模糊聚类信息融合算法在异构多传感器网络中的应用

Fuzzy Data Association and Fusion Approach in Netted Heterogeneous Sensor Environment

摘要:

在多传感器协同探测的应用背景下,提出将模糊聚类算法应用于多传感器网络的数据融合方向,解决异构多传感器网络由于各传感器探测信息粒度、时空不同而造成的航迹分裂和航迹冗余现象；通过仿真结果表明,该算法可以减少传统统计学方法错关联、漏关联的概率,对于复杂运动轨迹的机动目标(交叉航路目标)能够很好地进行多传感器测量数据的聚类,正确地进行测量数据的关联和融合,并进一步在通用航空监视管理系统的工程应用中加以验证；该算法在通用航空监管、物联网、协同探测信息系统方向均有广泛的应用空间。

Abstract:

In order to solve the data association and fusion approach problem in Netted Heterogeneous Sensor Environment, data association algorithm by exploiting the theory of fuzzy data fusion is proposed. Simulated results and further project validation show that different observational data from Multi-sensors can be associated correctly and the disadvantages of the conventional statistics judgment can be overcome. The algorithm would widely be applied in General Aviation, Internet of Things and coordinated detection system.