Anti-bias Track Association Algorithm of Radar and Electronic Support Measurements Based on Track Vectors Detection
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摘要:
针对雷达与电子支援设施(ESM)存在系统误差、上报目标不完全一致等复杂场景下目标航迹关联问题，该文基于高斯随机矢量统计特性，提出一种基于航迹矢量检测的雷达与ESM航迹抗差关联算法。首先在修正极坐标系(MPC)下推导目标状态估计分解方程，采用真实状态对消的方法得到航迹矢量，为剔除大部分非同源目标航迹，构建方位角变化率-距离变化率与距离比(ITG)统计量进行粗关联，然后采用基于航迹矢量
\begin{document}${\chi ^2}$\end{document} 检验的方法实现雷达与ESM的航迹关联。最后通过实验仿真验证了该文算法在不同系统误差、目标密度、检测概率等环境下的有效性。
Abstract: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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