OSPA-based sensor control

This paper presents a new sensor control method for multi-object filtering, that is designed based on maximizing a measure of confidence in state estimation accuracy. Confidence of estimation is quantified by measuring the dispersion of the multi-object posterior about its statistical mean using Optimal Sub-Pattern Assignment (OSPA). The proposed method is generic and the presented algorithm can be used with common statistical filters. Implementation of the algorithm in conjunction with a labeled multi-Bernoulli filter is presented. Simulation studies demonstrate that the proposed method works in a challenging sensor control for multi-target tracking scenario.