Tracking the direction-of-arrival of multiple moving targets by passive arrays: algorithm

• Published in: IEEE transactions on signal processing Vol. 47; no. 10; pp. 2655 - 2666
• Main Authors: Yifeng Zhou, Yip, P.C., Leung, H.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 1999; Institute of Electrical and Electronics Engineers
• Subjects: Algorithms; Applied sciences; Array signal processing; Arrays; Artificial satellites; Convergence; Covariance matrix; Detection, estimation, filtering, equalization, prediction; Direction of arrival estimation; Dynamics; Equipments and installations; Estimates; Exact sciences and technology; Information, signal and communications theory; Mathematical models; Maximum likelihood estimation; Mobile communication; Mobile radiocommunication systems; Moving targets; Radiocommunications; Sensor arrays; Signal and communications theory; Signal processing algorithms; Signal, noise; Spread spectrum communication; Target tracking; Telecommunications; Telecommunications and information theory; Tracking; Mobile radiocommunication; Direction of arrival; Moving target; Motion estimation; Optimization method; Satellite telecommunication; Signal processing; Multiple target; Maximum likelihood; Newton method; Observability
• ISSN: 1053-587X
• DOI: 10.1109/78.790648

We propose a maximum likelihood (ML) approach for tracking the direction-of-arrival (DOA) of multiple moving targets by a passive array. A locally linear model is assumed for the target motion, and the multiple target states (MTSs) are defined to describe the states of the target motion, The locally linear model is shown to be strongly locally observable almost everywhere. The approach is to estimate the initial MTS by maximizing the likelihood function of the array data. The tracking is implemented by prediction through the target motion dynamics using the initial MTS estimate. By incorporating the target motion dynamics, the algorithm is able to eliminate the spread spectrum effects due to target motion. A modified Newton-type algorithm is also presented, which ensures fast convergence of the algorithm. Finally, numerical simulations are included to show the effectiveness of the proposed algorithm.