Embedded Vehicle Dynamics Aiding for USBL/INS Underwater Navigation System

This brief presents an embedded vehicle dynamics (VD) aiding technique to enhance position, velocity, and attitude error estimation in low-cost inertial navigation systems (INSs), with application to underwater vehicles. The model of the VD provides motion information that is complementary to the INS and, consequently, the fusion of both systems allows for a comprehensive improvement of the overall navigation system performance. In this brief, the specific VD equations of motion are directly embedded in an extended Kalman filter, as opposed to classical external vehicle models that act as secondary INSs. A tightly-coupled inverted ultrashort baseline is also adopted to enhance position and attitude estimation using measurements of relative position of a transponder located in the vehicle mission area. The improvement of the overall navigation system is assessed in simulation using a nonlinear model of the INFANTE autonomous underwater vehicle, resorting to extensive Monte Carlo runs that implement perturbed versions of the nominal dynamics. The results show that the vehicle dynamics produce relevant performance enhancements, and that the accuracy of the system is robust to modeling uncertainties.