Event-Triggered Particle Filter for State Estimation of Non-linear Stochastics Hybrid System with Missing Measurements

The precision of state estimation is subjected to correct state prediction for the multi-model system. Our proposed algorithm is able to detect the State transition govern by event detection for Non-linear Stochastics Hybrid system. In this paper, a novel algorithm based on particle filter for the non-linear stochastic hybrid system called Event Trigger Particle filter based on reallocation resample method (RRPF), which detect the state transition of Hybrid System to adapt itself for accurate state estimation is presented. Target Tracking benchmark test model of the non-linear system example is used to check the performance of the proposed algorithm. Simulated results show the competence of the proposed algorithm.