A Segmented Low-Order Bistable Stochastic Resonance Method for Fixed-Distance Target Detection in Millimeter-Wave Fuze Under Rainy Conditions

Millimeter-wave (MMW) fuze signals experience significant degradation in rainy environments due to combined raindrop-induced attenuation and scattering effects, substantially reducing echo signal-to-noise ratio (SNR) and critically impacting ranging accuracy. To address these limitations while satis...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Vol. 25; no. 12; p. 3801
Main Authors: Yang, Bing, Wu, Kaiwei, Guo, Zhe, Liang, Yanbin, Hao, Shijun, Huang, Zhonghua
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 18.06.2025
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ISSN:1424-8220, 1424-8220
Online Access:Get full text
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Summary:Millimeter-wave (MMW) fuze signals experience significant degradation in rainy environments due to combined raindrop-induced attenuation and scattering effects, substantially reducing echo signal-to-noise ratio (SNR) and critically impacting ranging accuracy. To address these limitations while satisfying real-time processing requirements, this study proposes (1) a novel segmented low-order bistable stochastic resonance (SLOBSR) system based on piecewise polynomial potential functions and (2) a corresponding fixed-distance target detection algorithm incorporating signal pre-processing, particle swarm optimization (PSO)-based parameter optimization, and kurtosis threshold detection. Experimental results demonstrate the system’s effectiveness in achieving a 9.94 dB SNR enhancement for MMW fuze echoes under rainy conditions, enabling reliable target detection at SNRs as low as −15 dB. Comparative analysis confirms the SLOBSR method’s superior performance over conventional approaches in terms of both SNR enhancement and computational efficiency. The proposed method significantly enhances the anti-rainfall interference capability of the MMW fuze.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s25123801