Robust adaptive subspace extraction for DOA tracking

This paper addresses the problem of extracting a time-varying signal subspace from noisy signal measurements for direction-of-arrival (DOA) estimation and tracking. A robust adaptive method for extracting the signal subspace is developed based on robust statistics. The method is more resistant to the presence of outliers than existing adaptive methods. Robust DOA estimation and tracking are achieved by incorporating the method with the TLS-ESPRIT method. Experimental results demonstrate the viability and superiority of the proposed method over existing methods