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驗證碼

基于高爐料線的RCS測量及SAR成像驗證

王晨露 陳先中 侯慶文 王正鵬

王晨露, 陳先中, 侯慶文, 王正鵬. 基于高爐料線的RCS測量及SAR成像驗證[J]. 工程科學學報, 2018, 40(8): 979-988. doi: 10.13374/j.issn2095-9389.2018.08.012
引用本文: 王晨露, 陳先中, 侯慶文, 王正鵬. 基于高爐料線的RCS測量及SAR成像驗證[J]. 工程科學學報, 2018, 40(8): 979-988. doi: 10.13374/j.issn2095-9389.2018.08.012
WANG Chen-lu, CHEN Xian-zhong, HOU Qing-wen, WANG Zheng-peng. RCS measurement and SAR imaging verification based on blast furnace stock line[J]. Chinese Journal of Engineering, 2018, 40(8): 979-988. doi: 10.13374/j.issn2095-9389.2018.08.012
Citation: WANG Chen-lu, CHEN Xian-zhong, HOU Qing-wen, WANG Zheng-peng. RCS measurement and SAR imaging verification based on blast furnace stock line[J]. Chinese Journal of Engineering, 2018, 40(8): 979-988. doi: 10.13374/j.issn2095-9389.2018.08.012

基于高爐料線的RCS測量及SAR成像驗證

doi: 10.13374/j.issn2095-9389.2018.08.012
基金項目: 

國家自然科學基金資助項目(61671054);北京市自然科學基金資助項目(4182038)

詳細信息
  • 中圖分類號: TN959.1

RCS measurement and SAR imaging verification based on blast furnace stock line

  • 摘要: 圍繞高爐雷達料面監測系統成像需求,針對高爐雷達測量目標的雷達橫截面積(radar cross section,RCS)展開應用研究,首次實現了微波暗室中高爐料線RCS的高精度自動化測量,為高爐雷達目標特性的深入研究奠定了硬件基礎.基于比較法測得10 GHz處的焦炭、燒結礦顆粒的RCS典型值分布以及高爐料線散射方向性圖,測量動態范圍為-10~15 dB.通過RCS測量和成像診斷等方法對工業現場布焦、布礦的雷達回波信號強度差別大等問題進行了探索和分析.模擬工業現場的焦炭、燒結礦等平臺加漏斗的料線形狀,對散裝物料進行了等比例縮小的實際擺放,對典型料線縮比模型進行了合成孔徑雷達(synthetic aperture radar,SAR)成像驗證,并深入分析了成像缺失和成像誤差原因,得知漏斗部分在低頻情況下成像效果不理想,需要提高測試頻段;利用標準球模擬料線分析成像誤差,方位向和距離向絕對誤差在1.2%和5.8%以內,暗室內方位向測量誤差不超過±0.01 m.

     

  • [2] Yang Y L, Yin Y X, Wunsch D, et al. Development of blast furnace burden distribution process modeling and control. ISIJ Int, 2017, 57(8):1350
    [3] Wei J D, Chen X Z, Wang Z P, et al. 3-dimension burden surface imaging system with T-shaped MIMO radar in the blast furnace. ISIJ Int, 2015, 55(3):592
    [4] Zankl D, Schuster S, Feger R, et al. BLASTDAR——a large radar sensor array system for blast furnace burden surface imaging. IEEE Sens J, 2015, 15(10):5893
    [5] Xu D, Li Z P, Chen X Z, et al. A dielectric-filled waveguide antenna element for 3D imaging radar in high temperature and excessive dust conditions. Sens, 2016, 16(8):1339
    [10] Wang H, Chen X Z, Hou Q W. SAR imaging algorithm for the burden surface in BF based on ωk algorithm//2016 12th World Congress on Intelligent Control and Automation (WCICA). Guilin, 2016:1436
    [11] Sheen D M, McMakin D L, Hall T E. Three-dimensional millimeter-wave imaging for concealed weapon detection. IEEE Trans Microwave Theory Tech, 2001, 49(9):1581
    [16] Mitra T. Modeling of Burden Distribution in the Blast Furnace [Dissertation]. Turku/Åbo:Åbo Akademi University, 2016
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  • 文章訪問數:  727
  • HTML全文瀏覽量:  195
  • PDF下載量:  19
  • 被引次數: 0
出版歷程
  • 收稿日期:  2017-08-23

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