適用於車用偵測系統之高性能 FMCW 雷達研究

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劉芷妍(Chih-Yen Liu) 查詢紙本館藏

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通訊工程學系

論文名稱

適用於車用偵測系統之高性能 FMCW 雷達研究
(Effective FMCW Radar in Automotive Detection System)

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摘要(中)

近年來，隨著自動駕駛越來越興盛，在汽車中可以找到各種感測器，像是聲納、影像、光達和雷達系統。這些感測器可以用來輔助駕駛，精確測量汽車前方、旁邊或後方物體的距離和相對速度，使駕駛在能見度差時或物體隱藏在盲點時，能得知物體的位置。如果感測器不能準確探測到目標，就會對駕駛員的安全構成嚴重威脅。相較於其他感測器，雷達具有不易受環境影響、量測距離長且精準的優勢。在汽車雷達中，調頻連續波（FMCW）雷達被廣泛使用，因為與脈衝雷達相比，其可降低訊號處理的硬體複雜度。然而實務上存在由干擾效應和反射損耗等引起的系統誤差，且這些誤差有可能被誤認為是所需訊號。如何有效的抑制雜訊以及如何準確判斷物體位置將是本篇論文探討的重點，首先考慮了線性回歸的方法將雜訊與訊號區隔並利用深層神經網路將物體定位。

摘要(英)

With self-driving automobiles becoming more and more popular in recent years, various sensors could be found in cars such as Sonar, Vision, Lidar, and Radar Systems. These sensors are used to assist drivers. Exact measurement of distance and relative velocity of objects in front, besides, or behind the car allow the driver to perceive objects during bad visibility or objects hidden in the blind spot. If sensors do not accurately detect targets, it can pose a serious threat to driver’s safety. Compared with other sensors, radar has the advantages of not being easily affected by the environment, and being capable of measuring longer distances precisely. For automotive radar systems, Frequency Modulation Continuous Wave (FMCW) radar is generally utilized because the complexity of hardware in the signal processing part can be reduced, compared to that of pulse radar. However, there are interference effects, reflection loss and some system errors in the practical application, which could be mistaken for desired signals. How to reduce the noise and accurately position the object will be the focus of this paper. First, the linear regression method is used to distinguish the noise and the signal, and the deep neural network is used to locate the object.

關鍵字(中)

★ FMCW 雷達
★ 車用感測器
★ 自動駕駛

關鍵字(英)

★ FMCW Radar
★ Automotive Detection
★ self-driving automobiles

論文目次

中文摘要 ………………………………………………………………………. i
英文摘要 ………………………………………………………………………. ii
目錄 ……………………………………………………………………………. iii
圖目錄 …………………………………………………………………………. iv
表目錄 …………………………………………………………………………. vi
第一章緒論 …………………………………………………………………... 1
1.1 研究動機 ………………………………………………………………. 1
1.2 研究背景 ………………………………………………………………. 3
1.3 論文架構 ………………………………………………………………. 5
第二章 FMCW雷達系統 …………………………………………………….. 6
2.1 雷達基本原理 …………………………………………………………. 6
2.2 雷達分類 ………………………………………………………………. 6
2.3 FMCW訊號處理 ……………………………………………………... 8
2.4 FMCW基頻訊號頻譜 ………………………………………………... 11
第三章定位與雜訊分析演算法 ……………………………………………... 13
3.1 線性迴歸 ………………………………………………………………. 13
3.2 深度神經網路 …………………………………………………………. 17
第四章模擬結果與討論 ……………………………………………………... 23
4.1 量測 ……………………………………………………………………. 23
4.2 線性迴歸模擬 …………………………………………………………. 30
4.3 深度神經網路模擬 ……………………………………………………. 31
第五章結論與未來展望 ……………………………………………………... 34
參考文獻 ………………………………………………………………………. 35

參考文獻

參考文獻

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指導教授

林嘉慶(Jia-Chin Lin)

審核日期

2022-7-19

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