Application of Multi-Sensors Data Fusion Technology in the Theodolite Tracking System

Abstract:

The task of multi-sensors data fusion technology is to obtain more precise estimate of object state and light path than single sensor through dealing with the information from different sensors. The paper puts forward the ideal of applying the data fusion theory to O-E theodolite system, based on the data fusion theory and Kalman filter and estimate theory. At the condition of losing and covering object, the theodolite tracks object normally. The theory of multi-sensors data fusion is validated improving acquiring and tracking ability of the theodolite effectively in practice.

• Periodical: Applied Mechanics and Materials (Volume 392)
• Pages: 783-786
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.392.783
• Online since: September 2013
• Authors: Bing Ge, Yi Yu
• Keywords: Data Fusion, Kalman Filter (KF), Multi-Sensors

References

[1] Yang Wanhai, multisensor data fusion and its application, Xi an, Xi an Electronic and Science University press, 2004. 4.

[2] C Stiller, J Hipp, C Rossing, et al. Multisensor obstacle detection and tracking[J]. Image and Vision Computing, 2000, 18,: 389-396.

DOI: 10.1016/s0262-8856(99)00034-7

[3] Yuan Hongyin, Guo lihong, et al. Simulation on Tracking Mobile Target by Kalman Prediction Method[J]. Journal of Jilin Agricultural University. 2003, 25(6): 679~681.

[4] Shen Yi, Kalman Filter Technology and Its Application in Target Tracking[D]. Graduate School of National University of Defense Technology. Hunan, May (2006).