从雷达动目标信号变换实现相参积累的角度出发，选取 4种典型的相参积累方法：短时傅里叶变换 (STFT)、维格纳-威利分布 (WVD)、平滑伪维格纳 -威利分布 (SPWVD)及分数阶傅里叶变换(FRFT)，并将其应用于雷达动目标检测。重点研究了采样频率、脉冲数、输入信噪比 (SNR)对相参积累性能以及动目标检测性能的影响。结果表明， FRFT运算速度相对较慢但适用范围最广，尤其在处理噪声背景较强的信号时，能够有效抑制噪声，且参数估计精确度较高，具有良好的时频聚集性，为雷达相参积累检测的工程化应用提供理论支撑。

Four typical coherent integration methods are selected and applied to radar moving target detection according to the transformation of radar moving target signal to realize coherent integration, which are Short Time Fourier Transform(STFT), Wigner-Ville Distribution(WVD), Smoothed Pseudo Wigner-Ville Distribution(SPWVD) and Fractional Fourier Transform(FRFT). The effects of sampling frequency, pulse number, input Signal-to-Noise Ratio(SNR) on coherent integration performance and moving target detection performance are emphatically studied. The result shows that the FRFT is relatively slow but has a wider application range, and it can effectively suppress noise when dealing with signals with strong background noise. It has high parameter estimation accuracy and good time-frequency clustering, which provides theoretical support for engineering application of radar coherent integration detection.