Spatial size of sample set control-based multiresolutional particle filter

When the multiresolutional analysis method is applied to reduce the number of particles in particle filter, it may cause the drop of filtering accuracy. Aiming at this problem, a size control-based multiresolutional particle filter is proposed. The method predicts the possible enlarging of error by observing the quasi-measurement error probability density, and then increases the size of sample set when the filtering is becoming unsteady by quasi-Monte Carlo sampling or multiplying the original particle set to avoid the possible divergence. The simulation results show that the algorithm maintains the estimation performance of particle filter, meantime also reduces the number of particles and improves the computation efficiency.