Content Tags

There are no tags.

Underwater acoustic target recognition using attention-based deep neural network

Xu Xiao, Wenbo Wang, Qunyan Ren, Peter Gerstoft, Li Ma

Underwater acoustic target recognition based on ship-radiated noise is difficult owing to the complex marine environment and the interference by multiple targets. As an important technology for target recognition, deep-learning has high accuracy but poor interpretability. In this study, an attention-based neural network (ABNN) is proposed for target recognition in the pressure spectrogram with multi-source interference using an attention module to inspect the inner workings of the neural network. From data obtained during a September 2020 sea trial, the ABNN exhibited a gradual focus on the frequency-domain feature of the target ship and suppressed environmental noises and marine vessel interference, which led to high accuracy in the target detection and recognition.

Stay in the loop.

Subscribe to our newsletter for a weekly update on the latest podcast, news, events, and jobs postings.