Considering the problem of poor tracking accuracy and particle degradation in the standard particle filter algorithm, a new improved extend kalman particle filter algorithm based on markov chain monte carlo(MCMC) is discussed. The algorithm uses the Extended Kalman filter to generate the proposal distribution that can integrate with the current observation and introduces MCMC technique after the resampling step to figure out the problem of sample impoverishment, so it can obtain a relatively

more »

... d tracking performance by using fewer particles. Meanwhile, the algorithm is optimized by MCMC sampling method, which makes the particles more diverse. The simulation results show that the improved extend kalman particle filter algorithm based on MCMC solves particle degradation effectively and improves tracking accuracy.