Title :
Asymptotic efficiency of manifold ambiguity resolution for DOA estimation in nonuniform linear antenna arrays
Author :
Abramovich, Yuri I. ; Gorokhov, Alexei Y. ; Spencer, Nicholas K.
Author_Institution :
Cooperative Res. Centre for Sensor Signal & Inf. Processing, The Levels, SA, Australia
Abstract :
Linear dependence amongst the nonuniform linear array antenna manifold ("steering vectors") leads to a failure of the MUSIC algorithm to identify the correct signal sources (a "manifold ambiguity"). However, this failure does not necessarily imply that unambiguous DOA estimates are unobtainable. For fully-augmentable array geometries, an algorithm involving the standard augmentation approach successfully resolves the manifold ambiguity. For partially-augmentable and arbitrary-geometry arrays, the augmentation approach was generalised, mainly relying upon maximum-entropy covariance matrix completion. This paper deals with an asymptotic analysis of the generalised approach which is capable of resolving manifold ambiguity (provided the corresponding Fisher matrix is not rank-deficient).
Keywords :
covariance matrices; direction-of-arrival estimation; linear antenna arrays; maximum entropy methods; signal sources; DOA estimation; Fisher matrix; MUSIC algorithm; algorithm; arbitrary-geometry arrays; asymptotic efficiency; augmentation approach; fully-augmentable array geometries; linear dependence; manifold ambiguity resolution; maximum-entropy covariance matrix completion; nonuniform linear antenna arrays; nonuniform linear array antenna manifold; partially-augmentable arrays; signal sources; steering vectors; Antenna arrays; Antenna measurements; Australia; Direction of arrival estimation; Geometry; Linear antenna arrays; Multiple signal classification; Sensor arrays; Signal processing; Signal resolution;
Conference_Titel :
Signal Processing Advances in Wireless Communications, First IEEE Signal Processing Workshop on
Conference_Location :
Paris, France
Print_ISBN :
0-7803-3944-4
DOI :
10.1109/SPAWC.1997.630231