A robust Kalman filter based on Gaussian-Exponential distribution for SINS/USBL integration navigation system

In order to meet the needs of high-precision navigation for underwater vehicles, a strapdown inertial navigation system (SINS)/ultra-short baseline (USBL) tightly coupled integrated strategy is proposed, which can avoid the errors generated in the calculation of absolute position and improve the positioning accuracy of the integrated navigation system compared with the loosely coupled strategy. In addition, due to the influence of environmental noise in the ocean, the measurement of USBL is accompanied by a large number of outliers, which leads to the decrease of the precision of the integrated navigation system based on traditional Kalman filter. Therefore, a robust filter based on Gaussian-Exponential distribution is presented for the SINS/USBL integrated navigation system in this paper. Finally, the feasibility and the superiority of the proposed algorithm is verified through simulation and field test in the Yangtze River.