A Multi-sensor Data Fusion Algorithm Based on Improved Kalman Filter

  • Changchun Tang
  • Zhigang Ao
  • Kangyi Zhang
  • Youcheng Wang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 237)

Abstract

Aiming to the handling issue of the multi-source information of joint training, a multi-sensor data fusion algorithm applicable for monitoring joint training is designed. On the basis of Kalman filter, this paper proposed an improved filtering algorithm which takes the quality of measurement data into consideration, a framework of data fusion system is provided based on the needs of algorithm, and this paper also improves the strategy of getting the weights for data fusion. The result of simulation shows that more accurate data can be achieved than any other single sensor measurements after fusing the multi-sensor data through this method.

Keywords

Dada fusion Oint training Kalman filter Correction coefficient 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Changchun Tang
    • 1
  • Zhigang Ao
    • 1
  • Kangyi Zhang
    • 1
  • Youcheng Wang
    • 1
  1. 1.Engineering Institute of Corps of EngineersPeople’s Liberation Army University of Science and TechnologyNanjingChina

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