Data Preprocessing and Kalman Filter Performance Improvement Method in Integrated Navigation Algorithm

Nowadays, the integrated navigation system is very important in all kinds of aircraft, and the integrated navigation algorithm is the core of the integrated navigation system. The main research in this paper are as follows: (1) Introduce three low-pass filters to filter out the high-frequency noise collected by sensors. Then compare and analyze the performance of these three low-pass filters. (2) Adjust the Kalman filter parameters to improve the performance of the Kalman filter. The final conclusions are: (1) Through comparative analysis of the three low-pass filters, Wiener low-pass filter is the most suitable, which can better achieve the purpose of filtering out high-frequency noise. (2) By adjusting the parameters in the Kalman filter, a set of approximate optimal parameters is obtained. This set of parameters verifies that the performance of the Kalman filter can be improved.