Fifth-degree continuous-discrete cubature Kalman filter for radar

Abstract

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.