基于证据理论的跟踪辅助目标识别

为提高目标属性识别精度,本文以证据理论为基础,提出一种跟踪辅助目标识别方法。通过在属性融合中引入目标的跟踪信息,增加了属性融合空间的维数,改进了目标的识别性能,提高了目标的识别正确度。实验结果证明了这一方法的有效性,特别是在属性测量传感器较少的情况下,这一方法更有其实际意义。

Evidence theory based track aided target identification

To improve the precision of target attribute identification, a tracking aided target identification method based on evidence theory is advanced in this paper. By introducing the tracking information into attribute fusion, the dimension of attribute fusion space is increased, the performance of target identification is improved, and the accuracy of target identification is also increased. The experiment result proves the validity of this method. This method is practical especially when there are only a few sensors for attribute measurement.