DOA estimation by eigendecomposition using single vector Lanczos Algorithm.

Abstract

Subspace methods of solving spectral estimation and direction of arrival (DOA) problems involve finding the eigenvalues and eigenvectors of correlation matrices. Using the Lanczos algorithm some of the extreme eigenvalues and eigenvectors can be approximated without requiring the entire matrix decomposition theoretically saving many computations. This thesis develops a model and a form of the Lanczos algorithm to solve the DOA problem. The relationship of the number of eigenvectors used to the accuracy of the results in a low signal to noise ratio example are examined.