可观测性
协方差交集
协方差
计算机科学
航程(航空)
协方差矩阵的估计
估计员
惯性测量装置
实时计算
人工智能
控制理论(社会学)
协方差矩阵
算法
工程类
数学
控制(管理)
航空航天工程
统计
应用数学
作者
Chunyu Li,Jianan Wang,Junhui Liu,Jiayuan Shan
出处
期刊:IEEE Transactions on Aerospace and Electronic Systems
[Institute of Electrical and Electronics Engineers]
日期:2023-07-21
卷期号:59 (6): 7851-7865
被引量:5
标识
DOI:10.1109/taes.2023.3297555
摘要
In this article, the cooperative navigation issue is investigated for a group of unmanned aerial vehicles (UAVs). A distributed estimation architecture fusing range, visual, and intermittent position measurements is proposed. Relative range and co-observed features are utilized to construct direct and indirect geometric constraints between UAVs, respectively. Compared with its independent counterpart, the proposed collaborative estimation scheme is more accurate and robust, while maintaining scalability and efficiency in practical deployment. To solve the intractable problem of evaluating the cross covariance between local estimators during estimation, the covariance intersection (CI) algorithm is introduced into the distributed fusion scheme, where each UAV only estimates its own pose and covariance. Observability analysis is provided to gain insights about the system's identification properties. Finally, the algorithm is applied to a practical patrolling scenario of multiple UAVs, and both numerical and software-in-the-loop (SITL) simulations are performed to illustrate the feasibility and effectiveness of the proposed scheme.
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