| Citation: | Baozhu LI, Jian GUAN, Yunlong DONG. Anti-bias Track Association Algorithm of Radar and Electronic Support Measurements Based on Track Vectors Detection[J]. Journal of Electronics & Information Technology, 2019, 41(1): 123-129. doi: 10.11999/JEIT180303
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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 detection is proposed according to the statistical characteristics of Gaussian random vectors. The state estimation decomposition equation is firstly derived in the Modified Polar Coordinates (MPC). The track vectors are obtained by the real state cancellation method. Second, In order to eliminate most non-homologous target tracks, the rough association is performed according to the features of the azimuthal rate and Inverse-Time-to-Go (ITG). Finally, the track-to-track association of radar and ESM is extracted based on track vectors chi-square distribution. The effectiveness of the proposed algorithm are verified by Monte Carlo simulation experiments in the presence of sensor biases, targets densities and detection probabilities.
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