Research on Height Enhancement Algorithms for Combined Navigation Systems
YANG Shu
WANG Yihua
Abstract：Aiming at the problems existing in the height measurement of barometric altimeter and GPS,a data fusion algo-rithm of barometric altimeter/gps combined system is proposed.By establishing the measurement model of the combined system,the data of the combined system are fused based on maximum likelihood estimation,and according to the principle of Kalman filter,a constant Kalman gain filtering algorithm is obtained.At the same time,the changes of sea level pressure and temperature are con-sidered,by adding adaptive weights to change the Kalman gain,the observation results of the combined system can be corrected.The results show that the adaptive Kalman filtering algorithm has an error standard deviation of 7.53 m for constant sea level pres-sure and temperature and 13.24 m for varying sea level pressure and temperature,which significantly improves the altitude estima-tion accuracy in the case of incorrect barometric altimeter measurements and ensures the altitude safety of the aircraft during flight.
Keywords：barometric altimeterGPSdata fusionmaximum likelihood estimationadaptive Kalman filter
Publication Date：2025-04-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 1015-1019,1090 )