Abstract
The federated and fuzzy adaptive filter is composed of the federated filter and the fuzzy adaptive filter which has been improved. To adjust the structure coefficient and algorithm for the new innovation of the matching filter, the federated and fuzzy adaptive filter adjust the weight of locally estimated state on the velocity matching and the angular rate matching in the transfer alignment by the difference between the real innovation variance and the theory innovation variance. And it guarantees the stability of matching filter and the accuracy of transfer alignment. The result of simulation shows that the federated and fuzzy adaptive filter is better to estimate the initial attitude misalignment angle of inertial navigation system (INS) when the system dynamic model and noise statistics characteristics of inertial navigation system are unclear.
This thesis is supported by Project supported by the National Natural Science Foundation of China, project Number: 51178373.
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Song, L., Duan, Z., Chen, D., Sun, J., Xu, S. (2015). Application of Federated and Fuzzy Adaptive Filter on the Velocity and Angular Rate Matching in the Transfer Alignment. In: Liu, H., Kubota, N., Zhu, X., Dillmann, R., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2015. Lecture Notes in Computer Science(), vol 9244. Springer, Cham. https://doi.org/10.1007/978-3-319-22879-2_9
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DOI: https://doi.org/10.1007/978-3-319-22879-2_9
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