Currently, she is
Associate Member of IEEE Signal Processing Society, Sensor Array Multichannel Technical Committee
and serves for IEEE Communications Society, Multimedia Communications Technical Committee as Vice
Chair of Interest Group on Acoustic and Speech Processing for Communications. Her research interests
include array processing, statistical signal processing, wireless MIMO communications and distributed
processing in wireless sensor networks. Dr Chung is a senior member of IEEE.