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Real-Time Radar Data Fusion and Registration Systems for Single Integrated Air Picture

机译：单一集成航空影像的实时雷达数据融合和注册系统

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摘要

Real-time fusion of data collected from a variety of radars that acquire information from multiple perspectives and/or different frequencies, is being shown to provide a more accurate picture of the adversary threat cloud than any single radar or group of radars operating independently. This paper describes a cooperative multi-sensor approach in which multiple radars operate together in a non-interference limited manner, and where decision algorithms are applied to optimize the acquisition, tracking, and discrimination of moving targets with low false alarm rate. The approach is twofold: (ⅰ) measure and process radar returns in a shared manner for target feature extraction by exploiting frequency and spatial diversity; and (ⅱ) employ feature-aided track/fusion algorithms to detect, discriminate, and track real targets from the adversary noise cloud. The results of computer simulations are provided that demonstrate the advantages of this approach.
机译：从多种角度和/或不同频率获取信息的各种雷达收集到的数据的实时融合显示，与任何独立运行的雷达或雷达组相比，它可以提供更准确的敌方威胁云图。本文介绍了一种协作式多传感器方法，其中多个雷达以无干扰的方式一起运行，并应用决策算法来优化低误报率的移动目标的捕获，跟踪和识别。该方法是双重的：（ⅰ）以共享的方式测量和处理雷达回波，以通过利用频率和空间分集来提取目标特征； （ⅱ）采用特征辅助的跟踪/融合算法来检测，区分和跟踪来自敌方噪声云的真实目标。提供的计算机仿真结果证明了这种方法的优势。

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