Author Affiliations
1School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, Hubei , China2National Key Laboratory of Multispectral Information Intelligent Processing Technology, Wuhan 430074, Hubei , China3Wuhan National Laboratory for Optoelectronics, Huazhong Institute of Electro-Optics, Wuhan 430223, Hubei , Chinashow less
Fig. 1. Test field diagram
Fig. 2. Gyroscope output and temperature curves. (a) Zerobias curve; (b) temperature curve
Fig. 3. Temperature change process correlation curve
Fig. 4. Location diagram of two temperature sensors
Fig. 5. Output curves of two temperature sensors
Fig. 6. Process correlation considering temperature, temperature variation rate, and temperature gradient
Fig. 7. Gyroscope output contrast curves before and after compensation
Fig. 8. Process correlation curves considering coupling term factors
Fig. 9. Algorithm compensation effect considering coupling term factor
Fig. 10. Results of gyroscope experiment before algorithm compensation. (a) Temperature curve; (b) zerobias curves
Fig. 11. Results of gyroscope experiment after algorithm compensation. (a) Temperature curve; (b) zerobias curves
Item | Temperature | Temperature variation rate | Zero offset /[(°)·h-1] | Variable temperature zerobias stability(100 s smoothing)/[(°)·h-1] |
---|
1 | Zero-order | Zero-order | 7.631 | 0.0516 | 2 | First-order | Zero-order | 7.631 | 0.0514 | 3 | Zero-order | First-order | 7.631 | 0.0069 | 4 | First-order | First-order | 7.631 | 0.0059 | 5 | Second-order | First-order | 7.631 | 0.0059 | 6 | First-order | Second-order | 7.631 | 0.0059 | 7 | Second-order | Second-order | 7.631 | 0.0059 |
|
Table 1. Different compensation effects of temperature and temperature variation rate factors