Research on Particle Filter in Submarine Target Tracking

In view of the complex and changeable underwater environment submarine faces, and the noise it receives may not be Gaussian noise. In this paper, particle filter (PF) for nonlinear and non-Gaussian systems is studied. But the biggest problem we face when using PF is particle degradation. In order to solve the influence of particle degradation problem on the tracking and positioning accuracy of submarine targets on enemy ships, improved particle filtering algorithms, namely extended Kalman particle filtering algorithm (EPF) and untraced Kalman particle filtering algorithm (UPF), are also studied in this paper. Under the same initial conditions, the three filtering algorithms are simulated. The simulation results show that UPF algorithm has the best filtering effect in submarine tracking and positioning of enemy ship targets.