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Data Fusion and Tracking in a Simulated Multiradar Air Command and Control System

机译:模拟多址空气指挥控制系统中的数据融合和跟踪

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Radars play a crucial role in military air operations. They allow the detection with great accuracy of aircrafts flying at long distances. The exploitation of radars within an air command and control (C2) operational center is made possible through the use of operational information systems. The process of detecting an aircraft’s position, direction and speed from radar measurements to identify possible threats lies in the field of data fusion and especially in tracking. The implementation and testing of tracking algorithms require realistic radar data, and especially data that correspond to extreme radar phenomena that might occur in air C2 data fusion systems. A simulation of a parameterizable multi radar network that lies under an air C2 system has been developed. After simulating radar data, several sensor data fusion algorithms have been implemented and applied, with aim to find a solution that best fits in the specific problem and the environment of study. Specifically, Kalman filters, gating, nearest neighbor, interactive multiple filter and joint probability data association (IMMJPDA) have been implemented and evaluated. The simulation of both aircraft and radar data allowed for the evaluation of the performance of these algorithms. The results showed that IMMJPDA is a solution that handles well radar tracking even in extreme simulated scenarios.
机译:雷达在军事空中行动中发挥着至关重要的作用。它们允许在长距离飞行的飞机精确度的检测。通过使用操作信息系统,可以使空气指令和控制(C2)操作中心内的雷达的开发。从雷达测量中检测飞机的位置,方向和速度来识别可能的威胁的过程在于数据融合领域,尤其是跟踪。跟踪算法的实现和测试需要现实的雷达数据,尤其是对应于可能在AIR C2数据融合系统中发生的极端雷达现象的数据。已经开发了在Air C2系统下进行的可参数化多雷达网络的模拟。在模拟雷达数据之后,已经实现了多个传感器数据融合算法并应用了,目的是找到最适合在特定问题和学习环境中的解决方案。具体地,已经实现和评估了卡尔曼滤波器,门控,最近邻,交互式多滤波器和联合概率数据关联(IMMJPDA)。模拟飞机和雷达数据允许评估这些算法的性能。结果表明,即使在极端模拟场景中,ImmjPDA也是一种解决方案,即使在极端模拟场景中也可以处理雷达跟踪。

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