使用都卜勒雷達系統進行非接觸式生命體徵檢測，以往研究大多使用長週期時間窗口來保證頻譜上使用峰值搜索方法能夠準確估計生理訊號，當使用小於5秒的時間窗口時，會有頻譜解析度不足的問題，使準確度顯著下降。因此為了解決解析度的問題，本論文提出了一套訊號處理流程，首先以快速傅立葉轉換的方法對短窗口原始訊號進行振幅、頻率的估計，接著透過縮小估計範圍並將短窗口原始訊號不斷對估計訊號做時域扣除，直至殘餘能量滿足所設定之閥值。結果顯示無論是在雜訊存在或頻率非常接近的情況下，皆能夠成功解析出接近參考訊號的結果，展現出良好的性能。在實際的感測實驗中，請兩位受測者坐於雷達前以非常接近之頻率進行短時間的都卜勒運動，同樣能成功分離出接近實際數值的結果。從結果上顯示出本論文所提出的訊號處理方法計算出來的頻率誤差大約都能維持在5%以下，準確度皆有著不錯的表現。然而，這個算法仍然存在著配對性問題，可能無法準確地將解析出的結果與原始訊號進行配對。此外，運算時間會隨著感測都卜勒數量的提高而隨之增加，這些問題需要在使用算法時進行考慮和解決，以確保算法在實際應用中的效能和效率。

Using Doppler radar systems for non-contact physiological sensing, previous studies have mostly utilized long-period time windows to ensure accurate estimation of physiological signals using peak search methods on the spectrum. However, when using time windows shorter than 5 seconds, there is an issue with insufficient spectral resolution, leading to a significant decrease in accuracy. To address the resolution problem, this paper proposes a signal processing procedure. First, the short-window raw signal is processed using fast Fourier transform to estimate amplitude and frequency. Then, by iteratively subtracting the estimated signal from the short-window raw signal within a narrowed estimation range and continuing until the residual energy meets the set threshold. Results demonstrate that whether in the presence of noise or situations with very close frequencies, the proposed method successfully resolves results close to reference signals, showcasing good performance.In practical sensing experiments, two subjects were seated in front of the radar, performing short-duration Doppler movements at very close frequencies. The method was able to successfully separate results close to actual values. Results show that the frequency error calculated using the signal processing approach proposed in this paper is approximately maintained below 5%, with consistent accuracy. However, the algorithm still faces matching issues and may not accurately match the resolved results with the original signal. Additionally, computation time increases with the number of sensed Doppler frequencies, requiring consideration and resolution when using the algorithm to ensure its effectiveness and efficiency in real-world applications.

論文審定書 i
誌謝 ii
摘要 iii
Abstract iv
目錄 v
圖次 vii
表次 x
第一章序論 1
1.1研究背景與動機 1
1.2雷達演進及系統介紹 2
1.2.1連續波雷達 4
1.2.2自我注入鎖定雷達 5
1.3演算法回顧 7
1.3.1餘弦轉換 8
1.3.2頻率估計演算法 10
第二章演算法文獻回顧及模擬 12
2.1基礎訊號處理概論 12
2.2頻率估計演算法與快速傅立葉比較 15
2.2.1窗長度分析 19
第三章演算法介紹與驗證 22
3.1演算法介紹 22
3.2兩都卜勒頻率分離驗證 25
3.2.1可分離頻率極限 27
3.2.2可分離雜訊極限 30
3.2.3初始相位問題 32
3.2.4單一都卜勒頻率分離驗證 35
3.2.5蒙地卡羅方法 37
第四章系統架構與感測實驗 40
4.1相位正交自我注入鎖定雷達 40
4.1.1 直流校正與生理訊號提取 42
4.2 雷達系統設置 43
4.3 致動器感測實驗 44
4.4 人體感測實驗 51
第五章 結論 56
參考文獻 57

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