Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (24): 25-27.DOI: 10.3778/j.issn.1002-8331.2009.24.008

• 博士论坛 • Previous Articles     Next Articles

Method of improved grey relational degree for multi-sensor target recognition

WAN Shu-ping   

  1. College of Information Technology,Jiangxi University of Finance and Economics,Nanchang 330013,China
  • Received:2009-05-18 Revised:2009-06-19 Online:2009-08-21 Published:2009-08-21
  • Contact: WAN Shu-ping

多传感器目标识别的改进灰关联度法

万树平   

  1. 江西财经大学 信息管理学院,南昌 330013
  • 通讯作者: 万树平

Abstract: arget recognition problem of multi-sensor with multiple characteristic indexes,a new fusion method data is proposed.The method uses the distance of confidence to improve the grey relational coefficient.By solving the optimal programming of maximizing the total square deviation of the confidence distance for all attributes,the weights of attributes are derived.Hence,the method of object recognition is given.The method can overcome the subjectivity of the weights acquisition of attributes,and improve the accuracy and trustworthy degree of target recognition.The simulated example proves the effectiveness of the method.

Key words: multi-sensor, data fusion, target recognition, grey relational degree

摘要: 针对具有多个特征指标的多传感器目标识别问题,提出了一种新的融合方法。该方法利用置信距离改进了灰关联系数,通过求解各属性的置信距离的偏差平方之和最大的优化问题,获得属性的权重,从而给出目标识别方法。克服了特征权重选取的主观性,提高了目标识别结果的准确性和可信度。仿真实例验证了方法的有效性。

关键词: 多传感器, 数据融合, 目标识别, 灰关联度

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