A non-myopic, receding horizon control strategy for an AUV to track an underwater target in a bistatic sonar scenario

We investigate how to improve the autonomy of AUVs to operate effectively in a multistatic network for littoral surveillance. We present a novel algorithm to control the movement of an AUV towing a line array acting as a receiver node in the network. The proposed algorithm uses a non-myopic, receding horizon policy to control the AUV heading to minimize the expected target position estimation error of a tracking filter. Minimizing this error is typically of the utmost interest in target state estimation since it is one way of maintaining track. Methods to simplify the resulting decision tree are used together with a branch and bound technique to solve an optimization problem at each ping time with the low computational power available onboard AUVs. Results from COLLAB13 sea trials are reported and show both the feasibility of running the algorithm in real-time on an onboard computer and the benefits of using the proposed algorithm over conventional predefined paths. These results represent, to the best of our knowledge, the first successful demonstration at sea of a complex non-myopic algorithm running in real-time on AUVs in a realistic multistatic littoral surveillance scenario.