An Efficient Positioning and Tracking Algorithm for AUV in Underwater Environment

Xiaohong Tong ； Chao Tang

《淡江理工學刊》 21卷1期 (2018/03) Pp. 77-87

https://doi.org/10.6180/jase.201803_21(1).0010

摘要

Autonomous underwater vehicle (AUV) research has focused on tracking, positioning, precise guidance, return to dock, and other tasks. The AUV called a robotic fish has become a hot research topic in several areas, including for intelligent education, civil and military uses. In the nonlinear tracking analysis of the robotic fish, it was found that the interval Kalman filtering algorithm contains all possible filtered results but that the range is wide and relatively conservative, and the interval data vector is uncertain. This paper proposes an optimized algorithm for suboptimal interval Kalman filtering. The suboptimal interval Kalman filtering scheme uses the interval inverse matrix with its lowest inverse. This proposed method provides a more approximate nonlinear state equation and measurement equation than does the standard interval Kalman filtering, increases the accuracy of the nominal dynamic system model, and improves the speed and precision of the tracking system. Monte-Carlo simulation results show that the optimal trajectory of the suboptimal interval Kalman filtering algorithm is better than that of both the interval Kalman filtering method and the standard filtering method.

關鍵字

AUV ； Kalman Filtering ； Suboptimal Interval Kalman Filtering ； Robotic Fish Tracking ； Monte-Carlo Simulation