Feasibility analysis of the robust adaptive Kalman filtering model

Zhang-yu Huang; Xi-qiang Chen

doi:10.1117/12.913955

24 October 2011 Feasibility analysis of the robust adaptive Kalman filtering model

Zhang-yu Huang, Xi-qiang Chen

Proceedings Volume 8286, International Symposium on Lidar and Radar Mapping 2011: Technologies and Applications; 82861B (2011) https://doi.org/10.1117/12.913955
Event: International Symposium on Lidar and Radar Mapping Technologies, 2011, Nanjing, China

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.

Citation Download Citation

Zhang-yu Huang and Xi-qiang Chen "Feasibility analysis of the robust adaptive Kalman filtering model", Proc. SPIE 8286, International Symposium on Lidar and Radar Mapping 2011: Technologies and Applications, 82861B (24 October 2011); https://doi.org/10.1117/12.913955

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