一个解分解噪声分析模型,用于闭环模式局部化的倾斜传感器
Kunfeng Wang1,2,3, XingYin Xiong1, Zheng Wang4
1The State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China.
Microsystems & nanoengineering
|December 22, 2023
概括
这项研究引入了一种用于模式局部化传感器的新型解分解 (DD) 噪声模型. 该模型通过分析弱合共振器中的振幅噪声来提高倾斜传感器的分辨率.
科学领域:
- * 物理学和工程学
- * 传感器技术 * 传感器技术
- * * 信号处理 信号处理
背景情况:
- * 模式本地化传感器通过使用合共振模式提供高灵敏度和分辨率.
- * 振幅比 (AR) 中的振幅噪声对于传感器分辨率至关重要,但在弱合的共振器电路中不太了解.
- *现有的传感技术面临着模式本地化旨在克服的局限性.
研究的目的:
- * 开发和验证一种用于模式局部化传感器的新型解分解 (DD) 噪声分析模型.
- * 为了研究和模拟弱合共振器的闭环电路内的振幅噪声.
- * 为了提高模式本地化的倾斜传感器的分辨率.
主要方法:
- *将解分解 (DD) 噪声分析模型应用于本地化模式的倾斜传感器.
- *使用解方法分离弱合的共振器,以考虑共振器非线性.
- *闭环电路的分解成不同的振幅和相位噪声分析路径.
- *通过MATLAB/Simulink模拟对理论分析进行DD模型的验证.
主要成果:
- *DD噪声模型准确地预测了弱合共振器的闭环电路中的系统噪声.
- * 一个定位模式的倾斜传感器在最佳操作点实现了3.91 × 10-4°的输入引用不稳定性.
- * 传感器显示输入引用幅度比功率光谱密度 (PSD) 为 2.01 × 10-4°/√Hz.
- *开发的噪声模型适用于各种模式局部化传感器.
结论:
- *DD噪声模型提供了一个强大的框架,用于分析和减轻模式局部化传感器中的噪声.
- *经过验证的模型能够显著提高倾斜感应应用的分辨率.
- * 这项研究有助于推进模式本地化传感技术的性能和应用.
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