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研究生:李崧瑋
研究生(外文):Li, Song-Wei
論文名稱:無人機之雷達截面積模擬及其於雷達目標辨識之應用
論文名稱(外文):Simulation for Radar Cross Section of Drones and Its Application to Radar TargetRecognition
指導教授:李坤洲李坤洲引用關係
指導教授(外文):Lee, Kun-Chou
口試委員:王健仁卿文龍
口試日期:2023-07-31
學位類別:碩士
校院名稱:國立成功大學
系所名稱:系統及船舶機電工程學系
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2023
畢業學年度:111
語文別:中文
論文頁數:75
中文關鍵詞:目標辨識雷達截面積資料視覺化ORB演算法圖像特徵提取 SURF圖像增強
外文關鍵詞:Target recognitionRadar cross sectionData visualizationOriented FAST and Rotated BRIEFSpeeded-Up Robust FeaturesImage enhancement
相關次數:
  • 被引用被引用:0
  • 點閱點閱:88
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  • 收藏至我的研究室書目清單書目收藏:0
摘要 I
英文延伸摘要 II
致謝 V
目錄 VI
表目錄 VIII
圖目錄 IX
第一章 緒論 1
§ 1.1 研究動機與目的 1
§ 1.2 文獻回顧 2
§ 1.3 研究貢獻與論文架構 3
第二章 無人機之雷達截面積 5
§ 2.1 電磁散射理論 5
§ 2.1.1 散射截面積 5
§ 2.1.2 雷達截面積 6
§ 2.2 無人機雷達截面積模擬 7
§ 2.2.1 無人機及環境設置 7
§ 2.2.2 主要零件分析 8
§ 2.2.3 初步統計數據分析 8
§ 2.2.4 數據分析與結果 9
第三章 無人機RCS之目標辨識應用 27
§ 3.1 RCS資料處理過程 27
§ 3.2 ORB演算法 28
§ 3.2.1 Oriented FAST特徵點檢測 28
§ 3.2.2 Rotated BRIEF 特徵點描述與匹配 29
§ 3.2.3 漢明距離 31
§ 3.2.4 ORB演算法之分析與討論 31
§ 3.3 特徵提取SURF圖像重建和ORB演算法 31
§ 3.3.1 特徵提取SURF 31
§ 3.3.2 特徵提取SURF圖像重建和ORB演算法之分析與討論 33
§ 3.4 圖像增強和ORB演算法 33
§ 3.4.1 非局部均值降噪 34
§ 3.4.2 伽瑪校正 35
§ 3.4.3 圖像增強和ORB演算法之分析與討論 35
§ 3.5 餘弦距離 35
§ 3.5.1 餘弦距離之分析與討論 35
§ 3.6 各種圖像辨識方法比較 36
第四章 結論與未來展望 70
§ 4.1 結論 70
§ 4.2 未來展望 70
參考文獻 72
附錄 74
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[4]L. Wilkinson and M. Friendly, "The history of the cluster heat map," The American Statistician, vol. 63, no. 2, pp. 179-184, May 2009.
[5]Z. Zhang, L. Zhao, and T. Yang, "Research on the application of artificial intelligence in image recognition technology," in Journal of Physics: Conference Series, vol. 1992, no. 3: IOP Publishing, p. 032118, July 2021.
[6]I. Goodfellow, Y. Bengio, and A. Courville, Deep learning, Cambridge, MA, USA: MIT press, 2016.
[7]D. W. Hess, "Introduction to RCS measurements," in 2008 Loughborough Antennas and Propagation Conference, Loughborough, UK, pp. 37-44, March 2008.
[8]P. Rajyalakshmi and G. Raju, "Characteristics of radar cross section with different objects," International Journal of Electronics and Communication Engineering, vol. 4, no. 2, pp. 205-216, 2011.
[9]C. Sudhendra, A. Madhu, A. Pillai, G. Shekar, T. Rukmini, and K. Rao, "Design and implementation of a novel rasorber for aircraft stealth applications," in 2014 First International Conference on Computational Systems and Communications (ICCSC), Trivandrum, India, pp. 176-180, Dec 17-18, 2014.
[10]C. Durlu and H. T. Hayvaci, "Monostatic RCS analysis for armed and unarmed UAV," in 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, San Diego, CA, USA July 09-14, 2017.
[11]N. M. K. K. bin Yahya, N. E. Abd Rashid, N. A. Zakaria, Z. I. Khan, and K. K. M. Shariff, "Drone’s Radar Cross Section Computation for Various Reflected Angles using LTE frequency," in 2019 IEEE Asia-Pacific Conference on Applied Electromagnetics (APACE), Melacca, Malaysia, Nov 25-27, 2019.
[12]A. Krizhevsky, I. Sutskever, and G. E. Hinton, "Imagenet classification with deep convolutional neural networks," Advances in neural information processing systems, vol. 25, 2012.
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[14]A. Yousry, M. Taha, and M. M. Selim, "Currency Recognition System for Blind people using ORB Algorithm," Int. Arab. J. e Technol., vol. 5, no. 1, pp. 34-40, Jan 2018.
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[16]F. M. Kahnert, "Numerical methods in electromagnetic scattering theory," Journal of Quantitative Spectroscopy and Radiative Transfer, vol. 79, pp. 775-824, Sep 2003.
[17]Z. Chen and M. M. Ney, "Method of moments: A general framework for frequency-and time-domain numerical methods," in 2007 Workshop on Computational Electromagnetics in Time-Domain, Perugia, Italy, Oct 15-17, 2007.
[18]V. Semkin et al., "Analyzing radar cross section signatures of diverse drone models at mmWave frequencies," IEEE access, vol. 8, pp. 48958-48969, March 2020.
[19]E. Rublee, V. Rabaud, K. Konolige, and G. Bradski, "ORB: An efficient alternative to SIFT or SURF," in 2011 International conference on computer vision, Barcelona, Spain, Jan 06-13, 2011.
[20]D. G. Viswanathan, "Features from accelerated segment test (fast)," in Proceedings of the 10th workshop on image analysis for multimedia interactive services, London, UK, May 6-8, 2009.
[21]M. Calonder, V. Lepetit, C. Strecha, and P. Fua, "Brief: Binary robust independent elementary features," in Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, Sep 5-11, 2010.
[22]H. Bay, T. Tuytelaars, and L. Van Gool, "Surf: Speeded up robust features," in Computer Vision–ECCV 2006: 9th European Conference on Computer Vision, Graz, Austria, Graz, Austria, May 7-13 2006.
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[24]A. Buades, B. Coll, and J.-M. Morel, "Non-local means denoising," Image Processing On Line, vol. 1, pp. 208-212, 2011.
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