Scheduling of Multistatic Sonobuoy Fields Using Multi-Objective Optimization

Gilliam, C, Angley, D, Suvorova, S, Ristic, B, Moran, B, Fletcher, F, Gaetjens, H and Simakov, S 2018, 'Scheduling of Multistatic Sonobuoy Fields Using Multi-Objective Optimization', in Proceedings of the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018), Calgary, Canada, 15-20 April 2018, pp. 3206-3210.


Document type: Conference Paper
Collection: Conference Papers

Title Scheduling of Multistatic Sonobuoy Fields Using Multi-Objective Optimization
Author(s) Gilliam, C
Angley, D
Suvorova, S
Ristic, B
Moran, B
Fletcher, F
Gaetjens, H
Simakov, S
Year 2018
Conference name ICASSP 2018: Signal Processing and Artificial Intelligence: Changing the World
Conference location Calgary, Canada
Conference dates 15-20 April 2018
Proceedings title Proceedings of the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018)
Publisher IEEE
Place of publication United States
Start page 3206
End page 3210
Total pages 5
Abstract Sonobuoy fields, comprising a network of transmitters and receivers, are commonly deployed to find and track underwater targets. For a given environment and sonobuoy field layout, the performance of such a field depends on the scheduling, that is, deciding which source should transmit, and which from a library of available waveforms should be transmitted at any given time. In this paper, we propose a novel scheduling framework based on multi-objective optimization. Specifically, we pose the two tasks of the sonobuoy field-tracking and searching-as separate, competing, objective functions. Using this framework, we propose a characterization of scheduling based on Pareto optimality. This characterization describes the trade-off between the search-track objectives and is demonstrated on realistic multistatic sonobuoy simulations.
Subjects Signal Processing
Keyword(s) Multi-static sonar
Sensor scheduling
Multiobjective optimization
Target tracking
Pareto optimality
DOI - identifier 10.1109/ICASSP.2018.8462152
Copyright notice © 2018 IEEE
ISBN 9781538646588
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