A Fine Resampling algorithm for general particle filters

Resampling algorithm for particle filters aimed at solving particle degeneracy problem but causing sample impoverishment. To maintain the diversity of the particle system and thus enhance the accuracy of state estimation in the nonlinear/non-Gaussian models, the paper proposed an improved resampling algorithm for general particle filters, called as PF-FR (Particle Filters with Fine Resampling). By introducing distance-comparing process and generating new particle based on optimized combination scheme, PF-FR algorithm overcomes the defects of general resampling algorithm. Simulations prove that the proposed PF-FR algorithm can effectively avoid sample impoverishment and simultaneously solve the degeneracy problem, thereby improving the estimation accuracy evidently. As a consequence, PF-FR algorithm is an effective alternative to resampling algorithm.