A novel INS/ADS integrated navigation method based on INS error model-aided unbiased converted measurement

Zhenwei Li, Yongmei Cheng, Xiaodong Zhang, Yachong Zhang, Shaohua Yang

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

In the inertial navigation system (INS)/ air data system (ADS) integrated navigation system, the measurements of INS and ADS need to be converted to a unified coordinate for fusion. However, the sensor noises cause serious conversion bias in the direct measurement conversion method. In this paper, a novel INS/ADS integrated navigation method based on INS error model-aided unbiased converted measurement (IEM-UCM) is proposed. First, the IEM-UCM model of ADS data from spherical frame to navigation frame is developed, which exploits the INS error model to calculate the compensation factors. Subsequently, the noise covariance of the converted measurement is derived. Finally, a standard Kalman filter (KF) is implemented for INS/ADS integrated navigation. The simulation results validate the effectiveness of the proposed method in terms of the unbiasedness and consistency of the converted measurement. The root mean square error values indicate that the proposed method outperforms the existing methods in navigation accuracy.

Original languageEnglish
Article number065006
JournalMeasurement Science and Technology
Volume33
Issue number6
DOIs
StatePublished - Jun 2022

Keywords

  • Kalman filter
  • inertial navigation system
  • integrated navigation
  • nonlinear filter
  • unbiased converted measurement

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