Title :
Target Localization and Tracking in Noncoherent Multiple-Input Multiple-Output Radar Systems
Author :
Niu, Ruixin ; Blum, Rick S. ; Varshney, Pramod K. ; Drozd, Andrew L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Virginia Commonwealth Univ., Richmond, VA, USA
fDate :
4/1/2012 12:00:00 AM
Abstract :
For a noncoherent multiple-input multiple-output (MIMO) radar system, the maximum likelihood estimator (MLE) of the target location and velocity, as well as the corresponding Cramer-Rao lower bound (CRLB) matrix, is derived. MIMO radar´s potential in localization and tracking performance is demonstrated by adopting simple Gaussian pulse waveforms. Due to the short duration of the Gaussian pulses, a very high localization performance can be achieved, even when the matched filter ignores the Doppler effect by matching to zero Doppler shift. This leads to significantly reduced complexities for the matched filter and the MLE. Further, two interactive signal processing and tracking algorithms, based on the Kalman filter and the particle filter (PF), respectively, are proposed for noncoherent MIMO radar target tracking. For a system with a large number of transmit/receive elements and a high signal-to-noise ratio (SNR) value, the Kalman filter (KF) is a good choice; while for a system with a small number of elements and a low SNR value, the PF outperforms the KF significantly. In both methods, the tracker provides predictive information regarding the target location, so that the matched filter can match to the most probable target locations, reducing the complexity of the matched filter and improving the tracking performance. Since tracking is performed without detection, the presented approach can be deemed as a track-before-detect approach. It is demonstrated through simulations that the noncoherent MIMO radar provides significant tracking performance improvement over a monostatic phased array radar with high range and azimuth resolutions. Further, the effects of coherent integration of pulses are investigated for both the phased array radar and a hybrid MIMO radar, where only the pulses transmitted and received by colocated transceivers are coherently integrated and the other pulses are combined noncoherently. It is shown that the hybrid MIMO radar achieves significa- t tracking performance improvement when compared with the phased array radar, by using the extra Doppler information obtained through coherent pulse integration.
Keywords :
Doppler effect; Kalman filters; MIMO radar; matched filters; particle filtering (numerical methods); radar tracking; target tracking; Cramer-Rao lower bound matrix; Doppler effect; Doppler information; Gaussian pulse waveform; Kalman filter; MIMO radar system; coherent pulse integration; interactive signal processing; matched filter; maximum likelihood estimator; noncoherent multiple input multiple output radar system; particle filter; target localization; target location; target tracking; target velocity; track-before-detect approach; tracking algorithm; MIMO radar; Matched filters; Maximum likelihood estimation; Radar tracking; Receivers; Target tracking;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
DOI :
10.1109/TAES.2012.6178073