TY - GEN
T1 - Sensor scheduling with waveform design for dynamic target tracking using MIMO radar
AU - Manjunath, Bhavana
AU - Zhang, Jun J.
AU - Papandreou-Suppappola, Antonia
AU - Morrell, Darryl
PY - 2009
Y1 - 2009
N2 - Multiple-input, multiple-output (MIMO) radar systems have gained significant attention as they can enhance target detection, identification and parameter estimation performance. In this paper, we consider the problem of optimizing the target tracking performance of a widely-separated MIMO radar system by scheduling the transmitter sensors and adaptively designing their waveforms. Specifically, for a tracking scenario consisting of a large number of MIMO radars, we propose: (a) a transmitter scheduling algorithm to achieve tracking performance gains based on resource constraints; and (b) an adaptive waveform optimization algorithm that further improves tracking performance. Under an ideal receiver assumption, we evaluate the predicted tracking mean-squared error using the derived Craḿer-Rao lower bound (CRLB) on the estimation of the target states. The scheduling algorithm is then formulated as a mixed boolean-convex optimization problem to minimize the CRLB. The optimum waveform parameters are adaptively obtained using sequential quadratic programming. The effectiveness of combining the MIMO radar technology with adaptive waveform design and sensor scheduling was demonstrated with simulations.
AB - Multiple-input, multiple-output (MIMO) radar systems have gained significant attention as they can enhance target detection, identification and parameter estimation performance. In this paper, we consider the problem of optimizing the target tracking performance of a widely-separated MIMO radar system by scheduling the transmitter sensors and adaptively designing their waveforms. Specifically, for a tracking scenario consisting of a large number of MIMO radars, we propose: (a) a transmitter scheduling algorithm to achieve tracking performance gains based on resource constraints; and (b) an adaptive waveform optimization algorithm that further improves tracking performance. Under an ideal receiver assumption, we evaluate the predicted tracking mean-squared error using the derived Craḿer-Rao lower bound (CRLB) on the estimation of the target states. The scheduling algorithm is then formulated as a mixed boolean-convex optimization problem to minimize the CRLB. The optimum waveform parameters are adaptively obtained using sequential quadratic programming. The effectiveness of combining the MIMO radar technology with adaptive waveform design and sensor scheduling was demonstrated with simulations.
UR - http://www.scopus.com/inward/record.url?scp=77953897347&partnerID=8YFLogxK
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U2 - 10.1109/ACSSC.2009.5470145
DO - 10.1109/ACSSC.2009.5470145
M3 - Conference contribution
AN - SCOPUS:77953897347
SN - 9781424458271
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 141
EP - 145
BT - Conference Record - 43rd Asilomar Conference on Signals, Systems and Computers
T2 - 43rd Asilomar Conference on Signals, Systems and Computers
Y2 - 1 November 2009 through 4 November 2009
ER -