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      Method for Multiple Targets Tracking in Cognitive Radar Based on Compressed Sensing

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          Abstract

          A multiple targets cognitive radar tracking method based on Compressed Sensing (CS) is proposed. In this method, the theory of CS is introduced to the case of cognitive radar tracking process in multiple targets scenario. The echo signal is sparsely expressed. The designs of sparse matrix and measurement matrix are accomplished by expressing the echo signal sparsely, and subsequently, the restruction of measurement signal under the down-sampling condition is realized. On the receiving end, after considering that the problems that traditional particle filter suffers from degeneracy, and require a large number of particles, the particle swarm optimization particle filter is used to track the targets. On the transmitting end, the Posterior Cramér-Rao Bounds (PCRB) of the tracking accuracy is deduced, and the radar waveform parameters are further cognitively designed using PCRB. Simulation results show that the proposed method can not only reduce the data quantity, but also provide a better tracking performance compared with traditional method.

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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 February 2016
          : 5
          : 1
          : 90-98
          Affiliations
          [1 ] Information and Navigation Institute, Air Force Engineering University
          Article
          26f77c44ff5a432fa20663b4eaf498ec
          10.12000/JR14107

          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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