A Genetic Algorithm-Based Optimization of Multi-Station Cooperative Localization Deployment


연구 분야: Infrastructure



학회: AIPR '24: Proceedings of the 2024 7th International Conference on Artificial Intelligence and Pattern Recognition


초록

To solve the nonlinearity issue in TDOA FDOA passive positioning, a multi-station cooperative positioning optimization approach based on GA is suggested. Using GA, the algorithm iteratively looks for the best deployment plan inside a given region. Its optimal deployment is based on the guiding idea of minimizing the GDOP value of the localized target space. It greatly improves the Multi-UAVs Passive Localization Dynamic Rapid Deployment Capability and dramatically lowers the positioning error of regional targets as compared to traditional positioning with a fixed number of UAVs.


Author Profile
Jie Yang

School of Communication and Information Engineering Xi'an University of Posts & Telecommunications Xi'an shaanxi China yangjie@xupt.edu.cn

Andorra
Author Profile
Lei Cao

School of Communication and Information Engineering Xi'an University of Posts & Telecommunications Xi'an shaanxi China caolei@stu.xupt.edu.cn

Andorra
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Jiale Wang

School of Communication and Information Engineering Xi'an University of Posts & Telecommunications Xi'an shaanxi China 3024229241@qq.com

Andorra

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발행 연도 2025년
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