The paper deals with the particle filter in state estimation of a discrete-time nonlinear nongaussian system. The aim of the paper is to design a sample size adaptation technique to guarantee an estimate quality. The proposed sample size adaptation technique considers an unadapted particle filter with a fixed number of samples that would be drawn directly from the filtering probability density function and modifies the sample size of the adapted particle filter to keep the particle filters estimate quality identical. The adaptation technique is based on the effective sample size and utilizes the sampling probability density function and an implicit form of the filtering probability density function. Application of the particle filter with the sample size adaptation technique is illustrated in a numerical example.
