TY - GEN
T1 - Tracking of elliptical extended object with unknown but fixed lengths of axes
AU - Li, Mingkai
AU - Lan, Jian
AU - Li, X. Rong
N1 - Publisher Copyright:
© 2020 International Society of Information Fusion (ISIF).
PY - 2020/7
Y1 - 2020/7
N2 - This paper studies tracking of an elliptical extended object with unknown but fixed lengths of major and minor axes. In most practical applications (e.g., tracking vehicles or aircraft carriers), the size of the extended object is time invariant, while the orientation and kinematics may change over time. In order to describe this problem accurately and improve tracking performance, we handle the problem by modeling the kinematics and orientation information as a state vector, and estimate it in a Bayesian framework. We model the unknown but fixed lengths of axes of the object as non-random parameters, and estimate them using maximum likelihood estimation (MLE). To evaluate the proposed approach, simulation results of an extended target tracking scenario are presented, which illustrate that the proposed modeling and estimation is effective.
AB - This paper studies tracking of an elliptical extended object with unknown but fixed lengths of major and minor axes. In most practical applications (e.g., tracking vehicles or aircraft carriers), the size of the extended object is time invariant, while the orientation and kinematics may change over time. In order to describe this problem accurately and improve tracking performance, we handle the problem by modeling the kinematics and orientation information as a state vector, and estimate it in a Bayesian framework. We model the unknown but fixed lengths of axes of the object as non-random parameters, and estimate them using maximum likelihood estimation (MLE). To evaluate the proposed approach, simulation results of an extended target tracking scenario are presented, which illustrate that the proposed modeling and estimation is effective.
UR - https://www.scopus.com/pages/publications/85092708919
U2 - 10.23919/FUSION45008.2020.9190367
DO - 10.23919/FUSION45008.2020.9190367
M3 - 会议稿件
AN - SCOPUS:85092708919
T3 - Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020
BT - Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd International Conference on Information Fusion, FUSION 2020
Y2 - 6 July 2020 through 9 July 2020
ER -