摘要
在被动系统中,多传感器多目标数据关联一直是一个难解决的问题。对静态数据关联多维指派"组合爆炸"问题,许多外学者提出了像最小距离法、最大似然算法等多种解决方法,但它们或正确相关率较低,或计算量较大。基于上述问题,提出了一种基于运动目标在时间上具有连续性的先验知识的新的航迹关联算法,该算法根据数据列之间发展态势的相似或相异程度来衡量航迹间接近的程度,使航迹关联问题突破了样本容量和典型分布这两条限制。仿真结果表明该算法计算量小,正确关联率高,具有较高的工程应用价值。
In passive sonar system, multisensor-multitarget data association is a very different problem. For the ＂combination Bang＂ problem of static data association, many researchers have presented many solutions such as the least distance method and the maximum likelihood method. But some of these methods have a low correct association rate or a high computation burden. A novel association method on the gray theory is presented based on continuous tran- scendent knowledge of moving target in time. This algorithm can weigh the degree of relative correlation by the developing situation between the factors in the data sequence, which breaks through the limitations of the sample quantities and the typical distributing rule. The results of simulation indicate that this algorithm has a high correct association rate with a low computation burden, and so it has a higher value in engineering applications.
出处
《声学技术》
CSCD
2009年第1期17-20,共4页
Technical Acoustics
基金
国防十一五预研课题(2007AA809502B)
关键词
被动系统
多传感器多目标
数据关联
灰色关联
passive system
multisensor-multitarget
data association
grey association
