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The big data processing of HF sky-wave radar sea echo for detection of sea moving targets

机译:HF天波雷达海回波的大数据处理,用于探测海移动目标

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摘要

A high-frequency (HF) sky-wave radar always monitoring large area of sea surface, for detecting sea surface moving objects, there must be big data waiting to be processed. A set of data processing methods were proposed, the successful implementation of HF sky-wave radar on the sea moving target detection. By setting the HF sky-wave radar parameters, after the initial data processing, the gotten HF sky-wave radar data were saved. Then a new HF sky-wave radar data processing method was provided, this method was the so-called three-step detection method (TSTM) which based on the constant false alarm rate (CFAR) technique. By using TSTM, setting the decision threshold G, with false alarms being ruled out, a moving target was detected out at last, its speed was calculated. The results also proved that TSTM could effectively reduce the sea clutter, and greatly lessen the echo-broadening and double-image caused by ionosphere contamination.
机译:高频(HF)天波雷达始终监视着大面积的海面,以检测海面移动的物体,必须有大数据等待处理。提出了一套数据处理方法,成功实现了HF天波雷达在海上运动目标的检测。通过设置高频天波雷达参数,对初始数据进行处理后,保存得到的高频天波雷达数据。然后提供了一种新的HF天波雷达数据处理方法,该方法是基于恒虚警率(CFAR)技术的所谓的三步检测法(TSTM)。通过使用TSTM,设置判定阈值G,排除错误警报,最后检测出移动目标,并计算其速度。结果还证明,TSTM可以有效减少海浪杂波,并大大减少电离层污染引起的回波展宽和双像。

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