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Citation: Baozhu LI, Lin ZHANG, Yunlong DONG, Jian GUAN. Anti-bias Track Association Algorithm of Radar and Electronic Support Measurements Based on Track Vectors Hierarchical Clustering[J]. Journal of Electronics and Information Technology, ;2019, 41(6): 1310-1316. doi: 10.11999/JEIT180714 shu

Anti-bias Track Association Algorithm of Radar and Electronic Support Measurements Based on Track Vectors Hierarchical Clustering

  • Corresponding author: Baozhu LI, libaozhu1324@163.com
  • Received Date: 2018-07-17
    Accepted Date: 2018-11-06
    Available Online: 2019-06-01

Figures(7)

  • To address track-to-track association problem of radar and Electronic Support Measurements (ESM) in the presence of sensor biases and different targets reported by different sensors, an anti-bias track-to-track association algorithm based on track vectors hierarchical clustering is proposed. Firstly, the equivalent measurement is derived in the Modified Polar Coordinates (MPC). Linear relationship between state estimates and real states, sensor biases, measurement errors are established based on the approximate expansion of the equivalent measurement. The track vectors are obtained by the real state cancellation method. The homologous tracks are extracted by the method of track vectors hierarchical clustering, according to the statistical characteristics of Gaussian random vectors. The effectiveness of the proposed algorithm is verified by Monte Carlo simulation experiments in the presence of sensor biases, targets densities and detection probabilities.
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