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The application of Square-Root Cubature Kalman Filter in the SINS/CNS integrated navigation system

Authors: null Dongyang Zhang; null Zhihong Deng; null Bo Wang; null Mengyin Fu;

The application of Square-Root Cubature Kalman Filter in the SINS/CNS integrated navigation system

Abstract

The integrated navigation system can improve the navigation accuracy utilizing the redundant information. The Extended Kalman Filter (EKF) is commonly used in the integrated navigation system. It usually takes only one-order of Taylor expansion and needs to calculate the Jacobian matrix, which will affect the accuracy and numerical stability of the system significantly. Thus in this paper the application of Square-Root Cubature Kalman Filter(SCKF) method was proposed to solve the above problems in the SINS/CNS integrated navigation system. The simulation results show that the position, velocity and attitude errors are reduced effectively compared with the EKF method. The SCKF method is more suitable for the state estimation problems in integrated navigation system.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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