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Track clustering based data association for sky-wave Over-the-horizon Radar

机译:基于跟踪聚类的天波超视距雷达数据关联

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The multipath propagation and low measurement precision in sky-wave Over-the-horizon Radar (OTHR) pose new challenges to data association. Aiming at the formation of ships, this paper presents a new method of data association. Firstly the plane measurement model is established, and the transformation between radar and ground coordinates is deduced according to the given ionospheres state, which leads to different propagation modes. Then measurements observed from radar are transformed to ground coordinates considering all possible propagation modes, and the transformed points in ground coordinates for each measurement are called hypothetic points. Max-min distance clustering method is adopted to divide these hypothetic points into multi-classes. The feasible classes are selected using the restriction of propagation modes, and the geometry center of clustering can be calculated by averaging the points of feasible class. Finally, the nearest neighbor method is used to associate the geometry centers of clustering among different scans and further find the correlation of measurements, propagation modes and targets. Simulation results indicate that the proposed algorithm can associate the tracks in the formation of ships effectively, and the influence of radar detection probability on the algorithm is also analyzed.
机译:天波超视距雷达(OTHR)中的多径传播和低测量精度对数据关联提出了新的挑战。针对舰艇编队,提出了一种新的数据关联方法。首先建立平面测量模型,并根据给定的电离层状态推导雷达与地面坐标之间的转换,从而导致不同的传播模式。然后,考虑所有可能的传播模式,将从雷达观测到的测量值转换为地面坐标,并且每次测量的地面坐标转换点称为假设点。采用最大-最小距离聚类方法将这些假设点分为多个类别。利用传播模式的限制来选择可行类,并且可以通过对可行类的点求平均来计算聚类的几何中心。最后,最近邻方法用于关联不同扫描之间的聚类的几何中心,并进一步找到测量值,传播模式和目标之间的相关性。仿真结果表明,该算法能有效地将航迹与舰艇编队联系起来,并分析了雷达探测概率对算法的影响。

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