Iterated Modified Gain Extended Kalman Filter with Applications to Bearings Only Tracking

نویسندگان

  • Yuan Huang
  • Taek Lyul Song
چکیده

A nonlinear filter called the iterated modified gain extended Kalman filter (IMGEKF) is presented in this paper. This filter uses bearings only measurements to estimate the target state in passive target tracking scenario. This work combines the MGEKF and the iteration method. The filter utilizes the updated state to re-linearize the measurement equation. Then the proposed work is tested in a two dimensional scenario. The simulation study compares the IMGEKF and some other filters to show the improvement.

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تاریخ انتشار 2015