浅海海床发育着不同尺度的活动性砂体，在大型活动性砂体上常叠加发育着大量小尺度沙波(纹)，分析这些小尺度沙波(纹)有助于揭示活动性砂体的成因机制。但它们的尺度较小，常规分析方法往往将其作为高频噪声滤除，难以对该尺度海底沙波(纹)进行分离量化研究。为了解决这个问题，本文设计并实现了一种基于小波分析的小尺度海底沙波地形分解方法，并以台湾浅滩典型区域的高精度近底原位观测数据为例，实现了小尺度海底沙波地形的分解和定量分析，分解出背景地形、小型沙波和沙波纹(波长小于0.6 m)3种地貌类型。本文提出的小尺度海底沙波地形分解量化方法，可广泛应用于浅海高活动性地貌发育演化和海底边界层沉积动力过程研究，对评估海洋工程的稳定性也具有一定的实用价值。

The seafloor is characterised by active sand bodies of different scales, and  a large number of small-scale sand waves (ripples) is often superimposed on the large active sand bodies. The analysis of the small-scale sand waves (ripples) can reveal the genetic mechanism of these active sand bodies. However, their scales are small, and conventional analysis methods often filter them out as high-frequency noise, making it difficult to separate and quantify sand waves on the seafloor at this scale. To address this problem, a method was designed and implemented for decomposing small-scale submarine sand wave topography based on wavelet analysis, and achieved the decomposition and quantitative analysis of small-scale submarine sand wave topography: background topography, small sand waves and sand ripples (wavelength less than 0.6 m) by using high-precision bottommoored in situ observation data from a typical area of the Taiwan Banks. A quantitative method for decomposition of small-scale submarine sandwave topography was proposed, which can be widely applied to the study of the development and evolution of highly active landforms in shallow seas and the sediment dynamics of submarine boundary layer, and also has practical value for assessing the stability of marine engineering.