基于分数阶傅里叶变换的Chirp浅剖精细探测方法

实现弱回波信号检测和高信噪比(SNR)浅剖图像获取是浅剖精细探测的首要任务。该文在分析分数阶傅里叶变换(FrFT)解卷积原理，推导时间量纲化变换公式的基础上，提出一种基于FrFT的浅剖精细探测新方法。该方法通过FrFT解卷积实现分数阶傅里叶域(u域)沉积层冲激响应求解，采用u域加窗滤波技术对带内噪声进行有效抑制，经时间量纲化变换实现高信噪比u域沉积层冲激响应包络信号至时域浅剖包迹的直接变换，得到高质量的浅剖图像。仿真实验和实测数据处理验证了算法的精细探测能力，算法性能优于脉冲压缩和自回归(AR)预测滤波方法。

Chirp Sub-bottom Profiling Detailed Detection Method Based on Fractional Fourier Transform

Weak signal detection and high SNR seismic image generation are primary tasks in detailed sub-bottom profile detection. After analyzing the principle of deconvolution based on Fractional Fourier Transform (FrFT) and deriving the formula of time dimensional transformation, a new detailed sub-bottom profile detection algorithm based on FrFT is proposed. The fractional Fourier domain (u domain) sub-bottom impulse response is achieved by u domain deconvolution and the intraband SNR is increased by u domain windowed filtering technique, then high SNR envelop of u domain sediment impulse response envelop is transformed to time domain by time dimensional transformation to get high quality sub-bottom profile. Simulation and experimental data processing validate the validity of the algorithm in intraband denoising and detailed detection, and its performance is better than pulse compression and AutoRegressive (AR) forecast filtering.