Integrated detection and tracking via closed-loop radar with spatial-domain matched illumination

We develop a framework for closed-loop detection and tracking of targets. The framework is based on a Bayesian representation that assigns probabilities to potential realizations of the radar channel. In this case, different realizations are characterized by different number and locations of targets present. The Bayesian channel representation can then be used to customize a transmit illumination pattern. The probabilistic representation is updated based on received measurements and Kalman-based prediction of the states of possible targets. Simulation results from a trial experiment of the closed-loop system are provided.