A nonlinear and non-Guassian rank filter (RF) method based on the principle of rank filter was presented. Furthermore

its filter recursive process was also given. Unscented Kalman filter(UKF) only for Gaussian distribution and particle filter (PF) for non-Gaussian distribution were the two common nonlinear filter methods

but PF had the problems of particle degeneracy

particle impoverishment caused by resampling and complicated calculation. Compared with the two methods

the proposed RF is suitable for not only Gaussian distribution but also non-Gaussian distributions such as multivariate t distributions and extreme value distributions

and RF is simple to calculate and easy to apply in engineering. Moreover

it has low amount of calculation. From the simulation comparisons of RF

UKF and PF in the example

the filtering accuracy of RF increased at least 500%.