在無線感知系統中，可以利用相關特性去偵測使用者的有無，但是若在高速環境下，則會影響到相關特性，進而降低偵測效能。若是可以在偵測前，先補償影響相關特性的參數後再行偵測，便可以增加偵測效能。本論文提出兩個特徵偵測器(feature detector, FD)，首先利用最大似然估計(maximum likelihood estimation, MLE)找出相關特性的時間偏移及系統的通道數，並補償正規頻率偏移(regular frequency offset, CFO)，利用概似比試驗(likelihood ratio test, LRT)設計偵測器，稱為原始偵測器(original detector, OD)。然後藉由最大似然估計的估測參數及原始偵測器，並再進一步利用相關特性的補數特性，估測並且補償都普勒頻率(Doppler frequency)所帶來的影響，同樣利用概似比試驗設計偵測器，稱為改良偵測器(modified detector, MD)。本論文所提偵測器相對於其他著作有較良好的偵測效能，並且能改善在高速環境下的偵測效能。

In wireless sensing system, correlation profile can be used to detect the user’s busy or idle, but if it is in high-speed scenes, the correlation profile will be affected, thereby reducing the detection performance. To improve the detection performance, the parameters that affect the correlation profile are compensated before the detection. In this study, we present two feature detectors (FD). Firstly, the maximum-likelihood estimation (MLE) is used to find the time offset of the correlation profile and the number of channels of the system, and the regular frequency offset (CFO) is compensated. We use likelihood-ratio test (LRT) to design a detector called original detector (OD). Then, by using the estimated parameters of maximum-likelihood estimation and original detector, and then further utilizing the complement property of the correlation profile, the Doppler frequency is estimated and compensated. We also use the maximum-likelihood estimation to design another detector called modified detector (MD). The detector proposed in this study has better detection performance than other works and can improve the detection performance in high-speed scenes.

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