Gravity Matching Aided Navigation Using a New Mixed Filter Algorithm

Chao Bin Wen; Yue Gang Wang; Xin Lei Jiang; Hong Lei Teng

doi:10.4028/www.scientific.net/AMM.644-650.2067

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 644-650Gravity Matching Aided Navigation Using a New...

Gravity Matching Aided Navigation Using a New Mixed Filter Algorithm

Abstract:

To solve low precision of basic gravity aided matching algorithm caused by the influence of gravimetric map error, observed model linearization error, insufficiency observed quantity and so on, a novel algorithm of square root KF+CKF mixed filter algorithm based on Rao-Blackwellizationptive is proposed. The calculation accurary,speed, noise immunity, and application scope are improved by approximation local gravity field model using gauss spline interpolation,establishing nonliear mixed model viewing at gravity and position error, model decomposition using Rao-Blackwellization thoery,improving KF and CKF by changing error covariance matrix to square root model, adaptively adjusting filter renewal process.The result shows that it is less sensitive to INS initial error and nonlinearized degree of navigation system model with higher speed,better accurary and stronger robustness.

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Periodical:

Applied Mechanics and Materials (Volumes 644-650)

Pages:

2067-2070

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.644-650.2067

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Online since:

September 2014

Authors:

Chao Bin Wen*, Yue Gang Wang, Xin Lei Jiang, Hong Lei Teng

Keywords:

Cubature Kalman Filter (CKF), Gravity Aided Navigation, KF, Nonlinear Filtering

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* - Corresponding Author

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