计算机工程与应用2012，Vol.48Issue(3)：111-113,3.DOI:10.3778/j.issn.1002-8331.2012.03.032
融合多特征信息的联合概率数据关联算法
Joint probability data association algorithm with fusing multi-feature information
摘要
Abstract
Joint Probability Data Association(JPDA) algorithm only uses the newest status measurements. As for this shortcoming, this paper proposes an improved JPDA algorithm which fuses multiple feature information. The new algorithm calculates the association matrix between each feature information and targets. According to D-S theory of evidence, this paper fuses status measurements with the other feature information to get fused association probability. Then the fused association probability will be used to modify the original association probability gotten by using JPDA algorithm. And the modified association probability will be used to update the state of targets. Compared to JPDA algorithm, simulations show that the tracking error of the new algorithm can be decreased from 27 to 60 percent.关键词
联合概率数据关联/D-S证据理论/特征信息/航向信息/信息融合Key words
joint data association/ D-S theory of evidence/ feature information/ course information/ data fusion分类
信息技术与安全科学引用本文复制引用
高倩,邹海林,柳婵娟,周莉..融合多特征信息的联合概率数据关联算法[J].计算机工程与应用,2012,48(3):111-113,3.基金项目
国家自然科学基金(No.61170161) （No.61170161）
山东省自然科学基金(No.ZR2009GM001) （No.ZR2009GM001）
山东大学技术项目基金(No.J09LG01) （No.J09LG01）
鲁东大学学科建设项目基金. （）
