SINS/CNS fast calibration method based on global observability analysis

Zhihao Xu; Zhaofa Zhou; Zihao Xu; Zhenjun Chang; Lei Feng

doi:10.3788/IRLA20210641

Journals >Infrared and Laser Engineering >Volume 51 >Issue 6 >Page 20210641 > Article

Infrared and Laser Engineering
Vol. 51, Issue 6, 20210641 (2022)

SINS/CNS fast calibration method based on global observability analysis

Zhihao Xu¹, Zhaofa Zhou¹, Zihao Xu², Zhenjun Chang¹, and Lei Feng¹

Author Affiliations

¹Missile Engineering Institute, Rocket Force University of Engineering, Xi'an 710025, China

²Air Force Academy, Beijing 100085, China

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DOI: 10.3788/IRLA20210641 Cite this Article

Zhihao Xu, Zhaofa Zhou, Zihao Xu, Zhenjun Chang, Lei Feng. SINS/CNS fast calibration method based on global observability analysis[J]. Infrared and Laser Engineering, 2022, 51(6): 20210641 Copy Citation Text

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Fig. 1. (a) Pitch angle error curve; (b) Roll angle error curve; (c) Heading angle error curve

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Fig. 2. (a) x-axis installation error estimation curve; (b) y-axis installation error estimation curve; (c) z-axis installation error estimation curve

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Fig. 3. (a) x-axis gyro constant drift estimation curve; (b) y-axis gyro constant drift estimation curve; (c) z-axis gyro constant drift estimation curve

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Fig. 4. (a) x-axis accelerometer zero deviation estimation curve; (b) y-axis accelerometer zero deviation estimation curve; (c) z-axis accelerometer zero deviation estimation curve

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Fig. 5. Observability curve of attitude error

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Fig. 6. Observability curve of installation error

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Fig. 7. Observability curve of constant drift of gyro

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Fig. 8. Observability curve of accelerometer zero deviation

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Error states	Group 1	Group 4	Group 5
Initial misalignment angles/(°)	(0.01 0.01 0.05)
Gyro bias/(°)·h−1	0.01	0.003	0.01
Angular random walk coefficient/(°)·h−1	0.005	0.0005	0.005
Accelerometer bias / ${\text{μg} }$	50	50	50
Speed random walk coefficient $/{\text{μg} } \cdot \sqrt {\text{s} }$	10	10	10
Star sensor accuracy/(″)(3σ)	3	3	15
Installation error/(′)	(10 10 20 )

Table 1. Error parameter settings

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Group	Feature amount	$ {\alpha _x}/('') $	$ {\alpha _y}/('') $	$ {\alpha _z}/('') $	$ {\varepsilon _x} $/(°)·h⁻¹	${\varepsilon _y}$/(°)·h⁻¹	${\varepsilon _z}$/(°)·h⁻¹	${\nabla _x}{\text{/μg} }$	${\nabla _y}{\text{/μg} }$	${\nabla _z}{\text{/μg} }$
1	Mean	−0.27	0.23	−0.28	−0.0001	−0.0003	0.0002	0.25	0.22	0.11
1	Standard deviation	0.45	0.30	0.51	0.0014	0.0014	0.0018	0.28	0.83	0.21
2	Mean	0.35	0.39	0.37	−0.0006	0.0005	−0.0006	0.26	−0.23	0.16
2	Standard deviation	0.63	0.73	0.75	0.0015	0.0017	0.0021	0.28	0.88	0.25
3	Mean	0.32	0.49	−193.5	−0.0010	−0.0009	−0.0013	0.30	−0.14	0.25
3	Standard deviation	0.53	0.91	216.5	0.0024	0.0016	0.0038	0.29	0.68	0.47
4	Mean	0.17	0.21	−0.31	−0.0005	−0.0002	−0.0004	0.15	−0.16	−0.12
4	Standard deviation	0.43	0.32	0.49	0.0017	0.0024	0.0016	0.34	0.56	0.23
5	Mean	0.58	0.65	−0.52	−0.0002	0.0004	−0.0005	0.17	0.18	0.17
5	Standard deviation	0.72	1.21	1.13	0.0012	0.0009	0.0025	0.33	0.50	0.20
6	Mean	6.36	6.61	1.75
6	Standard deviation	8.86	7.65	2.84

Table 2. Statistical characteristic quantities of state quantity estimation residuals

Zhihao Xu, Zhaofa Zhou, Zihao Xu, Zhenjun Chang, Lei Feng. SINS/CNS fast calibration method based on global observability analysis[J]. Infrared and Laser Engineering, 2022, 51(6): 20210641

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