使用单频微波测量对埋藏物体的威胁评估
İbrahim Halil Bayat1, Gülçin Yarimay1,2, Semih Doğu1
1Electronics and Communication Engineering Department, Istanbul Technical University, 34469 Istanbul, Turkey.
Sensors (Basel, Switzerland)
|August 28, 2025
概括
一个具有微波检测系统的新型轻量级神经网络模型使用现实世界的散射参数 (S-参数) 数据准确地识别埋藏的物体. 这种强大的系统可实现防务和安全应用的高精度.
科学领域:
- 应用物理
- 机器学习
- 地质学
背景情况:
- 埋藏物体的检测对于安全和未爆炸弹药 (UXO) 的清理至关重要.
- 现有的方法往往需要复杂的系统或广泛的训练数据.
- 基于微波的探测提供了一个非侵入性的地表分析方法.
研究的目的:
- 开发一个轻量级的神经网络模型用于埋藏物体的识别.
- 将这个模型与使用现实世界测量的微波检测系统集成.
- 对已建立的深度学习架构进行模型性能评估.
主要方法:
- 使用来自现实数据的16x16散射参数 (S参数) 测量.
- 将S参数数据转换为一个256维的特征向量.
- 在特征向量上开发和训练轻量级的神经网络架构.
主要成果:
- 该模型在识别危险物体时达到99.83%的准确性,F1得分为0.989,回忆率为0.979.
- 超越了基线卷积神经网络 (CNN),深度残留网络 (DRN) 和EfficientNet模型.
- 通过对现实世界测量的培训,证明了稳健性和实际相关性.
结论:
- 建议的轻量级神经网络和微波检测系统对于埋藏物体的识别非常有效.
- 这种方法为防御和安全提供了计算效率高,准确的解决方案.
- 现实世界的数据整合提高了模型的可靠性.
相关概念视频
Standing Waves in a Cavity
1.0K
A household microwave and lasers are examples of standing electromagnetic waves in a cavity. When two conducting metal plates are placed parallel at the nodal planes, it creates a cavity where standing waves are formed. The cavity between the two planes is analogous to a stretched string held at the points x = 0 and x = L. Here, the distance 'L' between the two planes must be an integer multiple of half of the wavelength. The wavelengths that satisfy this condition are given by:
1.0K
Electronic Distance Measuring Instruments
113
Electronic Distance Measuring Instruments (EDMs) are essential tools in modern surveying, offering precise distance measurements by emitting electromagnetic signals and calculating the time required for these signals to travel to a target and return. Two primary types of signals are used in EDMs — light waves and microwaves — each suited to specific environmental and distance requirements. Light-wave-based EDMs utilize either infrared or laser light, providing high accuracy over...
113


