在暴露下的陀螺仪MEMS噪声的分数顺序识别
Dominik Sierociuk1,2, Michal Macias1,2, Konrad Andrzej Markowski1,2
1Institute of Control and Industrial Electronics, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland.
Sensors (Basel, Switzerland)
|November 27, 2025
概括
这项研究分析了暴露于的MEMS惯性传感器中的陀螺仪噪声,使用分数计算来识别噪声模型. 结果详细介绍了暴露下噪声演变和传感器行为变化.
科学领域:
- 传感器技术 传感器技术
- 惯性导航系统 惯性导航系统
- MEMS 设备 MEMS 设备
背景情况:
- 惯性导航传感器对于导航系统至关重要.
- MEMS技术是现代惯性传感器的基础.
- 诸如气体暴露等环境因素会影响传感器性能.
研究的目的:
- 在暴露下分析和识别LSM06DSO32惯性传感器中的陀螺仪噪声.
- 为了研究陀螺仪噪声的偏差和偏差.
- 用微数计算来确定噪声模型的顺序.
主要方法:
- 收集的传感器数据在暴露期间的不同间隔.
- 应用差异和相关性分析来估计噪声模型的顺序.
- 使用分数式计算来识别噪音.
- 检查了暴露后的传感器行为.
主要成果:
- 在长时间暴露于气下,特征的陀螺仪噪声演变.
- 确定了受影响的特定噪声模型.
- 由于暴露而导致的偏差和方差的量化变化.
- 在去除后评估传感器性能恢复.
结论:
- 暴露显著影响MEMS陀螺仪的噪声特征.
- 分数式计算为噪声模型识别提供了一种有效的方法.
- 了解噪音行为对于在环境压力下可靠的惯性导航至关重要.
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