A new sampling method in particle filter based on Pearson correlation coefficient

Particle filters have been proven to be very effective for nonlinear/non-Gaussian systems. However, the great disadvantage of a particle filter is its particle degeneracy and sample impoverishment. An improved particle filter based on Pearson correlation coefficient (PPC) is proposed to reduce the disadvantage. The PPC is adopted to determine whether the particles are close to the true states. By resampling the particles in the prediction step, the new PF performs better than generic PF. Finally, some simulations are carried out to illustrate the effectiveness of the proposed filter.