基于智能雷场的多传感器数据融合

Multi-sensor Data Fusion Based on Smart minefields

在多传感器数据融合算法中,多属性决策在事先确定好的有限数目备选方案中用于偏好决策.多属性决策中使用的因素权值通常都是固定的,无法反应真实情况从而影响数据融合效果.为了解决这一问题,将多属性决策和变权理论相结合用于威胁评估.实验表明,与使用多属性决策相比,该方法有效地发挥了多属性决策和变权理论各自的优越性,所得结果准确地反映了目标真实的威胁程度.给智能雷场作战指挥决策提供了一个更为科学合理的理论方法.

In multi-sensor data fusion algorithms, multi- attribute decision is mainly used for preference decisions a- mong the limited number of pre-determined alternatives. In order to solve the problems that multi-attribute decision factor weights are usually fixed which can not reflect the real situation affecting the data fusion, multi-attribute decision combined with variable weight theoretical are put forward to be used for threat assessment. Experiments show that, com- paring with multi-attribute decision, this method effectively gives play to the advantages of the multi-attribute decision and variable weight theory and the results accurately show the actual threat level, which provides a more scientific and reasonable theory for smart minefields operational command decision.