ZHU Weiqing1 HU Juan1,2 LIU Xiaodong1 LIU Zhiyu1 PAN Feng1

(1  Ocean Acoustic Technique Lab., Institute of Acoustic, Chinese Academy of Sciences  Beijing 100190)

(2　 Graduate School of Chinese Academy of Sciences Beijing 100029)

Received Jul.8,2009

Revised Aug.5, 2009

Abstract  A eigenspace-based source number estimation was presented. It projects the estimated covariance matrix of array signal into signal eigen-subspace and noise eigen-subspace, respectively. Using the orthogonality between signal eigen-subspace and noise eigen-subspace,it is easy to differentiate the contribution of signal and noise by using the criterion value, or the magnitude of projection. Like the Direction-of-Arrival (DOA) estimation algorithm, the estimator uses the eigenvalue decomposition of covariance matrix with order M × M, where M is the number of elements, and hence can save much computational burden. To reduce more computational burden, the estimation can be implemented by the decomposition in the real-value space. Computer simulation demonstrates the distribution of criterion value and the performance of the estimation method. The estimation method was also tested with the sonar data, which shows good performances.

PACS numbers: 43.30,43.60