Autonomous ships are expected to improve the level of safety and efficiency in future
maritime navigation. Such vessels need perception for two purposes: to perform …

Abstract Machine learning covers a large set of algorithms that can be trained to identify
patterns in data. Thanks to the increase in the amount of data and computing power …

Underwater acoustic classification is a challenging problem because of presence of high
background noise and complex sound propagation patterns in the sea environment. Various …

Passive recognition of underwater acoustic targets is a hot research issue in acoustic signal
processing. The long-term interference of irregular noise in the marine environment caused …

Underwater acoustic target recognition (UATR) is usually difficult due to the complex and
multipath underwater environment. Currently, deep-learning (DL)-based UATR methods …

This paper presents a comprehensive review of hydrophones, their design considerations,
physical aspects, and structures by reviewing many publications that have been published …

The sonar received signals may contain various artifacts such as noise, reverberation, and
clutter that affect the proper target recognition and classification capabilities of sonar …

Facing the complex marine environment, it is extremely challenging to conduct underwater
acoustic target feature extraction and recognition using ship-radiated noise. In this paper …

In 2016, the world shipping fleet grew by 3.5%. Even if the annual growth rate remains at its
lowest since 2013, the global situation is still in overcapacity (UNCTAD 2016). Ninety …

In underwater acoustic target recognition, wave-based methods and time–frequency (TF)
representation-based methods are typically used to identify the target from different …