Application of genetic algorithm based on bi-level selection for passive positioning deployment optimization

Yan Rong; Peng Li; Gaogao Liu; Yaodong Zhao; Bin Wu

doi:10.1117/12.2659654

30 November 2022 Application of genetic algorithm based on bi-level selection for passive positioning deployment optimization

Yan Rong, Peng Li, Gaogao Liu, Yaodong Zhao, Bin Wu

Author Affiliations +

Proceedings Volume 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022); 1245603 (2022) https://doi.org/10.1117/12.2659654
Event: International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 2022, Qingdao, China

Abstract

Passive positioning systems play an essential role in the field of electronic countermeasures. Many factors affect the efficiency of passive positioning systems, especially the deployment of its observatories station. In this paper, the genetic algorithm based on bi-level selection is proposed to solve the deployment optimization problem of the time difference of arrival for a passive positioning system in three-dimensional space. In this paper, three sets of comparison experiments are set up to determine the superiority of the proposed algorithm. The experimental results show that the improved genetic algorithm can be well applied to the deployment of three-dimensional time difference of arrival positioning, and the proposed bi-level selection operation is clarified which has a great effect on promoting the convergence of the algorithm.

Citation Download Citation

Yan Rong, Peng Li, Gaogao Liu, Yaodong Zhao, and Bin Wu "Application of genetic algorithm based on bi-level selection for passive positioning deployment optimization", Proc. SPIE 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 1245603 (30 November 2022); https://doi.org/10.1117/12.2659654

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