摘要
目标航迹关联是分布式多传感器系统数据融合研究中的一个关键问题,传统航迹关联多采用统计相关的方法,计算较为复杂,且存在较大的不确定性。文中以分布式系统的航迹关联问题为研究对象,采用多因素模糊综合决策方法,建立了该算法的模糊因素集、评价集、单因素模糊矩阵、多因素模糊综合决策准则以及航迹关联质量域脱离质量等数学模型,最后给出了典型环境下的仿真结果,并与最近邻域法和K近邻法进行了比较,显示了该算法的优越性。
Track association is an important problem in the field of multi - sensor data fusion. Traditional statis-tical correlation methods have some uncertainties and the calculation is complex. This paper mainly discusses the track association problem for the distributed system. By using multi-factor fuzzy integration decision-making, several mathematic models are set up including the fuzzy factor sets, evaluation sets, single - factor fuzzy judgments matrix, multi - factor fuzzy integration decision - making rule, and the quality of accuracy and reliability of the tracks. At last, the simulation results under the typical environment are given. The comparison between the output of Nearest Neighbor（NN） and K-NN track association algorithm shows its advantage.
出处
《计算机仿真》
CSCD
2008年第2期104-107,共4页
Computer Simulation
关键词
分布式系统
航迹关联
模糊综合决策
算法
Distributed systems
Track association
Fuzzy integration decision- making
Algorithm
