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Article

Anchor-Free SNR-Aware Signal Detector for Wideband Signal Detection Framework

Aviation Engineering School, Air Force Engineering University, Xi’an 710038, China
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Author to whom correspondence should be addressed.
Electronics 2025, 14(11), 2260; https://doi.org/10.3390/electronics14112260
Submission received: 16 April 2025 / Revised: 22 May 2025 / Accepted: 28 May 2025 / Published: 31 May 2025
(This article belongs to the Section Artificial Intelligence)

Abstract

The spectrogram-based wideband signal detection framework has garnered increasing attention in various wireless communication applications. However, the front-end spectrograms in existing methods suffer from visual and informational deficiencies. This paper proposes a novel multichannel enhanced spectrogram (MCE spectrogram) to address these issues. The MCE spectrogram leverages additional channels for both visual and informational enhancement, highlighting signal regions and features while integrating richer recognition information across channels, thereby significantly improving feature extraction efficiency. Moreover, the back-end networks in existing methods are typically transferred from original object detection networks. Wideband signal detection, however, exhibits task-specific characteristics, such as the inherent signal-to-noise ratio (SNR) attribute of the spectrogram and the large variations in shapes of signal bounding boxes. These characteristics lead to issues like inefficient task adaptation and anchor mismatch, resulting in suboptimal performance. To tackle these challenges, we propose an SNR-aware detection network that employs an anchor-free paradigm instead of anchors for signal detection. Additionally, to address the impact of the SNR attribute, we design a trainable gating module for efficient feature fusion and introduce an auxiliary task branch to enable the network to capture more discriminative feature representations under varying SNRs. Experimental results demonstrate the superiority of the MCE spectrogram compared to those utilized in existing methods and the state-of-the-art performance of our SNR-aware Net among comparable detection networks.
Keywords: wideband signal detection framework; enhanced spectrogram; detection network; feature fusion; prior knowledge wideband signal detection framework; enhanced spectrogram; detection network; feature fusion; prior knowledge

Share and Cite

MDPI and ACS Style

Li, C.; Xiang, X.; Mao, H.; Wang, R.; Qi, Y. Anchor-Free SNR-Aware Signal Detector for Wideband Signal Detection Framework. Electronics 2025, 14, 2260. https://doi.org/10.3390/electronics14112260

AMA Style

Li C, Xiang X, Mao H, Wang R, Qi Y. Anchor-Free SNR-Aware Signal Detector for Wideband Signal Detection Framework. Electronics. 2025; 14(11):2260. https://doi.org/10.3390/electronics14112260

Chicago/Turabian Style

Li, Chunhui, Xin Xiang, Hu Mao, Rui Wang, and Yonglei Qi. 2025. "Anchor-Free SNR-Aware Signal Detector for Wideband Signal Detection Framework" Electronics 14, no. 11: 2260. https://doi.org/10.3390/electronics14112260

APA Style

Li, C., Xiang, X., Mao, H., Wang, R., & Qi, Y. (2025). Anchor-Free SNR-Aware Signal Detector for Wideband Signal Detection Framework. Electronics, 14(11), 2260. https://doi.org/10.3390/electronics14112260

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