HYBRID WAVELET-KALMAN FILTER MULTI-SCALE SEQUENTIAL FUSION METHOD

Funa Zhou, Tianhao Tang

2008

Abstract

With the development of automation, multi-scale data fusion has become a hot research topic, however, limited by the constraint that signal to implement wavelet transform must have the length of 2q, multi-scale data fusion problem involved with non- 2n sampled observation data still hasn’t been efficiently solved. In this paper, we develop a hybrid wavelet-Kalman filter multiscale sequential fusion method. First, we develop the hybrid wavelet-Kalman filter multiscale estimation method which combines the advantage of wavelet and Kalman filter to obtain the real time, recursive, multiscale estimation of the dynamic system. Then, a multiscale sequential fusion method is presented. Under the hybrid wavelet-Kalman filter multiscale estimation frame, we can easily fuse information from multiple sensors sequentially without designing other complex fusion algorithm. The multiscale sequential fusion method can fuse non- 2n sampled data just by analyzing the possible observation structure to design the observation model of the stacked dynamic system. Simulation result of three sensors with sampling interval 1, 2 and 3 shows the efficiency of this method.

References

  1. Wen Chenglin, Zhou Donghua, 2002. Multi-scale estimate theory and application, Being jing: Qstinghua Publication House.
  2. Wen Chenglin, Jin Feng, Zhou Donghua, 2002. Multiscale estimate algorithm for one single sensor and one model, Journal of Electronics 30(6):819-822.
  3. Lang Hong, 1994. Multi-resolution distributed filtering. IEEE Transactions on AC, 39(4): 853-856.
  4. Tong Xinzheng, A.A.Girgis, E.B.Makram, 2000. Hybrid wavelet-Kalman filter method for load for forecasting. Electric power systems research. 54(2):11-17.
  5. Wen Chenglin, Xie Jin, Zhou Funa, Wen Chuanbo, 2006. A New Hybrid Wavelet-Kalman Filter Method for the Estimation of Dynamic System .Journal of Electronics(China),23(1):139-143.
  6. Chenglin Wen, Chuanbo Wen, 2006. The Multiscale Sequential Filter with Multisensor Data Fusion. Proceedings of the 25th Chinese control conference:483-488. Harbin, Heilongjian, China.
  7. Funa Zhou, Tianhao Tang, Chenglin Wen, 2007. A New Multiscale Estimation Scheme for Dynamic System. Proceedings of the 26th Chinese control conference(5):396-400. Zhangjiajie, Hunan, China.
Download


Paper Citation


in Harvard Style

Zhou F. and Tang T. (2008). HYBRID WAVELET-KALMAN FILTER MULTI-SCALE SEQUENTIAL FUSION METHOD . In Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 978-989-8111-32-6, pages 244-248. DOI: 10.5220/0001483702440248


in Bibtex Style

@conference{icinco08,
author={Funa Zhou and Tianhao Tang},
title={HYBRID WAVELET-KALMAN FILTER MULTI-SCALE SEQUENTIAL FUSION METHOD},
booktitle={Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},
year={2008},
pages={244-248},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001483702440248},
isbn={978-989-8111-32-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
TI - HYBRID WAVELET-KALMAN FILTER MULTI-SCALE SEQUENTIAL FUSION METHOD
SN - 978-989-8111-32-6
AU - Zhou F.
AU - Tang T.
PY - 2008
SP - 244
EP - 248
DO - 10.5220/0001483702440248