Sensor selection for multi-target tracking via closed form Cauchy-Schwarz divergence

In this paper, we present an novel sensor selection technique for multi-target tracking where the sensor selection criterion is the Cauchy-Schwarz divergence between the predicted and updated densities. The proposed approach is attractive in that the multi-target states are modeled as Poisson random finite sets (RFS) that allow the objective function to be calculated in closed form. Simulation results are presented to demonstrate the viability of the proposed approach.