The multipath effect and Doppler effect of the Underwater Acoustic (UWA) channel cause intersymbol interference and inter-carrier interference at the receiver of the orthogonal frequency division multiplexing (OFDM) communication system, which degrades the system performance. A novel Passive Time ReversalConvolutional Neural Network (PTR-CNN) is constructed and applied to the OFDM UWA communication system re? ceiver. The PTR-CNN network consists of two parts. Firstly, it weakens the multipath and enhances the main path in? formation energy based on passive time reversal theory. Secondly, the above-mentioned output result is converted into a two-dimensional matrix, which is input into the CNN for signal detection to simultaneously combat the interfer? ence caused by the multipath and Doppler effect. Finally, the network output directly restores the bit stream. Simula? tion and experimental results demonstrate that when compared with the current mainstream channel estimation and signal detection algorithms, the proposed method can improve the reliability of the system, and it has better robust? ness in different UWA channel environment tests.