Adaptive Smoothing Method Based on Fuzzy Theory Study and Realization ()
Abstract
In this paper, we study about
a method to optimize the fused track quality in intelligence network of radar
target fusion system, considering the role of people in the fusion system; we
start to find ways to optimize the quality of the fused track, and adaptive
smoothing method is proposed based on fuzzy theory. Tests show that this method
can greatly improve the quality of the fused track system for battlefield
reconnaissance provides high-quality, high-reliability battlefield.
Share and Cite:
Wan, Y. and Hu, C. (2015) Adaptive Smoothing Method Based on Fuzzy Theory Study and Realization.
Journal of Computer and Communications,
3, 38-43. doi:
10.4236/jcc.2015.35005.
Conflicts of Interest
The authors declare no conflicts of interest.
References
[1]
|
Zhu, J., et al. (1995) Fuzzy Control Theory and Applications. Machinery Industry Press, Beijing.
|
[2]
|
Zadeh, L.A. (1965) Fuzzy Sets. Information Control, 8, 338-353.
http://dx.doi.org/10.1016/S0019-9958(65)90241-X
|
[3]
|
Waltz, E. and Llinas, J. (1990) Multisensor Data Fusion. Ar-tech Housem, Norwood.
|
[4]
|
Bu Kman, S.S. (1986) Multiple-Target Tracking with Radar Applications. Artech House, Norwood.
|
[5]
|
Zhang, W.X. and Liang, Y. (1998) Principle of Uncertainty Reasoning. Xi’an Jiaotong University Press, Xi’an.
|
[6]
|
Kleinla (1999) Sensor and Data Fusion Concepts and Applications. SPIE Optical Engineering Press.
|
[7]
|
.Zhang, H.X. (1995) Ship-Based Fuzzy Inference Rules Avoidance Strategy. Fire Control and Command Control, 2.
|
[8]
|
Billah, B., et al. (2006) Exponential Smoothing Model Selection for Fore-Casting. International Journal of Forecasting, 22, 239-247. http://dx.doi.org/10.1016/j.ijforecast.2005.08.002
|
[9]
|
Wei, W. (2000) Intelligent Control Basis. Tsinghua University Press, Beijing.
|