The Adaptive Federal Unscented Particle Filter Algorithm with Applications in All-Attitude Integrated BDS/INS Navigation System

Abstract

In order to improve the attitude accuracy, the thesis establishes the all-attitude integrated BDS/INS navigation nonlinear system model based on the position, velocity, attitude by adding the BDS’s attitude measurement information into the measurement equation of the traditional BDS/INS integrated navigation nonlinear system model. Considering the problem that the dynamic navigation system model is difficult to accurately describe the complex navigation environment, the thesis improves the dynamic characteristics of the information distribution of the federal filter algorithm which could timely change based on the eigenvalues ratio of each subsystem’s error variance matrix. Then, the adaptive federal unscented particle filter (AFUPF) is proposed. The simulation shows that the proposed algorithm could effectively weaken the impact on the system accuracy of the inaccurate high-dynamic model, and improve the adaptability, the fault tolerance and the accuracy, especially the attitude accuracy.

DOI: http://dx.doi.org/10.11591/telkomnika.v14i3.8069