基于区间灰关联度的多传感器目标识别方法

Method Based on Interval Grey Association Degree for Multi-sensor Target Recognition

针对具有多个特征指标的多传感器目标识别问题,提出了一种新的不确定性融合方法。该方法定义区间灰关联系数,通过熵权得到各目标类型的灰关联度,给出目标识别算法。克服了属性权重选取的主观性,提高目标识别结果的可信度,计算简单,易于计算机上实现。仿真实例验证了算法的有效性和实用性。

Aiming at the problem of target recognition for multi-sensor with multiple characteristic indexes, a new fusion method of uncertainty was proposed. The method defined the interval grey association coefficient. The weight vector of attributes was obtained by entropy weight. The algorithm of recognition was proposed according to the grey association degree. It can avoid the subjectivity of selecting attribute weight and improve the trustworthy degree of target recognition. It is straightforward and can be performed on computer easily. The simulated example proves that the method is both effective and practicable.