Adaptive Radial Rule based Cubature Kalman Filter

In this paper, a new adaptive cubature Kalman filter (ACKF) is proposed to improve the performance of the conventional cubature Kalman filter. The ACKF uses a new cubature rule that combines the third-degree spherical rule with the higher degree radial rule along the directions of larger uncertainty. More accurate and robust results can be achieved with slightly more points than the conventional third-degree cubature Kalman filter (CKF). Compared with the fifth-degree CKF, ACKF uses much fewer points but maintains very close performance. A target tracking benchmark problem is used to demonstrate the enhanced performance of the proposed filter.