Yihai Hu
ABSTRACT
In response to the recognition problem of multi-functional radar working modes in complex battlefield environments, a radar working mode recognition algorithm based on recurrent neural networks (RNNs) is proposed. This algorithm takes the original data of radar working modes as input and leverages the ability of RNNs to effectively recognize temporal correlation features of input signals. It avoids the factors of noise influence during feature extraction in traditional methods, enabling the discovery of more representative features from the original data and achieving effective recognition of radar working modes. Four different types of recurrent neural network models were used to recognize the raw data of radar working modes. The experiments demonstrated that RNNs are capable of recognizing radar working mode raw data with noise.
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Index Terms
- Radar Working Mode Recognition Algorithm Based on Recurrent Neural Networks
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