A Low Complexity Adaptive Algorithm for Eigenspace-Based Two-Dimensional Direction of Arrival Tracking

Kuo-Hsiung WU
Wen-Hsien FANG

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E92-A    No.8    pp.2097-2106
Publication Date: 2009/08/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E92.A.2097
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Intelligent Transport System
fast algorithm,  2-D DOA tracking,  2-D Unitary ESPRIT,  azimuth-elevation tracking,  smart antennas,  

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In this paper, we present a low complexity, yet accurate adaptive algorithm for the tracking of two-dimensional (2-D) direction of arrival (DOAs) based on a uniform rectangular array (URA). The new algorithm is a novel hybrid of tracking and beamforming processes by making use of three stages of one-dimensional (1-D) DOA tracking algorithms -- in a hierarchical tree structure -- to determine the two DOA components iteratively in a coarse-fine manner. In between every other 1-D DOA tracking algorithm, a complementary orthogonal beamforming process is invoked to partition the incoming signals into appropriate groups to enhance the tracking accuracy. Since the new algorithm only involves the 1-D subspace-based DOA tracking algorithm, the overall complexity is substantially less than the direct two-dimensional (2-D) extension of the existing 1-D DOA tracking algorithms, which requires an update of higher-dimensional vectors followed by a higher-dimensional eigendecomposition or a 2-D search. Furthermore, with the tree-structured DOA tracking scheme, the tracked 2-D DOA components are automatically paired without extra computational overhead. Furnished simulations show that the new algorithm can provide satisfactory tracking performance in various scenarios.