HIGH RESOLUTION BEARING ESTIMATION WITHOUT EIGEN DECOMPOSITION.
Date of Original Version
The authors consider the bearing estimation problem as a matrix approximation problem. The columns of a matrix X are embedded with the snapshot vectors from an N element array. The matrix X is approximated by a matrix X//M in the least square sense. The rank, as well as the structure, of the space spanned by columns of X//M is prespecified. After X//M is computed, the bearings of the sources and the spatial correlation of the source signals can be estimated. The technique is then compared with other methods such as MUSIC and SVD processing. When the number of snapshot vectors available for processing is large, a simpler adaptive algorithm is suggested.
Publication Title, e.g., Journal
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Kumaresan, R., and A. K. Shaw. "HIGH RESOLUTION BEARING ESTIMATION WITHOUT EIGEN DECOMPOSITION.." ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (1985): 576-579. https://digitalcommons.uri.edu/ele_facpubs/725