在通用多传感器集成战略下,IMU阵列的创新建模
Benjamin Brunson1, Jianguo Wang1, Wenbo Ma1
1Department of Earth and Space Science and Engineering, Lassonde School of Engineering, York University, Toronto, ON M3J 1P3, Canada.
Sensors (Basel, Switzerland)
|December 17, 2024
概括
本研究引入了将惯性测量单元 (IMU) 阵列集成到导航系统中的新方法,通过建模单个传感器错误来提高准确性. 该方法增强了陆地车辆的定位和态度估计.
科学领域:
- 导航系统 导航系统
- 传感器融合式传感器
- 动力学是动力学.
背景情况:
- 将惯性测量单元 (IMU) 阵列集成到多传感器系统中,在描述单个传感器错误方面存在挑战.
- 现有的方法通常假定传感器的行为是均的,这可能不反映战术级MEMS IMU的现实.
- 对传感器错误的准确建模对于强大的动力定位和导航至关重要.
研究的目的:
- 提出一种用于将IMU阵列集成到多传感器动力定位/导航系统中的新型建模方法.
- 为了能够在IMU阵列内对单个传感器错误进行时间变化的估计.
- 实施严格的故障检测和排除IMU传感器对外的测量.
主要方法:
- 利用通用多传感器集成战略 (GMIS) 实现IMU阵列集成.
- 使用离散卡尔曼过框架进行全面的错误分析.
- 应用差异组件估计 (VCE) 来描述个别IMU陀螺仪和加速度计的性能.
主要成果:
- 与单个IMU解决方案相比,多IMU解决方案的平均精度提高了14-16%的位置,30%的滚动/俯冲和40%的方向.
- 拟议的方法成功估计了阵列中的每个IMU的时间变化的传感器错误.
- 差异组件估计 (VCE) 允许在单个IMU传感器之间进行性能比较,揭示了非均的行为.
结论:
- 开发的方法有效地将IMU阵列集成到动力定位/导航系统中,大大提高了准确性.
- 一个数组中的IMU,即使是相同的模型,也会表现出不均的行为,需要个别的表征.
- 这项研究为未来对IMU阵列传感器配置和先进传感器融合技术的评估提供了基础.
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