Discrimination of small targets in sea clutter using a hybrid CNN-LSTM network
conference paper
Reliable and robust radar target detection is a challenging task in the maritime environment, particularly as bright returns or sea spikes share many similarities with true targets and can be difficult to distinguish. One approach to overcome this challenge is to exploit the persistence of the target and consider detection as a basic classification problem, i.e. either a target is present or absent. In this work, discrimination of small fluctuating targets in sea clutter is demonstrated using a hybrid convolutional neural network with long short-term memory (CNN-LSTM). The proposed approach is able to distinguish targets by exploiting amplitude fluctuations over time, with improved classification observed as longer sequences of data are processed. (C) 2023 IEEE.
Topics
TNO Identifier
993124
ISSN
10975764
ISBN
9781665482783
Publisher
Institute of Electrical and Electronics Engineers Inc.
Source title
Proceedings of the IEEE Radar Conference
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