Sequential Multi-model Unscented Kalman Filter for Shipborne High Frequency Surface Wave Radar

Shipborne high frequency surface wave radar (HFSWR) is a development of HFSWR, which install the transmitting and receiving equipment on the ship. In tracking problem, existing shipborne HFSWR are typically centered on the shipborne platform for detection and transferred to a coordinate system with a fixed origin. Therefore, the accuracy of the measurement on the shipborne platform is critical. However, in practice, it is a challenge to determine the accuracy of shipborne platform information measurements, which can lead to a reduction in the accuracy oftarget condition estimates. In this paper, we propose a sequential multi-model unscented Kalman filter (SMUKF) to address the uncertainty in the measurement of the shipborne platform. The SMUKF can get thejoint state estimation of shipborne platforms and targets. By applying multi-model method and using a more accurate filter value in the traceless Kalman filter, the SMUKF fuses the multi-model output to mitigate the impact of measurement errors on the target state estimation accuracy. The simulation results demonstrate that the proposed SMUKF outperforms the unscented Kalman filter (UKF) in terms of state estimation accuracy, and is more suitable for shipborne HFSWR.