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Journal of System Simulation

Abstract

Abstract: To address the lack of research on the optimal path of mobile search platform to search for moving targets, this paper proposes a path optimization method of mobile search platform based on cumulative search probability theory. Based on the cumulative detection probability (CDP), one of the important criteria of sensor performance evaluation, a single-peak CDP calculation formula is constructed by using a time series correlation model, namely the (λ, σ) process model. A set of target motion scenarios are constructed, and the trajectory probability of target scenarios and their CDP at different time are corrected by Bayesian posterior probability. Considering the maximum CDP at the completion of the search and the shortest time for CDP to reach the target level as multi-objectives, a path optimization model for sonar searching moving targets is constructed to realize efficient search in continuous time and continuous space, and the optimal solution is provided by utilizing the multiobjective genetic algorithm. Through comparison with CDP results in random search mode, it can be found that the optimization method proposed in this paper can obtain a higher CDP, and the search scheme obtained has better efficiency advantages than that obtained from single-objective optimization.

First Page

2674

Last Page

2683

CLC

TP391.9

Recommended Citation

Wei Xiang, Liu Xingxuan, Fu Dianzheng, et al. Platform Path Optimization Method Based on Cumulative Detection Probability of Sonar Search[J]. Journal of System Simulation, 2024, 36(11): 2674-2683.

Corresponding Author

Liu Xingxuan

DOI

10.16182/j.issn1004731x.joss.23-0953

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