The era of intelligence has arrived. Intelligent multimodal information is essential for underwater engineering. Sound is an indispensable medium in underwater multi-modal information technology. Orthogonal frequency division multiplexing underwater acoustic communication technology can achieve high bit rate communication. However, the time-varying Doppler of the underwater acoustic channel will cause inter carrier interference in the OFDM system, destroy the orthogonality between subcarriers, and affect system performance. In this paper, we propose a method based on wavelet function to compensate for the Doppler distortions of the underwater acoustic channel for OFDM data. This method uses a set of orthogonal polynomials to perform channel estimation in both the time and frequency domains and uses the matched filtering for channel equalization. Compared with the traditional polynomials, the smoothly varying polynomials in Wavelet FFT greatly reduces the correlation of the processed data, enable more accurate channel estimation and equalization. Finally, this paper verifies the feasibility of the algorithm through the Songhua Lake underwater experiment.

情报时代已经来临。智能多模式信息对于水下工程至关重要。声音是水下多模式信息技术中必不可少的媒介。正交频分复用水下声通信技术可以实现高比特率通信。然而，水下声信道的时变多普勒将在OFDM系统中引起载波间干扰，破坏子载波之间的正交性，并影响系统性能。在本文中，我们提出了一种基于小波函数的OFDM数据水下声信道多普勒失真补偿方法。该方法使用一组正交多项式在时域和频域中执行信道估计，并将匹配的滤波用于信道均衡。与传统多项式相比，小波FFT中平滑变化的多项式极大地降低了处理数据的相关性，使信道估计和均衡更加准确。最后，通过松花湖水下实验验证了该算法的可行性。