An IMM-SRHCKF tracking algorithm with doppler information
Zhichao Xie, S. Wang, J. Yu · IET conference proceedings. · 2023
To improve the tracking accuracy of manoeuvring targets, this paper introduces the Doppler information and the square-root high-degree cubature Kalman filter (SRHCKF) into the interacting multiple model (IMM) algorithm, then proposes an IMM-D-SRHCKF algorithm. The algorithm uses Doppler measurements to achieve an improvement in tracking accuracy. At the same time, adaptive state transition probabilities and dimensionality reduction by rounding off zero-weighted cubature nodes are incorporated to increase computational efficiency. Experimental results show that the tracking error of the proposed algorithm is 79.13% and 78.32% lower than that of the IMM-UKF and IMM-CKF without Doppler information, respectively, and 41.35% and 27.41% lower than that of the IMM-D-UKF and IMM-D-CKF with Doppler information, respectively, and the proposed algorithm also have pretty robustness in different scenarios.