A Novel Underwater SINS/USBL Dual-Responder Integrated Navigation Algorithm Considering Motion Effects

In order to address the impact of underwater vehicle motion effects and common errors in Ultra-short baseline (USBL) acoustic signals on positioning accuracy, this paper proposes a USBL rang correction model (RC) based on the Strapdown Inertial Navigation System (SINS). The model retains high-precision characteristics for a short period. By utilizing the high-precision navigation information provided by the SINS during the USBL transmission and reception processes, this model corrects the distance errors caused by underwater vehicle motion effects. Based on this, a novel USBL tightly integrated navigation model (DT) is proposed, which uses the differential distance method with two transponders to compensate for common errors in USBL acoustic signals. In addition, to effectively reduce the impact of underwater outliers on the positioning accuracy of integrated navigation, a chi-square detection assisted adaptive robust cubature Kalman filtering (ARCKF) algorithm is adopted to suppress outliers. Simulations and tests in the Yangtze River show that the proposed positioning model and algorithm achieve higher positioning accuracy compared to classical algorithms.