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access icon free Non-myopic sensor scheduling for multistatic sonobuoy fields

© Crown copyright
Received 02/04/2017, Accepted 26/08/2017, Revised 25/07/2017, Published 08/09/2017

Sonobuoy fields, consisting of many distributed emitter and receiver sonar sensors on buoys, are used to seek and track underwater targets in a defined search area. The authors seek a scheduling protocol, selecting both the emitter and its waveform in each time interval that optimises tracking performance. This study describes a stationary scheduling algorithm for sonobuoy fields called the continuous probability states algorithm. The algorithm replaces a full partially observed Markov decision process by a computationally feasible Markov decision process by focusing on probability of target detection. This approach is shown to result in high-quality tracks for multiple targets in a realistic simulation of a sonobuoy field.

Inspec keywords: Markov processes; sonar; probability

Other keywords: nonmyopic sensor scheduling; multistatic sonobuoy fields; full partially observed Markov decision process; stationary scheduling algorithm; receiver sonar sensors; continuous probability states algorithm; target detection; distributed emitter

Subjects: Sonar and acoustic radar; Markov processes

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