A Robust Vector-Tracking Loop Based on KF and RTS Smoothing for Shipborne Navigation

Abstract

High-precision navigation systems are crucial for unmanned autonomous vessels. However, commonly used Global Navigation Satellite System (GNSS) signals are often severely affected by environmental obstruction, leading to reduced positioning accuracy or even the inability to locate. To address the issues caused by signal obstruction in high-precision navigation systems, the research presented in this paper proposes a vector-tracking loop (VTL) structure based on the forward Kalman Filter (KF) and the backward Rauch Tung Striebel (RTS) smoothing algorithm. The introduction of loop filters in the signal-tracking loop improves the tracking accuracy of the carrier and code, thereby enhancing the stability and robustness of the navigation system. The traditional scalar-tracking loop (STL), traditional VTL, and Kalman Filter (KF)-based VTL were compared through shipborne motion experiments, and the proposed method demonstrated superior signal-tracking capability and navigation accuracy. In the experiment, there were three blocking areas along the experimental path. The experimental results show that, when there are signal blockages of 12 s, 18 s, and 40 s, compared to the traditional VTL method, the proposed method can reduce the horizontal position error by 93.9%, 95.8%, and 94.5%, respectively, as well as the horizontal velocity error by 71.1%, 95.8%, and 97.6%, respectively.