Maximum Correntropy Extend Kalman Filter for Multiple AUVs Cooperative Localization

Abstract

In general, the extended Kalman filter (EKF) performs well in Gaussian noise. However, when the system is disturbed by heavy-tailed noise, its performance may be greatly reduced. In this paper, a nonlinear robust filtering method is derived based on maximum correntropy criterion (MCC) to improve the accuracy of cooperative localization under the influence of heavy-tailed noise in complex underwater environments. By combining the advantages of EKF and MCC, the proposed filter has strong positioning accuracy and robustness. The simulation results show that it can effectively suppress the influence of heavy-tailed noise on the accuracy of cooperative localization.