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| Citation: | LI Weijie, YANG Wei, LI Xiang, et al. Robust high resolution range profile recognition method for radar targets in noisy environments
[J]. Journal of Radars, 2020, 9(4): 622–631. doi: 10.12000/JR19093
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Robust High Resolution Range Profile Recognition Method for Radar Targets in Noisy Environments
doi: 10.12000/JR19093
More Information-
Abstract
With the application of deep learning technology in the radar target recognition field, the automatic extraction of the target feature greatly improves the accuracy and robustness of the recognition, but its robustness in noisy environments needs to be further investigated. This paper proposes a robust target recognition method for radar High Resolution Range Profile (HRRP) data based on Convolutional Neural Networks (CNN). By enhancing training set and using the residual block, inception structure, and denoising sparse autoencoder layer to enhance the network structure, a higher recognition rate is achieved in a wider SNR range, under the condition of 0 dB Rayleigh noise, the recognition rate reaches 96.14%, and the influence of the network structure and noise type on results is analyzed. -
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References
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- Figure 1. The structure of CNN
- Figure 2. The schematic diagram of Dropout
- Figure 3. The structure of residual block
- Figure 4. The structure of inception
- Figure 5. The structure of residual DAE
- Figure 6. The structure of network
- Figure 7. The block diagram of network function
- Figure 8. Schematic diagram of HRRP
- Figure 9. The structure of CNN