EE Seminar: Optimal Adaptive Transmit Beamforming for Target Tracking in Cognitive MIMO Radar/Sonar

~~Speaker:  Nathan Sharaga, 
M.Sc. student under the supervision of Prof. Joseph Tabrikian and Hagit Messer

Wednesday, March 18th, 2015 at 15:00
Room 011, Kitot Bldg., Faculty of Engineering

Optimal Adaptive Transmit Beamforming for Target Tracking in Cognitive MIMO Radar/Sonar

Abstract
In this work, a new adaptive beamforming method for target tracking by cognitive multiple-input multiple-output (MIMO) radar or sonar is proposed. In this method, at each step, the transmit beampattern is sequentially determined based on history observations. The conditional Bayesian Cramér-Rao bound (BCRB) for one-step prediction of the state-vector in target tracking problem was used as the optimization criterion for beampattern design. The conditional BCRB for one-step prediction of the state vector is recursively computed at each step. The conditional BCRB is computationally expensive, therefore a low-complexity method for computing an approximation of the conditional BCRB is proposed. The proposed method is applied to the problem of target tracking in a shallow underwater environment in the presence of environmental uncertainties. It is shown that the method is able to automatically focus the transmit beampattern toward the target direction within a few steps at very low signal-to-noise ratios (SNR's). The method exhibits much better performance in terms of localization error compared to other methods, such as orthogonal (omni-directional) transmission.