Applications of Multi-height Sensors Data Fusion and Fault-tolerant Kalman Filter in Integrated Navigation System of UAV

This paper presents a scheme for integrated navigation systems with applications of multi-height sensors data fusion and fault-tolerant Kalman filter(FTKF). It can complete data fusion for multi-height sensors, detect faulty sensors online and conduct fault tolerance in real time. First, implement optimal data fusion of multi-height sensors by weighted method based on output error variance of every height sensor. Then, a fault-tolerant Kalman filter scheme is designed, including three sub-filters(GPS/barometric altimeter /radar altimeter) and a main Kalman filter. The FTKF can detect and isolate the faulty sensors by using fault detection based on method of residuals Chi-Square test and state Chi-Square test with two state vectors propagators. The comparative analysis of simulation results in case of radar altimeter fault shows that the proposed scheme may achieve the expected fault-tolerant performance in integrated navigation system of UAV.