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Abstract
To enhance the precision and reliability of integrated navigation systems, a novel fault-tolerant information fusion algorithm based on a federated filter is proposed. Decentralized filtering architecture is employed to fuse information from different navigation subsystems. The chi-square detection function and the filter innovation correlation are used as inputs to the fuzzy system, which then outputs the observation quality factor. The observation quality factor directly reflects the reliability of the measurement data and is utilized to adjust the local filter gain matrix online. Additionally, the information sharing coefficients, determined by the observation quality factors, ensure dependable fault isolation while improving the sensitivity of fault detection to gradual faults. Comparative experimental results demonstrate that the proposed method effectively detects various faults and significantly enhances the performance of the integrated navigation system during malfunctions.
Published Version
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