Research on the Indoor Environment Positioning Algorithm Using Sensor Fusion

Show-Ling Jang, Byoungman An, Sanghun Yoon, Ki-Taeg Lim
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引用次数: 1

Abstract

This paper proposes the indoor environment positioning algorithm using sensor fusion. The suggested method derived the positioning model for IMU (Inertial Measurement Unit) sensors and UWB (Ultra-wideband) sensors and combined them with EKF (Extended Kalman Filter). To verify the performance of the algorithm, the composite sensor module was constructed. The experiment was performed in an indoor environment. It was confirmed that the fusion of the two sensors is enough to satisfy the driving safety in the indoor environment. Consequently, the proposed algorithm showed that the closest positioning performance to a real trajectory comparing to the positioning performance with a conventional methodology of single sensor.
基于传感器融合的室内环境定位算法研究
提出了一种基于传感器融合的室内环境定位算法。该方法推导了惯性测量单元(IMU)传感器和超宽带(UWB)传感器的定位模型,并将其与扩展卡尔曼滤波(EKF)相结合。为了验证该算法的性能,构建了复合传感器模块。实验是在室内环境下进行的。验证了两种传感器的融合足以满足室内环境下的驾驶安全。结果表明,与传统的单传感器定位方法相比,该算法具有最接近真实轨迹的定位性能。
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