PROJECT TITLE :

Particle filter for nonlinear systems with multiple step randomly delayed measurements

ABSTRACT:

A replacement particle filter for nonlinear systems with multiple step randomly delayed measurements is proposed. Within the proposed technique, particles and their weights are updated within the Bayesian estimation framework by considering the multiple step randomly delayed measurement model. Simulation results show that the proposed method has higher estimation accuracy than existing methods.


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