隨著無線通訊系統朝向高頻寬與高度整合發展，如何在既有通訊架構下延伸環境 感測功能，已成為通訊與感測整合(Joint Communication and Sensing， JCS)領域之重要研究方向。正交分頻多工(Orthogonal Frequency Division Multiplexing， OFDM)波形廣泛應用於現代無線通訊系統，於系統驗證與量測過程中所蒐集之接收端 IQ 資料，本質上包含完整之通道頻率響應資訊，除可評估通訊品質外，亦隱含多徑延遲與距離相關特徵，使既有通訊訊號具備延伸應用於雷達感測之潛力。 在各式 OFDM 雷達距離估計方法中，能量估計法(energy-based estimation)僅利用子載波能量分佈即可進行距離推估，具有不依賴精確相位同步、計算複雜度低且高度相容於既有通訊硬體等優勢。然而於實際量測環境中，射頻前端頻率響應、天線增益不一致與硬體非理想效應將造成子載波能量呈現低頻乘性趨勢失真，破壞理想週期性結構，導致距離估計結果產生顯著誤差與不穩定現象。 為解決上述問題，本研究從能量域訊號模型出發，將通道失真建模為乘性低頻包 絡(multiplicative energy envelope)，並提出一套基於二次多項式迴歸之趨勢建模與振幅等化方法(quadratic polynomial regression-based detrending and equalization)。透過最小平方準則估計子載波能量背景趨勢並進行等化補償，可有效移除低頻失真，同時保留距離相關之高頻週期特徵。距離估計階段則採用可分離式四參數弦波估計法，透過 Zero-crossing 初始化與可分離式非線性最小平方估計相位斜率，再由相位斜率換算目標的估計距離。 實測結果顯示，在 5.8GHz/160MHz、5.8GHz/320MHz、7.2GHz/160MHz、 7.2GHz/320MHz 四組頻帶與頻寬條件、1~15m 連續距離量測下，PA 預補償與二次多項式包絡補償同時啟用時，整體平均絕對誤差(MAE)分別為 0.088m、0.082m、0.172m與0.157m，顯著提升估計準確度與穩定性。上述成果驗證既有通訊量測設備在無額外硬體成本下即可延伸為近距離雷達感測平台，展現 OFDM 通訊與雷達硬體共用架構之實務應用可行性。;With the rapid evolution of wireless communication systems toward higher bandwidth and tighter integration， extending environmental sensing capabilities within existing communication infrastructures has become a key research topic in joint communication and sensing (JCS). Orthogonal Frequency Division Multiplexing (OFDM) waveforms are widely adopted in modern wireless standards， and the in-phase and quadrature (IQ) measurements collected at the receiver inherently contain complete channel frequency response (CFR) information. Beyond communication quality evaluation， such measurements also embed multipath delay and distance-related characteristics， enabling communication signals to be reused for radar sensing. Among various OFDM-based ranging techniques， energy-based estimation determines target distance directly from subcarrier energy distributions and offers advantages including low computational complexity， no requirement for precise phase synchronization， and high compatibility with existing communication hardware. However， in practical measurement environments， radio-frequency front-end responses， antenna gain mismatches， and hardware non-idealities introduce low-frequency multiplicative distortions across subcarriers. These distortions disrupt the ideal periodic energy structure and significantly degrade ranging accuracy and stability. To address this issue， this study models the channel distortion as a multiplicative low-frequency energy envelope and proposes a quadratic polynomial regression-based detrending and equalization approach. By estimating the background energy trend using a least-squares criterion and compensating the measured energy sequence accordingly， the proposed method effectively suppresses low-frequency distortions while preserving the high-frequency periodic features associated with target distance. The range estimation stage employs a Separable four-parameter sinusoidal estimation method， in which the phase slope is first initialized by zero-crossing analysis and then refined using separable nonlinear least squares. The target range is subsequently obtained from the estimated phase slope. Experimental results demonstrate that， under four frequency-band and bandwidth conditions (5.8GHz/160MHz， 5.8GHz/320MHz， 7.2GHz/160MHz， and 7.2GHz/320MHz) over a continuous 1-15m distance range， the mean absolute error (MAE) achieved with both PA precompensation and quadratic polynomial envelope compensation enabled is 0.088m， 0.082m， 0.172m， and 0.157m， respectively. This substantial improvement verifies that existing communication measurement platforms can be directly extended to short-range radar sensing without additional hardware cost， highlighting the practical feasibility of OFDM-based hardware sharing between communication and radar systems.
