The application of AUV navigation based on cubature Kalman filter

Abstract

Precise positioning of AUV plays an important role in the efficient and reliable underwater operation. The extended Kalman filter (EKF) is the most commonly used method, because this algorithm is easy to implement. However, EKF is only effective for nonlinear systems with approximate linearity, then truncation error is introduced. When the initial state error is large or the system model has high nonlinearity, the estimation effect is poor and the convergence rate is slow. In order to overcome the shortcomings of the EKF, Ienkaran Arasaratnam and Simon Haykin put forward the cubature Kalman filter (CKF). Cubature Kalman filter (CKF) based on the third-degree spherical-radial cubature rule has been proposed and used in many applications, such as positioning, sensor data fusion, and attitude estimation [1]. A large number of experiments by the Swordfish-AUV system platform were carried out in Yantai Menlou reservoir. We analyze the experimental data and conclude that CKF algorithm is closer to the real trajectory than the EKF algorithm.