Fifth‐degree continuous–discrete cubature Kalman filter for radar

In this study, the authors extend the high‐degree cubature Kalman filter to operate with continuous‐time non‐linear stochastic systems with discrete measurements. For this purpose, they utilise two known approximations to solve the stochastic differential equation used in the modelling of continuous‐time dynamics. The first approach is grounded in an ordinary differential equations solver. The second approach is based on the Itô–Taylor expansion of order 1.5. In addition, the errors presented in each approach were classified. Finally, the proposed filters were compared with the continuous–discrete cubature Kalman filter in a challenging radar‐tracking experiment. The results of the experiment show an improvement in the accuracy of the proposed method, and more importantly, a better performance of the filters based on the Itô–Taylor expansion.