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Target Recognition for Ultra-Wideband Radio Fuzes Using 1D-CGAN-Augmented 1D-CNN

  • 0School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Entropy (basel, Switzerland) +

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September 27, 2025

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September 27, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

This study introduces a new signal processing system for ultra-wideband (UWB) radio fuzes, significantly improving target recognition and reliability in complex electronic warfare environments. The novel approach achieves zero false alarms and missed detections, enhancing detonation precision.

Area Of Science

  • Electrical Engineering
  • Signal Processing
  • Artificial Intelligence

Background

  • Ultra-wideband (UWB) radio fuzes require precise signal processing for reliable detonation in battlefield conditions.
  • Electronic warfare environments introduce interference, leading to false alarms and missed detections in UWB fuzes.
  • Current detection methods are vulnerable to jamming, compromising fuze reliability.

Purpose Of The Study

  • To develop a novel signal processing architecture for UWB radio fuzes to enhance reliability and accuracy in contested electromagnetic environments.
  • To address the vulnerability of energy-threshold detection methods to deliberate jamming.
  • To establish a new technical framework for UWB fuze operation in complex spectra.

Main Methods

  • Integration of fixed-parameter Least Mean Squares (LMS) front-end filtering for interference suppression.
  • Implementation of a One-Dimensional Convolutional Neural Network (1D-CNN) for target recognition.
  • Augmentation of training datasets using a One-Dimensional Conditional Generative Adversarial Network (1D-CGAN).

Main Results

  • The novel system achieved 0% false alarm and miss detection rates on test samples.
  • A segment recognition accuracy of 97.66% was attained, a 5.32% improvement over the baseline.
  • The system demonstrated resilience against deliberate jamming, overcoming limitations of traditional methods.

Conclusions

  • The developed signal processing architecture significantly enhances UWB fuze performance in electronic warfare.
  • This breakthrough offers a robust solution for reliable UWB fuze operation in jammed and contested spectra.
  • The study establishes a new benchmark for UWB fuze signal processing and target recognition.

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