Modified adaptive filter algorithm for shipborne SINS transfer alignment

被引：4

作者：

Cheng J.-H. ^{[1
]}

Wang T.-D. ^{[1
]}

Song C.-Y. ^{[1
]}

Yu D.-W. ^{[1
]}

机构：

[1] Automation College, Harbin Engineering University, Harbin

来源：

Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2016年 / 38卷 / 03期

关键词：

Flexural deformation; Sage-Husa adaptive filter; Shipborne strapdown inertial navigation system (SINS); Transfer alignment; Velocity plus attitude matching;

D O I：

10.3969/j.issn.1001-506X.2016.03.25

中图分类号：

学科分类号：

摘要：

In order to solve the problem that the performance of shipborne strapdown inertial navigation system (SINS) transfer alignment is affected by the system dynamic model and noise statistical properties, a new algorithm of "velocity+attitude" transfer alignment based on modified adaptive filter is put forward. In order to solve the problem of filtering divergence caused by noise matrix positive semi-definite, the iterative formulas of the adaptive filtering noise matrix are modified and a strategy to restrain filter divergence based on covariance matching technique is put forward. According to the problem that the dynamic model is affected by the carrier deformation during ship sailing, installation error angle and deflection deformation angle are added into the state and compensated in the algorithm. Computer simulation shows that the modified algorithm can estimate attitude misalignment angle and installation error angle in 50 seconds effectively, and achieve shipborne SINS transfer alignment rapidly. © 2016, Chinese Institute of Electronics. All right reserved.

引用

页码：638 / 643

页数：5

共 16 条

[1]

Gu S.S., Liu J.Y., Zeng Q.H., Et al., A Kalman filter algorithm based on exact modeling for FOG GPS/SINS integration, Optik-International Journal for Light and Electron Optics, 125, 14, pp. 3476-3481, (2014)

[2]

Liu X.X., Xu X.S., Liu Y.T., Et al., A fast and high-accuracy transfer alignment method between M/SINS for ship based on iterative calculation, Measurement, 51, 5, pp. 297-309, (2014)

[3]

Xu J., Wang Y., Xiao Z., Rapid transfer alignment for SINS of carrier craft, Journal of Systems Engineering and Electronics, 24, 2, pp. 303-308, (2013)

[4]

Wang B., Deng Z.H., Liu C., Et al., Estimation of information sharing error by dynamic deformation between inertial navigation system, IEEE Trans. on Industrial Electronics, 61, 4, pp. 2015-2023, (2013)

[5]

Wu W., Chen S., Qin S.Q., Online estimation of ship dynamic flexure model parameters for transfer alignment, IEEE Trans. on Control Systems Technology, 21, 5, pp. 1666-1678, (2013)

[6]

Chi J.N., Qian C.F., Zhang P.Y., Et al., A novel ELM based adaptive Kalman filter tracking algorithm, Neurocomputing, 128, 27, pp. 42-49, (2014)

[7]

Xu F.Z., Su Y.Q., Liu H., Research of optimized adaptive Kalman filtering, Proc. of the 26th Chinese Control and Decision Conference, pp. 1210-1214, (2014)

[8]

Su Y.X., Huang C.M., Liu P.W., Application of adaptive Kalman filter technique in initial alignment of inertial navigation system, Journal of Chinese Inertial Technology, 18, 1, pp. 44-47, (2010)

[9]

Xu L., Li S.L., Qu X.F., Robust adaptive algorithm for transfer alignment, Journal of System Simulation, 24, 11, pp. 2324-2328, (2012)

[10]

Zhang T., Xu X.S., Transfer alignment algorithm based on adaptive federated filter, Journal of Chinese Inertial Technology, 15, 5, pp. 512-516, (2007)

← 1 2 →