The flow physics around the underwater target and its direct interaction with the flexible free surface are the important prerequisite to non-acoustic detection technology, such as Synthetic Aperture Radar (SAR), optical measurement methods or infrared detection. How the structure of wake pattern changes over frequency in the spectral domain is the objective that can promote the applications of these new approaches and it plays a crucial role in better understanding of the relationship between free surface disturbances and the motion state of the submerged body. The existing data of wave height from Computational Fluid Dynamics (CFD) is transferred to a series of discrete nodes with evenly spaced increments through the data interpolation. Based on a joint analysis of 2D Fast Fourier Transform (FFT) and the dispersion relation, the X-shaped representation of submerged body wakes are identified in the wavenumber space, together with the curves of the dispersion relation so as to validate the correctness of the computational procedures. Then a decomposition of the wake system is performed, including the contribution of the near-field Bernoulli hump and far-field Kelvin wave, these two components can be separately reconstructed in the spatial domain using the Inverse Fast Fourier Transform (IFFT). The distance between the first two maximum peaks of the Bernoulli hump is given and the relationship with the Froude number (Fn) is also discussed. Finally, the 1D-Power Spectral Density (PSD) is available to describe the frequency components and proportion of the components. The results lead to a further understanding of the roles of wake components and the motion state of underwater target.

水下目标周围的流动物理及其与柔性自由表面的直接相互作用是非声学探测技术的重要前提，例如合成孔径雷达（SAR）、光学测量方法或红外探测。尾迹模式的结构如何在频谱域中随频率变化是可以促进这些新方法应用的目标，它对于更好地理解自由表面扰动与浸没体运动状态之间的关系起着至关重要的作用。计算流体动力学 (CFD) 的现有波高数据通过数据插值被传输到一系列具有均匀间隔增量的离散节点。基于二维快速傅里叶变换（FFT）和色散关系的联合分析，在波数空间中识别出淹没体尾迹的X形表示，以及色散关系曲线，以验证计算程序的正确性。然后对尾流系统进行分解，包括近场伯努利驼峰和远场开尔文波的贡献，这两个分量可以使用快速傅里叶逆变换 (IFFT) 在空间域中分别重建。给出了伯努利驼峰的前两个最大峰之间的距离，并讨论了与弗劳德数 (Fn) 的关系。最后，一维功率谱密度 (PSD) 可用于描述频率分量和分量的比例。