摘要
目标航迹关联是多传感器信息融合研究中的一个重要问题,利用聚类分析理论,构建了目标观测数据相似度方程,提出了基于层次和密度聚类分析的航迹关联算法,提高了目标数量多且相互位置较近时航迹关联的准确性,对提高多传感器系统的实时处理能力和智能化水平具有一定的实用价值。实验结果表明,算法具有关联成功率高、时间复杂度低、存储量通信量小、易于实现的优点。
Plot-track association is an important problem in the field of multi-sensor data fusion. Based on clustering analysis, a similarity function of target's observed data has been set up, and a plot-track association algorithm based on hierarchical and density clustering analysis has been established. Experimental results show the algorithm can yield more effective association within shorter time, and it can improve the performance of multi-sensor system.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2005年第4期841-843,共3页
Journal of System Simulation
关键词
聚类分析
航迹关联
相似度
信息融合
clustering analysis
plot-track association
similarity
data fusion
