Direction of arrival tracking for signals with known waveforms based on block least squares techniques. Issue 11 (July 2017)

• Record Type: Journal Article
• Authors: Gu, Jian-Feng; Zhu, Wei-Ping; Swamy, M.N.S.
• Is Part Of: Journal of the Franklin Institute. Volume 354:Issue 11(2017:Nov.)
• Page Start: 4573
• Page End: 4594
• Publication Date: 2017-07
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2017.04.004
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: In this paper, we address the problem of tracking DOA of multiple moving targets with known signal source waveforms and unknown gains in the presence of Gaussian noise using a nonuniform linear array. Herein, we make use of the fact that the output of each sensor can be described as a linear regression model whose coefficients each contain a pair of DOA and gain information corresponding to one target. These coefficients are determined by solving a linear least squares (LS) problem and then updated recursively based on a block QR decomposition recursive least squares (QRD-RLS) technique or a block regularized LS technique. Since the coefficients from different sensors have the same amplitude but variable phase information for the same signal, along with simple algebraic manipulations the well-known generalized least squares (GLS) are used to obtain an asymptotically-optimal DOA estimate without requiring a search over a large region of the parameter space. Computer simulations show that the proposed DOA tracking techniques when applied to a sparse antenna array can provide a better tracking performance than some of the existing methods do.