Cluster Computing

, Volume 22, Supplement 6, pp 15267–15272 | Cite as

Analysis and design of an attitude calculation algorithm based on elman neural network for SINS

  • Chengjun GuoEmail author
  • Jiahan Yan
  • Zhong Tian


In view of the shortcomings of strapdown inertial measurement unit (IMU) such as large noise and error accumulation, poor precision of traditional attitude calculation algorithms and poor adaptability to environment, this paper proposes an attitude calculation algorithm aided by Elman neural network. For multi-sensor information fusion, not every neural network is applicable, but the Elman neural network structure contains a receiving layer, which stores the information of the previous hidden layer, this structural feature enables the Elman neural network to predict in continuous signal. The simulation results show the effectiveness of the algorithm and improve the accuracy and adaptability of the algorithm.


Attitude calculation Elman neural network Adaptive 



The authors would like to thank Prof. Wei Guo at National Key Laboratory of Science and Technology on Communications of UESTC for help, and Prof. Long Jin and Prof. Yonglun Luo at Research Institute of Electronic Science and Technology of UESTC for them assistance in SINS. The author also wants to thank Research Institute of Electronic Science and Technology and Key Laboratory of Integrated Electronic System, Ministry of Education for their support of this research. However, the opinions expressed in this paper are solely those of the authors.


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.National Key Laboratory of Science and Technology on CommunicationsUniversity of Electronic Science and Technology of ChinaChengduChina
  2. 2.Research Institute of Electronic Science and Technology, University of Electronic Science and Technology of ChinaChengduChina

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