Improved position estimation by fusing multiple inaccurate inertial measurement unit sensors

Yuhao Zhang,Chenghao Lyu,Haotian Xu,Yijing Xia,Fei Feng,Gurjeet Singh,Patrick Yin Chiang, X. Sean Wang

2016 IEEE MTT-S International Wireless Symposium (IWS)（2016）

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摘要

This paper presents improved position tracking and location estimation of dead reckoning, by combining the data from multiple inaccurate inertial sensors together using unscented Kalman filtering (UKF). Experimental test results using two 9-axis inertial measurement unit (IMU) sensors show that position estimation of each sensor achieves a 26 % decrease in max error (ME) and a 37% improvement in root-mean-square error (RMSE), when compared with a single independent sensor.

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关键词

inertial measurement unit,multiple inertial sensors,position estimation,sensor data fusion,equality-constrained unscented Kalman filtering

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