一种基于可观测性的多源融合自适应滤波结构构建方法
By establishing an observable multi-source fusion adaptive filtering structure in the spacecraft autonomous navigation system, eliminating fault data and selecting the optimal measurement channel, the problems of large computational load and poor robustness are solved, and efficient multi-source fusion autonomous navigation is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING INST OF SPACECRAFT SYST ENG
- Filing Date
- 2023-05-31
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies in spacecraft multi-source fusion autonomous navigation systems suffer from problems such as high computational load, difficulty in data interconnection, and poor robustness. In particular, they cannot achieve efficient autonomous navigation when dealing with multiple measurement sensors and complex environments.
An observability-based multi-source fusion adaptive filtering structure is adopted. By establishing state equations and observation equations, fault data is removed using threshold preprocessing, the observability of the sensor is calculated, and the optimal measurement channel is adaptively selected. State estimation is then performed in conjunction with a Kalman filter.
It improves the state estimation accuracy of the spacecraft autonomous navigation system, overcomes the constraints of environmental uncertainty and resource limitations, reduces the computational burden, and enhances the system's adaptability and reliability.
Smart Images
Figure CN116819510B_ABST