Iterated Modified Gain Extended Kalman Filter with Applications to Bearings Only Tracking
Yuan Huang and Taek Lyul Song
Department of Electronic Systems Engineering, Hanyang University, Republic of Korea
Abstract—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.
Index Terms—surveillance, target tracking, nonlinear estimation, bearings only, iteration method
Cite: Yuan Huang and Taek Lyul Song, "Iterated Modified Gain Extended Kalman Filter with Applications to Bearings Only Tracking," Jounal of Automation and Control Engineering, Vol. 3, No. 6, pp. 475-479, December, 2015. doi: 10.12720/joace.3.6.475-479
Index Terms—surveillance, target tracking, nonlinear estimation, bearings only, iteration method
Cite: Yuan Huang and Taek Lyul Song, "Iterated Modified Gain Extended Kalman Filter with Applications to Bearings Only Tracking," Jounal of Automation and Control Engineering, Vol. 3, No. 6, pp. 475-479, December, 2015. doi: 10.12720/joace.3.6.475-479