A Maximum Correntropy Divided Difference Filter for Cooperative Localization

This paper derives a new maximum correntropy divided difference filter (DDF) to address the heavy-tailed measurement noise induced by non-Gaussian measurements in cooperative localization of autonomous underwater vehicles. By integrating the advantages of both the DDF and the maximum correntropy criterion, the proposed filter exhibits localization accuracy and robustness to address the heavy-tailed impulsive noise. The proposed maximum correntropy DDF has been tested through a lake trial. Experimental results indicate the superior performance of the proposed algorithm.