Existing researches focused on improving the Kalman Filter’s performance under non-Gaussian noise. The Maximum Correntropy Criterion (MCC) has good effect in evaluating non-Gaussian noise.

Applies this understanding to enhancing the robustness of the filter and to extend to applications including prediction and smoothing. Shows how to implement a target-tracking application in Octave ...

Kalman filters have long stood as a cornerstone in the field of target tracking and state estimation, providing an optimally recursive solution for estimating the state of dynamic systems in the ...

Vold and Leuridan [1] introduced in 1993 an algorithm for high resolution, slew rate independent order tracking based on the concepts of Kalman filters [5, 6]. The algorithm has been highly successful ...