Abstract
Aiming to the problem of filtering divergence easily caused by large error of initial state estimation, an accurate initial state estimation approach based on analytic derivation and Levenberg-Marquardt algorithm is presented, which can improve the accuracy of initial state estimation under low accuracy of target parameters measurement. In order to reduce the computation of filtering process and speed up the filtering convergence rate, the combination of accurate initial state estimation and extended Kalman filter (EKF) algorithm is implemented, therefore, a precise 3D target tracking in forward scattering radar (FSR) could be achieved. Through comparative analysis of simulation results, the validity of proposed accurate tracking method is verified.
Original language | English |
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Pages (from-to) | 942-948 |
Number of pages | 7 |
Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
Volume | 32 |
Issue number | 9 |
Publication status | Published - Sept 2012 |
Keywords
- 3D target tracking
- Extended Kalman filter (EKF)
- Filter algorithm
- Forward scattering radar
- Initial state estimation