The Performance Study of Positioning and Tracking in Dynamic Model
In the process of maneuvering target tracking, there has the phenomenon of non-linear and linear model estimation. In order to deal with this problem, this paper studies the dynamic positioning and tracking algorithm based on EKF (Extended Kalman Filter), which adopts Singer model in y direction and Uniform motion model in x direction. The simulation results show that positioning result has a precision of 15 m, the EKF method can be used effectively to restrain errors and get high precision.
KeywordsGlobal positioning system Positioning tracking error Kinematic model Extended kalman filter
This work was supported by Science and Technology Project of Chongqing Municipal Education Commission under Grant KJ130528, and Nature Science Foundation of Yunnan Province Education Department under Grant 2013Y017 about “the research of optimized satellite selection algorithm based on maximum determinant in positioning system”, and Nature Science Foundation of Qujing Normal College under Grant 2012QN022 & 2012QN023 about “the research of satellite selection algorithm in global positioning system”.
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