Title :
Tracking the direction-of-arrival of multiple moving targets by passive arrays: asymptotic performance analysis
Author :
Zhou, Yifeng ; Yip, Patrick C. ; Leung, Henry
Author_Institution :
Electron. Support Meas. Sect., Defence Res. Establ., Ottawa, Ont., Canada
fDate :
10/1/1999 12:00:00 AM
Abstract :
In the companion paper of Zhou, Yip and Leung (see ibid., vol.47, no.10, p.2655-66, 1999), the maximum likelihood (ML) algorithm for tracking the DOAs of multiple moving targets by passive arrays is presented. In this paper, we provide an asymptotic performance analysis of the algorithm. The statistical consistency of the ML estimates is discussed, and their asymptotic covariances are derived. The Cramer-Rao bounds for the ML estimates are investigated, and their relative efficiency conditions are discussed. The asymptotic performance of the ML tracking algorithm is compared with that of the extended Kalman filter (EKF) under the assumption that the target waveforms are known. Finally, numerical simulation results are used to verify the theoretical results
Keywords :
Kalman filters; array signal processing; covariance analysis; direction-of-arrival estimation; filtering theory; maximum likelihood estimation; nonlinear filters; target tracking; tracking filters; Cramer-Rao bounds; DOA tracking; ML estimates; ML tracking algorithm; Monte-Carlo simulations; asymptotic covariances; asymptotic performance analysis; direction-of-arrival tracking; efficiency; extended Kalman filter; maximum likelihood algorithm; multiple moving targets; numerical simulation results; passive arrays; statistical consistency; target waveforms; Array signal processing; Covariance matrix; Direction of arrival estimation; Gaussian noise; Maximum likelihood estimation; Numerical simulation; Performance analysis; Sensor arrays; Signal processing algorithms; Target tracking;
Journal_Title :
Signal Processing, IEEE Transactions on
