Title :
Signal subspace techniques for DOA estimation using higher order statistics
Author :
Leyman, A.R. ; Durrani, T.S.
Author_Institution :
Dept. of Electron. & Electr. Eng., Strathclyde Univ., Glasgow, UK
Abstract :
Eigendecomposition based techniques such as MUSIC and its variants constitute effective methods for determining the direction of arrival (DOA) estimates of narrowband sources. A new strategy which extends the MUSIC algorithm to higher order statistics (HOS) is proposed for estimation of the DOA. Also, we present a new method for the estimation of the number of multiple narrowband incoherent and coherent non-Gaussian source signals arriving on the array which we consider as a significant contribution. The performance of the technique is compared with other suggested HOS-based methods
Keywords :
direction-of-arrival estimation; eigenvalues and eigenfunctions; higher order statistics; DOA estimates; DOA estimation; HOS; MUSIC algorithm; coherent nonGaussian source signals; direction of arrival; eigendecomposition; higher order statistics; multiple source signals; narrowband incoherent nonGaussian source signals; performance; signal subspace techniques; Array signal processing; Direction of arrival estimation; Gaussian noise; Higher order statistics; Multiple signal classification; Narrowband; Sensor arrays; Signal processing; Signal resolution; Spatial resolution;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.480599
