Adaptive Kalman filtering for multi-constellation integrated navigation system

作者：Sun Yong Rong^*; Wu Ling; Zhao Wei; Liu Jian Ye

来源：Journal of Astronautics, 2009, 30(5): 1879-1884.

DOI：10.3873/j.issn.1000-1328.2009.05.022

• Adaptive federated Kalman filtering
• Adaptive filtering algorithms
• Adaptive Kalman filtering
• Adaptive Kalman filtering model
• Adjustment coefficient
• Current statistical model
• Error sources
• Federated filtering
• Filtering effects
• GALILEO system
• GLONASS
• Integrated navigation
• Integrated navigation systems
• Kalman-filtering
• Kinematic positioning
• Maneuvering targets
• Positioning accuracy
• Positioning precision
• Satellite navigation systems
• Simulation experiments
• Simulation result
• Subfilters
• Tracking performance
• Weighted factors

A multi-constellation integrated navigation adaptive federated Kalman filtering algorithm is put forward in this paper. Assuming a current statistical model for maneuvering targets and considering that errors caused by different error sources can be equivalent to a total error of positioning results from the receivers of each satellite navigation system, an adaptive Kalman filtering model in kinematic positioning is presented. In order to improve the performance of kinematic positioning filter, a modified adaptive filtering algorithm is proposed by means of introducing adjustment coefficient, weighted factor and adaptive regulating variable. Subfilters for GPS, GLONASS and GALILEO system are designed respectively; then data fusion processing is practiced on the subfilters by federated filtering algorithm; finally the simulation experiment is carried out on GPS/GLONASS/GALILEO multi-constellation integrated navigation system. The simulation results indicate that the tracking performance is enhanced, filtering effect is improved and positioning accuracy is increased.

• 出版日期2009
• 单位南京航空航天大学