Aiming at the degeneracy problem of general particle filter

an improved unscented kalman filter algorithm was proposed.First

a new sampling strategy called minimal skew sampling was proposed. The proposed sampling strategy was used in the UKF algorithm by which a proposal distribution is generated and draws samples from it. By doing this

problems such as particle degeneracy problem which were caused by the general particle filter using transition prior density function as proposal distribution were solved. Secondly

a new resampling method which incorporated multinomial resampling and stratified resampling was proposed

which efficiently solved the degeneracy problem of particle filtering .Finally

a simulation example about a nonlinear time series was given. The theory analysis and simulation results demonstrate that the improved UPF algorithm improves stability and accuracy of filtering

and has a great improvement in operating efficiency.