对低成本惯性传感器进行均质传感器融合优化
Dusan Nemec1, Jan Andel1, Vojtech Simak1
1Department of Control and Information Systems, Faculty of Electrical Engineering and Information Technology, University of Žilina, 01026 Zilina, Slovakia.
Sensors (Basel, Switzerland)
|July 29, 2023
概括
本研究介绍了惯性传感器阵列的实时传感器融合和校准. 该方法抑制了有缺陷的传感器,提高了估计精度,使用自适应权重提高了准确性.
科学领域:
- 传感器融合式传感器
- 惯性传感器阵列
- 实时校准实时校准
背景情况:
- 同质的惯性传感器阵列需要强大的校准才能获得准确的数据.
- 退化的传感器可以大大降低合传感器数据的精度.
- 现有的方法可能缺乏实时适应性和自动故障检测.
研究的目的:
- 为惯性传感器阵列开发实时传感器融合和校准方法.
- 为了使阵列内的退化传感器能够自动抑制.
- 为了保持或提高传感器估计的整体精度.
主要方法:
- 根据根平均平方误差 (RMSE) 对加权平均值进行传感器数据的自适应加权.
- 实时估计传感器校准常数,包括增益和偏差.
- 将估计的角速度与战术级光纤陀螺仪进行比较,作为地面真相.
主要成果:
- 拟议的方法成功地实时估计了校准常数.
- 退化的传感器被自动抑制,保持估计精度.
- 使用低成本的MEMS陀螺仪进行实验验证,证明了该方法的有效性.
结论:
- 开发的技术为惯性传感器阵列提供了强大的实时校准和传感器融合.
- 适应式加权和退化的传感器抑制提高了数据可靠性.
- 该方法适用于各种传感器阵列,包括MEMS陀螺仪.
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