Efficient particle filter for jump Markov nonlinear systems

Abstract

An efficient particle filtering algorithm is presented for state estimation of jump Markov nonlinear systems. The standard particle filter can easily suffer from particle degeneracy around mode changes. The new algorithm allows the user to fully control the number of particles in a certain mode, without distorting or violating the Markov property. This property can be exploited to prevent the filter degenerating.