• Semiconductor Optoelectronics
  • Vol. 43, Issue 6, 1087 (2022)
LIU Yu, LIANG Juyang, CHEN Yanping, PENG Hui, and HE Guangrui
Author Affiliations
  • [in Chinese]
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    DOI: 10.16818/j.issn1001-5868.2022121301 Cite this Article
    LIU Yu, LIANG Juyang, CHEN Yanping, PENG Hui, HE Guangrui. IMU De-Noising Method Based on Least Mean Square Algorithm and Extended Kalman Filter[J]. Semiconductor Optoelectronics, 2022, 43(6): 1087 Copy Citation Text show less

    Abstract

    Aiming at the problem that vehicle vibration affects the heading accuracy of MEMS IMU, a method that can effectively suppress vibration noise and improve heading accuracy and stability is proposed. Firstly, the minimum mean method was used to preprocess the data to improve the signal-to-noise ratio. Then, the bias noise of gyroscope was filtered by using the complementary characteristics of accelerometer and gyroscope. Finally, the extended Kalman filter was used for further filtering. A total of 4 hours of field experiment results show that IMU is less affected by carrier vibration, and the accuracy and stability of heading are improved. The relative heading error after large-angle mechanical motion is 3.08° and the heading variance at rest is 2.44×10-5.
    LIU Yu, LIANG Juyang, CHEN Yanping, PENG Hui, HE Guangrui. IMU De-Noising Method Based on Least Mean Square Algorithm and Extended Kalman Filter[J]. Semiconductor Optoelectronics, 2022, 43(6): 1087
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