Fast DOA Tracking of Coherently Distributed Sources Based on Subspace Updating
Xian Sheng Guo, Qun Wan, Wan Lin Yang · 2006
In this paper, we address the problem of tracking the direction (DOA) of coherently distributed (CD) sources using subspace updating. The conventional multiple signal classification (MUSIC) algorithm, which should estimate covariance matrix, can not perform DOA tracking until it acquires covariance matrix. In addition, MUSIC algorithm needs spectrum peaks search and inverse matrix operator, so it can not estimate DOA of distributed sources rapidly. By contrast, the proposed algorithm uses subspace tracking to estimate signal subspace iteratively, then, the central angles are estimated using TLS-ESPRIT for CD sources. This algorithm can rapidly track DOA of CD sources even when their angular spreads are slightly wide