Iterated extended Kalman auxiliary particle filter and analysis of algorithm' performance
Yanhui Xi, Hui Peng · Journal of systems engineering · 2012
In this paper,an improved filter procedure,named the iterated extended Kalman auxiliary particle filter(APF-IEKF),is proposed.The proposed algorithm consists of an auxiliary particle filter that uses an iterated extended Kalman filter to generate the importance proposal distribution.The simulation results show that the new procedure improves the distribution of the weights in the case of accurate measurement,which mitigates the effects of particle degeneracy problem.The experimental results also illustrate that the improved particle filter is superior to the existing filters and that it has less running time than the unscented Kalman particle filter(PF-UKF).Additionally,the performance of these algorithms is compared and some reasons of performance improving of each algorithm are analyzed.