New version of continuous-discrete cubature Kalman filtering for nonlinear continuous-discrete systems

For nonlinear continuous-discrete systems, this paper elaborates a new accurate implementation of continuous-discrete cubature Kalman filter (CD-CKF). As the main contribution of this work, the new Kalman prediction stage begins by integrating the nonlinear continuous model for all the cubature sample vectors; the prior estimate state and covariance prediction are based on the weighted statistics of these integrated cubature sample vectors and the Gauss-Legendre approximation scheme. The new square root form CD-CKF is also derived and accurately implemented by combining with the modified variable stepsize NIRK. As the advantages of proposed approach, the complicated and error-prone processes of solving covariance differential equation or calculating derivatives are avoided, while the positive semi definiteness of prior error covariance are numerically guaranteed. Simulations of traffic control scenarios further confirm the new approach's superior filtering performance in both reliability and accuracy. (C) 2019 ISA. Published by Elsevier Ltd. All rights reserved.