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The Big Data Processing of HF Sky-Wave Radar Sea Echo for Detection of Sea Moving Targets

Author

Listed:
  • Qianzhao Lei

    (School of Physics and Optoelectronic Engineering, Xidian University, Xi'an, China & School of Mathematics & Physics, Weinan Normal University, Weinan, China)

  • Zhensen Wu

    (School of Physics and Optoelectronic Engineering, Xidian University, Xi'an, China)

  • Lixin Guo

    (School of Physics and Optoelectronic Engineering, Xidian University, Xi'an, China)

  • Junmei Fan

    (Chinese Research Institute of Radiowave Propagation, National Key Laboratory of Electromagnetic Environment, Qingdao, China)

  • Senlin Geng

    (School of Mathematics & Physics, Weinan Normal University, Weinan, China)

Abstract

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.

Suggested Citation

  • Qianzhao Lei & Zhensen Wu & Lixin Guo & Junmei Fan & Senlin Geng, 2017. "The Big Data Processing of HF Sky-Wave Radar Sea Echo for Detection of Sea Moving Targets," International Journal of Information Technology and Web Engineering (IJITWE), IGI Global, vol. 12(4), pages 56-71, October.
    • Handle: RePEc:igg:jitwe0:v:12:y:2017:i:4:p:56-71
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