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      Affinity Propagation Based Measurement Partition Algorithm for Multiple Extended Target Tracking

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          Abstract

          It is difficult to accurately and rapidly partition measurement sets of multiple extended targets in cluttered environment. Hence the affinity propagation method is introduced and a novel measurement partition algorithm is proposed. First, the measurement set is preprocessed by using density analysis to remove clutters from the measurements. Second, the number and location of the extended targets is determined via competition among the measurements. Finally, state estimates are obtained by using the probability hypothesis density filter. Simulations show that the proposed algorithm offers good performance in measurement partitioning of extended target tracking with clutter disturbance. Compared with the distance partition and K-means++ methods, the proposed method effectively minimizes the computation time and retrieves the number of targets iteratively.

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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 August 2015
          : 4
          : 4
          : 452-459
          Affiliations
          [1 ] School of Internet of Things Engineering, Jiangnan University
          Article
          5e12f37d353043ef8d76bcbd3ebb0413
          10.12000/JR15003

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          Categories
          Technology (General)
          T1-995

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