Extended target tracking under multitarget tracking framework for convex polytope shapes

被引:5
作者
Mannari, Prabhanjan [1 ]
Tharmarasa, Ratnasingham [1 ]
Kirubarajan, Thiagalingam [1 ]
机构
[1] McMaster Univ, Elect & Comp Engn Dept, Hamilton, ON, Canada
关键词
Extended target; Convex hull; Data association; Self-occlusion; FILTER; OBJECT;
D O I
10.1016/j.sigpro.2023.109321
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper discusses the problem of extended target tracking for a single 2D extended target with a convex polytopic shape and known dynamics. Extended targets are those that produce multiple measurements for a single frame. One of the major challenges in extended target tracking is the joint uncertainty in the shape and the kinematics of the target. Another challenge is the lack of visibility due to self-occlusion in targets with a finite extent (as opposed to zero extent for point targets). To address these challenges, we develop a framework for tracking single (or widely separated) extended targets. This framework is based on the existing point multitarget tracking framework by modeling different parts of an extended target as separate targets. An algorithm is developed using the proposed framework for tracking convex polytope-shaped targets. The proposed shape function consists only of the boundary of the target since the center may not be observable. The algorithm is capable of dynamically changing the number of parameters used to describe the shape as more parts of the target become visible over time. The performance of the algorithm is evaluated for various scenarios using root mean square error (RMSE) of velocity, center, and intersection over union (IoU) metrics. It is seen that the algorithm is able to handle the self-occlusion problem and estimate the whole target shape even when different parts of the target are visible at different frames, for various shapes, and for various conditions of measurement noise covariance and number of measurements. New faces are added to the shape estimate as more parts of the target become visible. The algorithm is able to conserve the parts of the target that were visible in the previous frames but are no longer visible.
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收藏
页数:18
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