Tracking UUV based on interacting multiple model unscented particle filter with multi-sensor information fusion

Abstract For complexity and variability of obtaining UUV (Unmanned underwater vehicle) underwater movement information by acoustic sensors in underwater environment, a novel Least Square Interacting Multiple Model Unscented Particle Filter (LSIMMUPF) algorithms based Multi-sensor information fusion is proposed to solve the problem of tracking UUV. In order to realize the information fusion of Pitching Angle and Azimuth Angle from sensors, Least Square (LS) is used to pretreat the angles measurement; Moreover, the Interacting Multiple Model Unscented Particle Filter was combined the advantages of automatically adjusting filter bandwidth of Interacting Multiple Model and processing nonlinear non-Gaussian of Particle Filter to process the information pretreated, and the UKF was adopted to generate the important density function and the residual resampling was used to alleviate particle degradation phenomenon. Finally, to verify the performance of the proposed algorithm, a typical simulation is performed. Simulation results show that the proposed algorithm has good accuracy performance, which can satisfy the requirements for UUV.