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Joint tracking and classification of extended targets with complex shapes

Frontiers of Information Technology & Electronic Engineering 2021年第6期22卷 839-861页

作者： Liping WANG Ronghui ZHAN Yuan HUANG Jun ZHANG Zhaowen ZHUANG National Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense TechnologyChangsha 410073China

This paper addresses the problem of joint tracking and classification(JTC) of a single extended target with a complex shape. To describe this complex shape, the spatial extent state is first modeled by star-convex shape via a random hypersurface model(RHM), and then used as feature information for target classification. The target state is modeled by two vectors to alleviate the influence of the high-dimensional state space and the severely nonlinear observation model on target state estimation, while the Euclidean distance metric of the normalized Fourier descriptors is applied to obtain the analytical solution of the updated class probability. Consequently, the resulting method is called the "JTC-RHM method." Besides, the proposed JTC-RHM is integrated into a Bernoulli filter framework to solve the JTC of a single extended target in the presence of detection uncertainty and clutter, resulting in a JTC-RHM-Ber filter. Specifically, the recursive expressions of this filter are derived. Simulations indicate that:(1) the proposed JTC-RHM method can classify the targets with complex shapes and similar sizes more correctly, compared with the JTC method based on the random matrix model,(2) the proposed method performs better in target state estimation than the star-convex RHM based extended target tracking method,(3) the proposed JTC-RHM-Ber filter has a promising performance in state detection and estimation, and can achieve target classification correctly.

关键词： Extended target Fourier descriptors Joint tracking and classification random hypersurface model Bernoulli filter

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A multi-group target tracking algorithm based on probabilistic multi-hypothesis tracking

A multi-group target tracking algorithm based on probabilist...

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第43届中国控制会议

作者： Hongwei Yang Zhongjian Sun Guoqing Qi Yinya Li Andong Sheng School of Automation Nanjing University of Science and Technology ZHIYUAN RESEARCH INSTITUTE

Aiming at the problem of tracking multi-group target with joint estimation of their motion state and shape,a multi-group target tracking algorithm based on probabilistic multi-hypothesis tracking(PMHT) and random hypersurface model(RHM) is *** algorithm views the group target as a whole,models the extended shape of the group target with RHM,and then uses PMHT to estimate the state of the group target with the maximum a posteriori *** algorithm addresses the challenge of accurately associating measurements with the group target and provides precise estimation of the complex shape of the group ***,it verifies the effectiveness of the algorithm through simulation experiments.

关键词： target tracking multi-group target probabilistic multi-hypothesis tracking random hypersurface model

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