博碩士論文 109523020 詳細資訊




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姓名 張楷珉(KAI-MIN JHANG)  查詢紙本館藏   畢業系所 通訊工程學系
論文名稱 以NeighCoef演算法對FMCW chirp雷達訊號進行降雜訊
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摘要(中) 本論文使用了同致電子提供的超聲波頻率調變連續波雷達(Ultrasound FMCW radar)進行物體短距離的量測,硬體設備以及晶片還有數據都會在內容提及,接著以NeighCoef的方式將收集的訊號做雜訊的處理,本論文總共分五個部份。
本論文的第一部分會先做基本敘述,介紹關於研究的背景、研究動機以及論文大綱,第二部份會介紹關於FMCW chirp系統,包括系統介紹、訊號模擬、雷達介紹以及FMCW系統如何測量距離,本章節都有相關的介紹,第三部分介紹NeighCoef是什麼,此方法的理論背景以及此方法如何處理訊號已達到雜訊降低的目的,在本章節會有完整的公式敘述,第四部分進行模擬以及比較訊號前後差別,會附上各種不同的距離數據,從90cm到150cm每30cm為一個間隔,第五部分會做一個總結,裡面包括對模擬結果的討論以及還有什麼問題是未來需要克服以及還有什麼地方可以深入去研究。
摘要(英) This paper uses the Ultrasound FMCW radar provided by Tongzhi Electronics for short-distance measurement of objects. Hardware equipment, chips and data will be mentioned in the content, and then collected in the way of NeighCoef. This paper is divided into five parts in total.
The first part of this thesis will give a basic description, introduce the background of the research, research motivation and the outline of the thesis, the second part will introduce the FMCW chirp system, including system introduction, signal simulation, radar introduction and how the FMCW system measures distance, This chapter has related introductions. The third part introduces what NeighCoef is, the theoretical background of this method and how this method processes the signal to achieve the purpose of reducing noise. In this chapter, there will be a complete formula description, and the fourth part will simulate As well as comparing the difference before and after the signal, various distance data will be attached, from 90cm to 150cm every 30cm is an interval, the fifth part will make a summary, which includes a discussion of the simulation results and what problems still need to be overcome in the future and Where else can we dig deeper.
關鍵字(中) ★ 降雜訊
★ 雷達訊號
關鍵字(英) ★ FMCW
論文目次 摘要 - i -
Abstract - ii -
目錄 - iii -
圖目錄 - vi -
表目錄 - v -
第一章 緒論 - 1 -
1.1 研究背景與動機 - 1 -
1.2 研究目的 - 2 -
1.3 論文大綱 - 4 -
第二章 連續波調變 - 5 -
2.1 雷達分類 - 5 -
2.2 FMCW雷達系統 - 7 -
2.3 FMCW訊號模型 - 8 -
2.4 FMCW距離測量 - 10 –
2.5 Chirp訊號 - 12 –
第三章 即時功率分配演算法 - 14 –
3.1 理論背景 - 14 -
3.2 雜訊等級估計 - 14 -
3.3 時頻降雜訊 - 17 -
第四章 模擬結果與討論 - 20 -
第五章 結論 - 31 -
參考文獻 - 32 -
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[12] Rohling, H. Milestones in radar and the success story of automotive radar systems. 11-th INTERNATIONAL RADAR SYMPOSIUM, 2010, pp. 1–6.
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[14] Hasch, J.; Topak, E.; Schnabel, R.; Zwick, T.; Weigel, R.; Waldschmidt, C. Millimeter-Wave Technology for Automotive Radar Sensors in the 77 GHz Frequency Band. IEEE Transactions on Microwave Theory and Techniques, 2012, vol. 60, no. 3, pp. 845-860.
[15] Kukkala, V.K.; Tunnell, J.; Pasricha, S.; Bradley, T. Advanced Driver Assistance Systems: A Path Toward Autonomous Vehicles. IEEE Consumer Electronics Magazine, 2015, vol. 7, no. 5, pp. 18-25.
[16] Askari, R., Siahkoohi, H.R., 2008. Ground roll attenuation using the S and x-f-k transforms. Geophys. Prospect. 56, 105–114. http://dx.doi.org/10.1111/j.1365-2478.2007.00659.x.
[17] Astudillo, R.F., Orglmeister, R., 2013. ComputingMMSE estimates and residual uncertainty directly in the feature domain of ASR using STFT domain speech distortion models. IEEE Trans. Speech Audio Process. 21, 1023–1034.
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[21] 無人駕駛車益處, https://www.viatech.com/tw/2019/06/the-benefits-of-self-drivintw/#:~:text=%E5%8D%B3%E4%BD%BF%E6%B1%BD%E8%BB%8A%E4BB%8D%E7%84%B6%E4%BD%BF%E7%94%A8%E9%83%A8%E5%88%86,%E5%B0%8D%E7%92%B0%E5%A2%83%E6%9C%89%E7%9B%8A%E3%80%82
指導教授 林嘉慶 審核日期 2022-7-20
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