An Improved UWB/IMU Tightly Coupled Positioning Algorithm Study.

Airu Zou, Wenwu Hu, Yahui Luo, Ping Jiang
Author Information
  1. Airu Zou: College of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha 410128, China.
  2. Wenwu Hu: College of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha 410128, China.
  3. Yahui Luo: College of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha 410128, China.
  4. Ping Jiang: College of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha 410128, China.

Abstract

The combination of ultra-wide band (UWB) and inertial measurement unit (IMU) positioning is subject to random errors and non-line-of-sight errors, and in this paper, an improved positioning strategy is proposed to address this problem. The Kalman filter (KF) is used to pre-process the original UWB measurements, suppressing the effect of range mutation values of UWB on combined positioning, and the extended Kalman filter (EKF) is used to fuse the UWB measurements with the IMU measurements, with the difference between the two measurements used as the measurement information. The non-line-of-sight (NLOS) measurement information is also used. The optimal estimate is obtained by adjusting the system measurement noise covariance matrix in real time, according to the judgment result, and suppressing the interference of non-line-of-sight factors. The optimal estimate of the current state is fed back to the UWB range value in the next state, and the range value is dynamically adjusted after one-dimensional filtering pre-processing. Compared with conventional tightly coupled positioning, the positioning accuracy of the method in this paper is improved by 46.15% in the field experimental positioning results.

Keywords

References

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MeSH Term

Algorithms
Judgment
Mutation

Word Cloud

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