Optimized orthogonal transformed CKF and its application in initial alignment

Abstract The paper first analyzes the impact of nonlocal sampling problem on the high order estimation errors of sigma point filter. Then, we introduce that how TCKF reduces the impact of nonlocal sampling on filtering by introducing orthogonal matrices to sigma points generating framework, thus improving the estimation accuracy of high order terms. In order to further reduce the high order estimation errors of CKF, an orthogonal matrix cluster and PSO optimization algorithm are introduced in this paper. By minimizing the coefficients of the 4-th order terms of the Taylor series of state estimation, the optimized orthogonal matrix is obtained, and then the improved TCKF algorithm is proposed. The effectiveness of the algorithm isdemonstrated through simulation experiments and turntable initial alignment experiment. The method proposed in this paper has good generality for 2nd order and above sigma point filtering algorithm.