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Vol. 172, Issue 6, June 2014, pp. 39-44




Combining Gray Relational Analysis with Cumulative Prospect Theory for Multi-sensor Target Recognition

1 Qi Wang, 2 Haiping Ren

1 Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
2 School of Software, Jiangxi University of Science and Technology, Nanchang 330013, P. R. China
Tel.: 13590788079

E-mail: wangqirhp@163.com


Received: 16 April 2014 /Accepted: 30 May 2014 /Published: 30 June 2014

Digital Sensors and Sensor Sysstems


Abstract: The aim of this paper is to propose a new multi-sensor target recognition method for solving the problem which the discriminated object has multiple characteristics indexes. The method combines the concept of gray relational analysis (GRA) method and cumulative prospect theory. This method, the characteristic vector matrix was firstly transformed to standardize membership degree decision making matrix by using a minimum and maximum membership function model. Then the positive and negative ideal points are defined. Further, according to the cumulative prospect theory and GRA, the prospect value function is defined, and an optimization model is built to solve the optimum weight vector. Finally, the rule of target recognition is given. The method can avoid the subjectivity of the weight of characteristic indexes and improve the objectivity and accuracy of target recognition. Finally, numerical simulation illustrates the effectiveness and feasibility of the proposed method.


Keywords: Multi-sensor, Target recognition, Cumulative prospect theory, Gray relational.


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