OFDR分布式解调优化算法使用离散时间分析信号反向分散的雷利频谱
Shuaipeng Wang1, Haomao Wang2, Zhiguo Zhang2
1Beijing Smart-Chip Microelectronics Technology Co., Ltd., Beijing 100192, China.
Sensors (Basel, Switzerland)
|November 27, 2025
概括
一个新的算法通过使用离散时间分析 (DTA) 信号来增强光频域反射计 (OFDR),用于雷利反射信号 (RBS) 重建. 这种DTA-RBS方法可以提高传感精度和稳定性,而不会增加计算负载.
科学领域:
- 光电学是指光电子产品.
- 信号处理 信号处理
- 分布式传感器 分布式传感器
背景情况:
- 光学频域反射计 (OFDR) 是分布式传感的一个关键技术.
- 传统的OFDR解调方法面临着噪声和虚振荡的挑战,影响准确性.
- 雷利反向散射信号 (RBS) 的重建对于OFDR性能至关重要.
研究的目的:
- 为OFDR引入一种新的分布式解调优化算法.
- 通过使用一种新的信号处理技术,提高OFDR系统的性能和稳定性.
- 在RBS重建中增强光谱特征信息和抑制噪声.
主要方法:
- 将离散时间分析 (DTA) 信号应用于RBS重建,称为DTA-RBS.
- 在距离域中仅使用正频组件用于DTA-RBS生成.
- 采用DTA-RBS的频域构造方法,保持计算效率.
主要成果:
- DTA-RBS实现了0.9527的平均交叉相关性峰值强度,超过了传统方法 (0.9096).
- 在未应力纤维段上观察到标准偏差有63%的改善.
- DTA-RBS表现出优越的应变调节性能和稳定性,避免了传统方法中看到的异常数据点.
结论:
- 在理论上,DTA-RBS方法提供了一种合理且实用的方法来增强OFDR.
- 这种新的算法显著提高了传感准确性,稳定性和强度.
- 对于高精度分布式测量应用,DTA-RBS是有效的.
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