Multiple Sets of High-Precision Inertial Navigation Information Fusion Strategy Based on Confidence Analysis

When there is no external measurement information, this paper designs a new multi-set high-precision inertial navigation information fusion strategy based on confidence analysis to solve the problem of lack of information fusion and effective co-location solutions among multiple sets of high-precision inertial navigation systems. With the help of a conventional inertial navigation system, according to the specific non-Gaussian characteristics of measurement noise, the Kalman filter based on maximum correlation entropy is selected, and a comprehensive error model is established with high-precision inertial navigation. Furthermore, the statistical characteristics of the system integrated speed error estimation and the quantitative law of the measurement accuracy after filter fusion are deduced. The confidence index and normalized confidence index of each high-precision system can be calculated according to the second-order center distance of the comprehensive speed error state, so as to realize the fusion of high-precision inertial navigation information based on confidence analysis and improve the navigation accuracy and reliability of the system.