Abstract
Notice of Violation of IEEE Publication Principles<br><br>"Extended Target Tracking Using an IMM Based Nonlinear Kalman Filters,"<br>by Yucheng Zhou, Jiahe Xu, Yuanwei Jing, Georgi M. Dimirovski<br>in the Proceedings of the 2010 American Control Conference, July 2010, pp. 6870-6875<br><br>After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.<br><br>This paper contains significant portions of original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.<br><br>Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:<br><br>"Extended Target Tracking Using an IMM based Rao-Blackwellised Unscented Kalman Filter,"<br>by Zhiwen Zhong; Huadong Meng; Xiqin Wang<br>in the Proceedings of the 9th International Conference on Signal Processing, October 2008, pp.2409-2412<br><br> <br/> The unscented Kalman filter (UKF) and ensemble Kalman filter (EnKF) are developed to extended target tracking problem for high resolution sensors. The nonlinear Kalman filters are based on an ellipsoidal model, which is proposed to exploit sensor measurement of target extent. The ellipsoidal model can provide extra information to enhance tracking accuracy, data association performance, and target identification. In contrast to the most commonly used extended Kalman filter (EKF), the UKF and EnKF provide more accurate and reliable estimation performance, due to the presence of high nonlinearity of the model. Correspondingly, the EnKF has lower computational complexity than the UKF. An interacting multiple model (IMM) technique is combined with the filters to adapt the target maneuver and motion mode switching problem which is vital for nonlinear filtering. The developed IMM-UKF and IMM-EnKF algorithms on extended target tracking problem are validated and evaluated by computer simulations.
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