DocumentCode :
1807663
Title :
Extended object tracking based on support functions and extended Gaussian images
Author :
Lifan Sun ; Li, X. Rong ; Jian Lan
Author_Institution :
Center for Inf. Eng. Sci. Res. (CIESR), Xi´an Jiaotong Univ., Xi´an, China
fYear :
2013
fDate :
9-12 July 2013
Firstpage :
1526
Lastpage :
1533
Abstract :
This paper considers tracking of extended objects using down-range and cross-range extent measurements. For extended objects in radar or sonar tracking, existing elliptical modeling and rectangular modeling usually assume that the major axis of the object is parallel to its velocity vector. However, this may not be true in many practical applications. In view of this, we attempt to solve this problem by proposing two modeling approaches based on support functions and extended Gaussian images, respectively. The two approaches differ mainly in shape parametric representation for different objects and can be easily integrated into the extended object tracking framework which enables estimation of the kinematic state and object extension jointly. The effectiveness of the proposed modeling and estimation is illustrated by simulation results.
Keywords :
Gaussian processes; image representation; object tracking; state estimation; cross-range extent measurements; down-range extent measurements; elliptical modeling; extended Gaussian images; extended object tracking; kinematic state estimation; object extension; radar tracking; rectangular modeling; shape parametric representation; sonar tracking; support functions; velocity vector; Kinematics; Object tracking; Radar tracking; Sensors; Shape; Target tracking; Vectors; Extended object tracking; Hausdorff distance; down-range and crossrange extent; extended Gaussian image; support functions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion (FUSION), 2013 16th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-605-86311-1-3
Type :
conf
Filename :
6641183
Link To Document :
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