Sensor scheduling for bearings-only tracking with a single sensor

Abstract

In this paper, two types of optimality criteria for scheduling a single passive sensor in bearings-only tracking are investigated. Firstly, we examine the case of optimising sensor trajectory under a classical control frame work where the optimality criteria are based on Fisher information matrix. A first order numerical algorithm is discussed. Secondly, the sensor scheduling problem is treated as a partially observed Markov decision process where information divergence criterion is ultilised as a reward function. A grid based search strategy is adopted to find feasible sensor courses which can maximise the reward between prior and posterior densities of target state. Technically, accumulate..