基于相关性函数和模糊综合函数的多传感器数据融合

Multi-sensor data fusion based on correlation function and fuzzy integration function

针对多传感器数据融合过程中,各传感器可靠度估计的困难和如何对不同类型的传感器数据进行融合,提出了一种基于相关性函数和模糊综合函数的多传感器数据融合方法。该方法首先利用相关性函数计算多传感器的相互支持程度,然后由隶属函数得到每个传感器提供信息的可信度,最后用模糊综合函数获得多传感器对目标属性的融合结果。该方法计算简单,客观地反映了各传感器的可靠程度及相互关系。将该方法用于一个目标识别任务的仿真实验,结果表明应用该方法能确定地识别出目标,是一种有效可行的多传感器数据融合方法。

Focused on the problems that it is difficult to determine the reliability of each sensor and how the data measured by different sensors are fused, a multi-sensor data fusion method based on correlation function and fuzzy integration function is proposed. The mutual supportability of multiple sensors is obtained from the correlation function. Then by the membership function, the reliability of information provided by each sensor is gained. Finally, the supposed fusion result of the object attribute from the multiple sensors could be produced on the basis of fuzzy integration function. This method is simple computationally and can objectively reflect the reliability of each sensor and interrelationship between these sensors. By applying the method to the target identification, the simulation experiment shows that it can identify the target accurately and is an effective and feasible multi-sensor data fusion method.