Computer Science ›› 2018, Vol. 45 ›› Issue (2): 114-120.doi: 10.11896/j.issn.1002-137X.2018.02.020

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Robotic Fish Tracking Method Based on Suboptimal Interval Kalman Filter

TONG Xiao-hong and TANG Chao   

  • Online:2018-02-15 Published:2018-11-13

Abstract: Research of autonomous underwater vehicle (AUV) focuses on tracking and positioning,precise guidance and return to dock,and so on.The robotic fish of AUV has become a hot application in intelligent education,civil and military and so on.From the nonlinear tracking analysis of robotic fish,it is found that the interval Calman filtering algorithm contains all possible filtering results,but the range is wide and relatively conservative,and the interval data vector is uncertain before implementation.This paper proposed a ptimization algorithm of suboptimal interval Kalman filtering.Suboptimal interval Kalman filtering scheme uses the inverse of interval matrix instead of its worst inverse,and it is more approximate to nonlinear state equation and measurement equation than the standard interval Kalman filter,increasing the accuracy of the nominal dynamic system model,and improving the speed and precision of tracking system.Monte-Carlo simulation results show that the optimal trajectory of suboptimal interval Kalman filtering algorithm is better than that of the interval Kalman filtering method and the standard filter method.

Key words: Autonomous underwater vehicle,Kalman filter,Suboptimal interval Kalman filter,Robotic fish tracking,Monte-Carlo simulation

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