Target Recognition Based on Fuzzy Dempster Data Fusion Method

  • Yong Deng southwest university, chongqing
  • Xiaoyan Su Shanghai Jiao Tong University, Shanghai
  • Dong Wang Shanghai Jiao Tong University, Shanghai
  • Qi Li Shanghai Jiao Tong University, Shanghai
Keywords: Evidence theory, fuzzy sets theory, multi-sensor fusion, Target recognition

Abstract

Data fusion technology is widely used in automatic target recognition system. Problems in data fusion system are complex by nature and can often be characterised by not only randomness but also by fuzziness. To accommodate complex natural problems with both types of uncertainties, it is profitable to construct a data fusion structure based on fuzzy set theory and Dempster Shafer evidence theory. In this paper, after representing both, the individual attribute of target in the model database and the sensor observation or report as fuzzy membership function, a likelihood function was constructed to deal with fuzzy data collected by each sensor. The method to determine basic probability assignments of each sensor report is proposed. Sensor reports are fused through classical Dempster combination rule. A numerical example is illustrated to show the target recognition application of the fuzzy-Dempster approach.

Defence Science Journal, 2010, 60(5), pp.525-530, DOI:http://dx.doi.org/10.14429/dsj.60.576

Author Biographies

Yong Deng, southwest university, chongqing
He has obtained his Masters in Instrument Engg from Hunan University, Changsha, China, in 2000, and PhD in Precise Instrument and Mechanic Engg from Shanghai Jiao Tong University, Shanghai, China, in 2003. Currently, he is a Professor in Southwest University. His areas of research interests include: Information fusion, fuzzy logic, risk analysis and decision analysis. He has published about 40 papers in peer reviewed journals.
Xiaoyan Su, Shanghai Jiao Tong University, Shanghai

She has received the Bachelor (Measurement and Control Technology and Instrument) from Xiamen University, Xiamen, China, in 2009. Currently she is pursuing PhD from School of Electronics & Information Technology, Shanghai Jiao Tong University. Her research interests include: information fusion, fuzzy logic, risk analysis and decision analysis.

Dong Wang, Shanghai Jiao Tong University, Shanghai
She has received the Bachelor (Measurement and Control Technology and Instrument) from University of Electronics Science and Technology of China, Chengdu, China, in 2010. Currently she is pursuing PhD from School of Electronics & Information Technology, Shanghai Jiao Tong University. His research interests include: information fusion and automatic detection.
Qi Li, Shanghai Jiao Tong University, Shanghai

He has received the Bachelor (Electric Engineering) from University of Electronics Science and Technology of China, Chengdu, China, in 2006. Currently she is pursuing PhD from School of Electronics & Information Technology, Shanghai Jiao Tong University. His research interests include: decision analysis.

Published
2010-08-24
How to Cite
Deng, Y., Su, X., Wang, D., & Li, Q. (2010). Target Recognition Based on Fuzzy Dempster Data Fusion Method. Defence Science Journal, 60(5), 525-530. https://doi.org/10.14429/dsj.60.576
Section
Research Papers