Refined Alignment Method for Single-axis Rotary Inertial Navigation Based on Fuzzy Adaptive Filtering

doi:10.16182/j.issn1004731x.joss.19-0502

Abstract

Abstract: In order to restrain the influence of saw tooth velocity error caused by the inertial measurement unit (IMU) rotation on the initial alignment accuracy of single-axis rotary strapdown inertial navigation system (SINS), a refined alignment method based on fuzzy adaptive Kalman filtering is proposed. After calculating the ratio of actual covariance to theoretical covariance of the innovation sequence, the method adaptively adjusts the measurement noise covariance matrix by using the fuzzy inference system (FIS), so that it can adapt to the changes of measurement noise caused by IMU rotation. The initial alignment validation experiments under the swing environment have been carried out and experiment results show that the adaptive filtering algorithm can effectively restrain the filtering output error caused by the rotation of the IMU, and the heading angle error is reduced from 2.31° to 0.2°, the pitch angle error is reduced from 0.11° to 0.02°, and the roll angle error is reduced from 0.99° to -0.03°. Meanwhile, the initial alignment accuracy of the turntable in different azimuths meets the navigation requirements of high precision SINS.

Key words: strapdown inertial navigation system, single-axis rotary, adaptive Kalman filtering, fuzzy inference system

CLC Number:

Hu Jie, Shi Xiaozhu. Refined Alignment Method for Single-axis Rotary Inertial Navigation Based on Fuzzy Adaptive Filtering[J]. Journal of System Simulation, 2021, 33(2): 315-323.

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