Cooperative positioning method for UAV swarm belief propagation based on improved sparrow search algorithm

被引：0
|
作者：
Xiong Z. [1 ,2 ]
Li X. [1 ]
Xiong J. [1 ]
Chen M. [1 ]
Liu J. [1 ,2 ]
机构：
[1] Navigation Research Center, College of Automation, Nanjing University of Aeronautics & Astronautics, Nanjing
[2] Key Laboratory of Navigation, Guidance and Health-Management Technologies of Advanced Aerocraft, Ministry of Industry and Information Technology, Nanjing
来源：
Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology | 2021年 / 29卷 / 02期
关键词：
Belief propagation; Cooperative position; Sparrow search algorithm; Unmanned aerial vehicle swarm;
D O I：
10.13695/j.cnki.12-1222/o3.2021.02.005
中图分类号：
学科分类号：
摘要：
To deal with the cooperative positioning problems of unmanned aerial vehicles (UAVs) swarm, a cooperative positioning method for UAVs swarm belief propagation based on improved sparrow search algorithm (SSA) optimization is proposed. According to the principle of belief propagation, the factor graph model of UAVs is constructed, and the posteriori probability distribution of each node is inferred by continuously updating the inference; the value of geometric dilution of precision (GDOP) is adopted as the fitness function, and the original SSA is improved by chaotic initialization and adaptive variation, which improves the local optimization and the fast convergence performance of the algorithm. Simulation results show that the improved SSA achieves optimality in convergence accuracy and speed, and significantly improves the localization accuracy of follower UAVs. In the cluster, the cumulative error distribution of the positioning error less than 0.5 m reaches 97.1%, which is higher than the original confidence propagation (81.9%). At the same time the computation is simplified, which is beneficial to the application of large-scale UAV swarm. © 2021, Editorial Department of Journal of Chinese Inertial Technology. All right reserved.
引用
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页码：171 / 177
页数：6
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