基于偏好聚合的区间融合改进惯性MEMS传感器精度

S. Muravyov, P. Baranov, L. I. Khudonogova, Minh Dai Ho
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引用次数: 0

摘要

为了提高导航系统测量的精度,传统上对来自多个相同类型的MEMS传感器的数据进行处理,以获得尽可能小的不确定性的单一值。提出了一种基于区间融合偏好聚合(IF&PA)的惯性微传感器输出数据精确处理方法。采用IF&PA方法对MEMS陀螺仪采集的测量数据进行处理。结果表明,与传统方法相比,所提出的方法可以获得不确定度明显降低的值的最终估计值。因此,IF&PA提供了在不牺牲测量结果质量的情况下降低设备成本的机会。
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Inertial MEMS Sensors Accuracy Improvement by Interval Fusion with Preference Aggregation
To increase the accuracy of measurements in navigation systems, data from several MEMS sensors of the same type are traditionally processed to obtain the single value with minimal possible uncertainty. In this paper, it is proposed a method for precise processing of output data from inertial micro sensors based on the interval fusion with preference aggregation (IF&PA). The measurement data acquired from MEMS gyroscopes were processed by the IF&PA method. The results have shown that the proposed method allows to obtain the resulting estimate of the value with significantly lower uncertainty in comparison with traditional method. Thus, the IF&PA provides an opportunity to reduce the equipment cost without sacrificing the quality of measurement results.
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