Aiming at problem exists in conventional particle filtering algorithm of particle weight degradation and sampling particle impoverishment and it needs for a large number of particles to achieve accurate state estimation a firefly improved particle filtering algorithm based on chaotic is proposed.By using the ergodic and random initialization particle swarm of the chaotic system

the initial particle distribution is more uniform.At the same time

the optimization mechanism of the firefly algorithm is introduced into the conventional particle filtering algorithm

which can make the particles move to the high likelihood region

so as to improve the precision of the filtering.Using chaos search on the part of the weight of the excellent particle at the same time

and regenerate part of low weight particles

to achieve demand of diversity of improving population.Experiments show that this method is more accurate than the conventional particle filtering

especially in the case of small populations

and effectively improve the weight degeneracy and sample impoverishment problem.