计算机与数字工程2012，Vol.40Issue(9)：12-15,4.
基于TDOA测量的多目标P-GMPHD跟踪算法
A New P-GMPHD Filter Algorithm for Multiple Target Localization Based on Passive Multilateral TDOAs
摘要
Abstract
According to the traditional multi-target tracking based on TDOA being of higher computational, lower estimated accuracy, and the presence of association uncertainty, a novel pre-association Gaussian mixture probability hypothesis density filter (P-GMPHD) is proposed. The approach involves modeling the targets and measurements as random finite sets and applying the Gaussian mixture to propa-gate the posterior density, which could avoid the difficult problem of data association. To alleviate the computation of GMPHD, a pre-associ-ation method which eliminates false measurements is introduced. Simulation results show that the P-GMPHD algorithm could deal with un-known number of emitters under the complex environment with clutter. Moreover, without loses tracking accuracy,the algorithm presents lower tracking computation.关键词
多目标跟踪/随机有限集/TDOA/P-GMPHDKey words
multi-target tracking/random finite sets (RFS)/time difference of arrival (TDOA)/P-GMPHD分类
信息技术与安全科学引用本文复制引用
徐志军,苗秀梅,吴鑫辉..基于TDOA测量的多目标P-GMPHD跟踪算法[J].计算机与数字工程,2012,40(9):12-15,4.基金项目
国家自然科学基金项目(编号:60901069),湖北省自然科学基金(编号:2009CDB031)资助. （编号:60901069）
