In order to solve particle degeneracy and simultaneously avoid sample impoverishment, we propose a new improved particle filter algorithm based on the unscented Kalman filter (UKF), optimized combination strategy, and the standard particle filter method. We use the UKF to generate the importance density function and solve all the problems caused by the traditional particle filters which use prior density function as the particle distribution. And then we employ the optimized combination scheme to ensure all useful information inherited, which can maintain particle diversity. Theoretical analysis and simulation results both show that the improved particle filter algorithm can solve particle degeneracy and avoid sample impoverishment, and it has higher filtering accuracy in state estimation.