We describe the implementation of a novel nonmyopic, receding horizon strategy to control the movement of an AUV towing a line array acting as a receiver node in a multistatic network for littoral surveillance and Ant...
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ISBN:
(纸本)9781479949182
We describe the implementation of a novel nonmyopic, receding horizon strategy to control the movement of an AUV towing a line array acting as a receiver node in a multistatic network for littoral surveillance and Anti-Submarine Warfare (ASW). The algorithm computes the vehicle heading angles 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. The optimization solves a resulting decision tree taking into consideration a planning future horizon. In this paper, we focus on how to solve the different challenges related to the implementation of this kind of computational intensive algorithms on vehicles operating in realistic ASW scenarios and characterized by limited computational power. Specifically, we describe the multistatic network used in COLLAB13 experiments, how we simplify the solution of the resulting decision tree and the implementation of the algorithm in CMRE's software system running on AUVs and based on MOOS-IvP middleware. We conclude reporting results from COLLAB13 which demonstrate the feasibility to use the proposed algorithm in realistic operations onboard AUVs and its effectiveness over conventional predefined tracklines.
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