基于最近统计距离的多传感器一致性数据融合

为了剔除多传感器测量数据中的疏失误差,一致性数据融合方法得到广泛研究。在已有方法的基础上,定义了一种新的用于衡量传感器测量数据之间支持程度的统计距离,并在此统计距离的基础上,提出了一种基于最近统计距离的多传感器一致性数据融合新方法。数值仿真实验的结果表明,和已有方法相比,新定义的统计距离更能合理地反映传感器测量数据之间的支持程度,同时,整个融合过程的计算复杂度和计算量明显降低。

Consistent Multi-sensor Data Fusion Based on Nearest Statistical Distance

To eliminate the mistake errors within measurements from multiple sensors, consistent data fusion method is widely studied. Based on the existing methods, a new statistical distance is defined, which is designed to measure the support degree between any two sensors' measurements, then based on this statistical distance, a new consistent multi-sensor data fusion method which is based on the nearest statistical distance is proposed. Numerical simulation results show that, compared with the existing methods, the new defined statistical distance can reflect the support degree between any two sensors' measurements more rationally, and computational complexity and load of the new method are greatly reduced.