DOA estimation of quasi-stationary signals with less sensors than sources and unknown spatial noise covariance: a Khatri-Rao sub

In real-world applications such as those for speech and audio, there are signals that are nonstationary but can be modeled as being stationary within local time frames. Such signals are generally called quasi-stationary or locally stationary signals. This paper considers the problem of direction-of-arrival (DOA) estimation of quasi-stationary signals. Specifically, in our problem formulation we assume: i) sensor array of uniform linear structure; ii) mutually uncorrelated wide-sense quasi-stationary source signals; and iii) wide-sense stationary noise process with unknown, possibly nonwhite, spatial covariance. Under the assumptions above and by judiciously examining the structures of local second-order statistics (SOSs), we develop a Khatri

• Type: Journal
• Year: 2010
• Where: TSP
• Authors: Wing-Kin Ma, Tsung-Han Hsieh, Chong-Yung Chi
• Keywords: Artificial Intelligence, KR Subspace Approach, Quasi-stationary Signals, Quasi-stationary Source Signals, TSP 2010