Extension of root-MUSIC to non-ULA Array Configurations

In this paper we introduce a method for modelling the steering vector of an arbitrary array such that its steering vector can be expressed as the product of a characteristic matrix of the array itself and a vector with a Vandermonde structure containing the unknown parameter. We call this technique manifold separation. By exploiting this concept, we developed a novel version of the root-MUSIC algorithm for direction of arrival (DoA) estimation of sources. It can be applied to arbitrary 2-D array configurations. The proposed algorithm processes the data in element-space domain and does not require any transformation or array interpolation. The novel algorithm, named element-space root-MUSIC, provides computationally low complexity (search-free) DoA estimation and has close to CRB performance already at low SNRs

[1]  Michael D. Zoltowski,et al.  Eigenstructure techniques for 2-D angle estimation with uniform circular arrays , 1994, IEEE Trans. Signal Process..

[2]  G. Sommerkorn,et al.  Multidimensional high-resolution channel sounding in mobile radio , 2004, Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.04CH37510).

[3]  Buon Kiong Lau Applications of antenna arrays in third-generation mobile communications , 2002 .

[4]  Marius Pesavento,et al.  Virtual array design for array interpolation using differential geometry , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[5]  Anthony J. Weiss,et al.  Coherent wide-band processing for arbitrary array geometry , 1993, IEEE Transactions on Signal Processing.

[6]  Visa Koivunen,et al.  Beamspace Transform for UCA: Error Analysis and Bias Reduction , 2006, IEEE Transactions on Signal Processing.

[7]  V. Koivunen,et al.  Reducing Excess Variance in Beamspace Methods for Uniform Circular Array , 2005, IEEE/SP 13th Workshop on Statistical Signal Processing, 2005.

[8]  Benjamin Friedlander,et al.  The root-MUSIC algorithm for direction finding with interpolated arrays , 1993, Signal Process..

[9]  Björn E. Ottersten,et al.  Array interpolation and bias reduction , 2004, IEEE Transactions on Signal Processing.