A fusing positioning algorithm for small maritime unmanned vehicle

Introduction The 5th generation (5G) mobile communication and Beidou navigation system (BDS) antennas of offshore small maritime unmanned vehicles (SMUV) are shaken by waves and winds in harsh sea conditions, resulting in poor stability in positioning trajectory tracking and varying degrees of impulse noise in pseudo-range measurements. Methods Therefore, A Kalman filter algorithm combining approximate message passing (AMP) and variational Bayesian (VB) is proposed under a fusion positioning model of 5G and BDS with a high update rate. The AMP algorithm can predict the instantaneous position movement caused by waves, and the VB algorithm smooths the pulse error of trajectory tracking caused by intermittent shielding. Results Experimental results demonstrate that, in 100 positioning epochs, when the impact of waves on SMUV is 20 times, 30 times and 40 times, the root mean square error of the proposed algorithm is 1.19 meter (m), 1.26 m and 1.27 m respectively. Compared with the adaptive variational Bayesian algorithm, the positioning accuracy is improved by 7.75%, 16.4% and 24.4%, which obviously enhances the stability of positioning. Discussion The proposed algorithm can achieve high-precision positioning and tracking, and the performance of the algorithm is better than that of the comparison scheme when the amplitude and frequency of the waves are greater.