Research Multi-Sensor Data Fusion Algorithm based on the adaptive cubature kalman filter
Available Online March 2016.
- https://doi.org/10.2991/icmmct-16.2016.162How to use a DOI?
- Cubature kalman filter; adaptive; noise statistic estimator; correction function; integrated filtering; data fusion.
- Cubature kalman filter is prone to filtering divergence if the system model is inaccurate or measuring abnormal. In order to solve this problem, the adaptive cubature kalman filter algorithm was proposed in this paper, it constructed a group of noise statistic estimators to estimate the statistical characteristic of the noise in real time; and when the measurement anomaly, it adopted correction function to adjust the filtering process, and thus the estimation accuracy and the ability to restrain the filtering divergence can be improved effectively ; On the basis of centralized filter structure and federal filter structure, this paper designed a kinds of hybrid composite filter structure about multi-sensor system based on adaptive cubature kalman filter algorithm , and gave the method that fused the local filtering information of each sensorâ€™s to get the global filtering information; In the application background of positioning and navigation for vehicle to make simulation tests, and the results show the effectiveness of the proposed method.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Xiuguo Zhang PY - 2016/03 DA - 2016/03 TI - Research Multi-Sensor Data Fusion Algorithm based on the adaptive cubature kalman filter BT - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology PB - Atlantis Press SP - 831 EP - 834 SN - 2352-5401 UR - https://doi.org/10.2991/icmmct-16.2016.162 DO - https://doi.org/10.2991/icmmct-16.2016.162 ID - Zhang2016/03 ER -