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Cubature Kalman probability hypothesis density filter based on multi-sensor consistency fusion①
Hu, Zhentao[1]; Hu, Yumei[2]; Guo, Zhen[3]; Wu, Yewei[4]
刊名高技术通讯(英文版)
2016
卷号22期号:4页码:376-384
关键词multi-target tracking probability hypothesis density (PHD) cubature Kalman filter consistency fusion
ISSN号1006-6748
DOIhttp://dx.doi.org/10.3772/j.issn.1006-6748.2016.04.006
URL标识查看原文
收录类别EI
内容类型期刊论文
URI标识http://www.corc.org.cn/handle/1471x/5197551
专题河南大学
作者单位[1]Institute of Image Processing and Pattern Recognition, Henan University, Kaifeng, 475004, China [2]College of Automation, Northwestern Polytechnical University, Xi'an, 710072, China[3]Institute of Image Processing and Pattern Recognition, Henan University, Kaifeng, 475004, China [4]Institute of Image Processing and Pattern Recognition, Henan University, Kaifeng, 475004, China
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GB/T 7714
Hu, Zhentao[1],Hu, Yumei[2],Guo, Zhen[3],et al. Cubature Kalman probability hypothesis density filter based on multi-sensor consistency fusion①[J]. 高技术通讯(英文版),2016,22(4):376-384.
APA Hu, Zhentao[1],Hu, Yumei[2],Guo, Zhen[3],&Wu, Yewei[4].(2016).Cubature Kalman probability hypothesis density filter based on multi-sensor consistency fusion①.高技术通讯(英文版),22(4),376-384.
MLA Hu, Zhentao[1],et al."Cubature Kalman probability hypothesis density filter based on multi-sensor consistency fusion①".高技术通讯(英文版) 22.4(2016):376-384.
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