Double-Stage Filtering Fusion Navigation Algorithm Based on Multisource Optimal Selection

作者：Fujun Song, Zeng Qing-hua, Rui Zhang, Zhu Xiaohu, Huan Zhou, Xiaoyu Ye · 发表于：IEEE Sensors Journal · 年份：2025 · DOI：10.1109/jsen.2025.3563215 · 被引用次数：6 · 研究领域：Advanced Algorithms and Applications、Advanced Sensor and Control Systems、Advanced Measurement and Detection Methods

To address the navigation accuracy issues of UAV formations arising from leader failures, environmental factors, and other elements, the paper presents the double-stage filtering fusion (DF) navigation algorithm based on multi-source optimal selection. Traditional cooperative navigation algorithms often overlook the influence of geometric relationships inherent in cooperative information, which can significantly impact estimation accuracy. In response to this oversight, we propose a multi-source optimal selection. Traditional cooperative navigation algorithms often overlook the influence of geometric relationships inherent in cooperative information, which can significantly impact estimation accuracy. In response to this oversight, we propose a multi-source optimal selection strategy founded on the posterior error matrix. This strategy identifies cooperative nodes characterized by optimal performance evaluation coefficients to aid in rectifying the estimated positions of malfunctioning UAVs. Furthermore, to address challenges related to external environmental disturbances and the relative states within formations, we have developed a double-stage filtering that incorporates both local and relative state estimators. The local state filter employs a hybrid time difference of arrival (TDOA) and direction of arrival (DOA) to propose a two-step weighted least squares (TSWLS) method that considers errors in observation station location. Subsequently, the relative state filter integ...