Journal of System Simulation
Abstract
Abstract: In order to improve the dynamic error coefficient speed of the calibration strapdown inertial group, a dynamic error model is established in the inertial navigation system. The Kalman filter is used to reflect the observation degree of the error term to determine the objective function of the optimal algorithm. The penalty function for the reduced space search algorithm is improved by genetic algorithm. At the end, it not only gets rid of the interference of the local pseudo-optimal solution, but also improves the recognition speed when it is close to the optimal solution. Compared with the solution length of the conjugate gradient method, the efficiency of the improved reduced space search algorithm for dynamic coefficient identification is verified, and the problem that the dynamic error of the strapdown inertial group cannot be quickly compensated is effectively solved.
Recommended Citation
Yan, Hongyan; Yu, Zhang; Zhu, Weihua; Ming, Shi; and Zhang, Yexin
(2019)
"Design of IMU Dynamic Coefficient Calibration Based on Reduced Space Search Algorithm,"
Journal of System Simulation: Vol. 31:
Iss.
11, Article 35.
DOI: 10.16182/j.issn1004731x.joss.19-FZ0338
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol31/iss11/35
First Page
2485
Revised Date
2019-07-18
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.19-FZ0338
Last Page
2491
CLC
TP391.9
Recommended Citation
Yan Hongyan, Zhang Yu, Zhu Weihua, Shi Ming, Zhang Yexin. Design of IMU Dynamic Coefficient Calibration Based on Reduced Space Search Algorithm[J]. Journal of System Simulation, 2019, 31(11): 2485-2491.
DOI
10.16182/j.issn1004731x.joss.19-FZ0338
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