A Cascaded kalman filter model-aided inertial navigation system for underwater vehicle

Abstract

This paper reports the development of a low cost model aided inertial navigation system for an underwater vehicle. The inertial navigation is a combination of a complementary indirect Kalman filter for attitude estimation and another extended Kalman filter for the fusion of the dynamic model and the inertial measurement unit's output. It is shown that the fusion of an attitude and heading reference system (AHRS) with a model aided inertial navigation system (INS) can improve the accuracy of the navigation. This approach can improve the underwater navigation capabilities when no other aiding sensors are present.