Comparison of suboptimal strategies for optimal own-ship maneuvers in bearings-only tracking

Suboptimal optimization techniques for computing observer trajectories in the bearings-only tracking problem, are considered. It is well known that the observer motion can aid in the quality of track performance, The aim is to obtain tight bounds on the location and velocity of this target through own ship maneuvers. The authors (1997), derived two mutual information measures and optimal trajectories were computed via dynamic programming. The memory requirements and the computational burden for computing optimal observer paths via dynamic programming is prohibitive. Thus, suboptimal strategies are explored here which considerably reduce the computational cost. The optimization methods are divided into two groups. In the first group a scalar function of the target state error covariance matrix is minimized, while in the second group approximate forward-reduced complexity-dynamic programming techniques are used. Simulation studies are carried out that compare the suboptimal optimization methods proposed in this paper