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Yiming Wang, Xingpeng Mao, Jie Zhang. Effective Sea Clutter Spectrum Extraction Method for HFSWR in Adverse Conditions[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2017, 26(3): 367-374. doi: 10.15918/j.jbit1004-0579.201726.0312
Citation: Yiming Wang, Xingpeng Mao, Jie Zhang. Effective Sea Clutter Spectrum Extraction Method for HFSWR in Adverse Conditions[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2017, 26(3): 367-374.doi:10.15918/j.jbit1004-0579.201726.0312
shu

Effective Sea Clutter Spectrum Extraction Method for HFSWR in Adverse Conditions

doi:10.15918/j.jbit1004-0579.201726.0312
  • 1.

    School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China;The First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China

  • 2.

    School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China

  • 3.

    The First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China

  • Received Date:2017-02-14
    Abstract
  • An effective approach in solving the sea clutter spectrum extraction problem is studied in the paper. Different from the conventional signal to noise ratio (SNR) method based on Doppler frequency or range domain information, a method is developed to characterize the differences between the sea echo and those interferences are by signal to interference plus noise ratio (SINR) which jointly utilizing the range, Doppler frequency and azimuth domain information. Furthermore, these differences can be adaptable to adverse conditions by forming the necessary boundaries and constraints in searching of the maximum SINR, which greatly promotes the extraction of sea clutter spectrum. The real high frequency surface wave radar (HFSWR) data demonstrate that the proposed method is less influenced by those interferences and can effectively extract the sea clutter spectrum even under the adverse conditions. Furthermore, it has been shown as an effective method for ship detection and sea state remote sensing of HFSWR.
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    • References (16)
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