Many applications of engineering require the state estimation of the real-time systems. The real-time dynamic systems are normally modeled as discrete time state space equations. The behaviors of the state space equations of many of the dynamic systems are nonlinear and non-Gaussian. Particle filter is one of the methods used for the analysis of these dynamic systems. In this review paper, many modified variants of particle filter algorithms and its application to different dynamic systems are discussed. State vector estimation using modified variants of particle filter was discussed and compared with the other standard algorithms.
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P. Sudheesh and Jayakumar, M., “Nonlinear Signal Processing Applications of Variants of Particle Filter: A Survey”, Lecture Notes in Electrical Engineering(accepted for publication), vol. 521, pp. 91-97, 2017.