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Proceedings Paper

Feasibility analysis of the robust adaptive Kalman filtering model
Author(s): Zhang-yu Huang; Xi-qiang Chen
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Paper Abstract

Classic Kalman Filter is a dynamic and efficient data processing method, but there are some limitations. Robust estimation theory will be introduced to the Classical Kalman Filter (CKF) method, that is: Robust Adaptive Kalman Filter (RAKF). There is a clear advantage in reducing the observational errors and the state prediction errors context. In this paper, it uses a dam deformation monitoring example to illustrate that the RAKF is more reliable than the CKF in the deformation monitoring data processing effectively, and it is obviously in inhibiting the aspect of the state prediction errors and the observational errors. It is a viable and effective method of estimation method.

Paper Details

Date Published: 24 October 2011
PDF: 9 pages
Proc. SPIE 8286, International Symposium on Lidar and Radar Mapping 2011: Technologies and Applications, 82861B (24 October 2011); doi: 10.1117/12.913955
Show Author Affiliations
Zhang-yu Huang, Hohai Univ. (China)
Xi-qiang Chen, Hohai Univ. (China)


Published in SPIE Proceedings Vol. 8286:
International Symposium on Lidar and Radar Mapping 2011: Technologies and Applications
Jonathan Li, Editor(s)

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