A UKF-based Active Target Tracking Algorithm for High-speed Autonomous Underwater Vehicles
Chaohuan Hou · Jisuanji fangzhen · 2008
The problem of active tracking for a unitary target based on a platform of high-speed autonomous underwater vehicles(AUV),was researched.A robust Unscented Kalman Filter(UKF)based tracking algorithm was founded.In case of strong observation noises and long sampling intervals,it led to estimate for the state parameters,which were used to describe the target's movement real time.This filter was also compared with Extended Kalman Filter(EKF)for this application.Simulation results show that the EKF can lead to some accurate estimate for the target's speed values,meanwhile,the estimates for the target's distance values become divergent.Using the UKF,both of the speed and distance values can be estimated accurately.Moreover,the speed values can be estimated more accurately than using EKF.