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Time-Frequency Aliased Signal Identification Based on Multimodal Feature Fusion
Hailong Zhang1, Lichun Li1, Hongyi Pan1
1School of Information Engineering, University of Information Engineering, Zhengzhou 450000, China.
Sensors (Basel, Switzerland)
|April 27, 2024
Summary
This study introduces a novel multi-mode fusion method (TRMM) for recognizing time-frequency aliasing signals in wideband reception. The TRMM method achieves over 97.3% accuracy, overcoming limitations of traditional separation techniques.
Area of Science:
- Signal Processing
- Machine Learning
- Communications Engineering
Background:
- Identifying multi-source signals with time-frequency aliasing is challenging in wideband signal reception.
- Traditional separation-first methods fail under high aliasing conditions due to significant errors.
- Single-mode recognition methods lack sufficient signal information for accurate identification.
Purpose of the Study:
- To propose a robust method for recognizing time-frequency aliasing signals.
- To overcome the limitations of existing signal separation and single-mode recognition techniques.
- To improve the accuracy of identifying complex aliased signals in wideband reception.
Main Methods:
- A novel time-frequency aliasing signal recognition method based on multi-mode fusion (TRMM) is proposed.
- The U-Net network is employed to extract pixel-level features from time-frequency and wave-frequency images.
- Weighted fusion of multimodal features is performed for classification.
Main Results:
- The TRMM method effectively recognizes time-frequency aliasing signals.
- A recognition rate exceeding 97.3% was achieved for a four-signal aliasing model at 0 dB SNR.
- The proposed method demonstrates superior performance compared to traditional approaches.
Conclusions:
- The TRMM method offers an effective solution for time-frequency aliasing signal recognition.
- Multi-mode fusion enhances the accuracy and robustness of signal identification.
- This approach advances the field of wideband signal reception and analysis.
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