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一種改進的高斯逆威沙特概率假設密度擴展目標跟蹤算法

李文娟 呂靖 顧紅 蘇衛(wèi)民 馬超 楊建超

李文娟, 呂靖, 顧紅, 蘇衛(wèi)民, 馬超, 楊建超. 一種改進的高斯逆威沙特概率假設密度擴展目標跟蹤算法[J]. 電子與信息學報, 2018, 40(6): 1279-1286. doi: 10.11999/JEIT170883
引用本文: 李文娟, 呂靖, 顧紅, 蘇衛(wèi)民, 馬超, 楊建超. 一種改進的高斯逆威沙特概率假設密度擴展目標跟蹤算法[J]. 電子與信息學報, 2018, 40(6): 1279-1286. doi: 10.11999/JEIT170883
LI Wenjuan, Lü Jing, GU Hong, SU Weimin, MA Chao, YANG Jianchao. Improved Gaussian Inverse Wishart Probability Hypothesis Density for Extended Target Tracking[J]. Journal of Electronics & Information Technology, 2018, 40(6): 1279-1286. doi: 10.11999/JEIT170883
Citation: LI Wenjuan, Lü Jing, GU Hong, SU Weimin, MA Chao, YANG Jianchao. Improved Gaussian Inverse Wishart Probability Hypothesis Density for Extended Target Tracking[J]. Journal of Electronics & Information Technology, 2018, 40(6): 1279-1286. doi: 10.11999/JEIT170883

一種改進的高斯逆威沙特概率假設密度擴展目標跟蹤算法

doi: 10.11999/JEIT170883
基金項目: 

國家自然科學基金(61471198, 61671246),江蘇省自然科學基金(BK20160847, BK20170855)

Improved Gaussian Inverse Wishart Probability Hypothesis Density for Extended Target Tracking

Funds: 

The National Natural Science Foundation of China (61471198, 61671246), The Natural Science Foundation of Jiangsu Province (BK20160847, BK20170855)

  • 摘要: 假設擴展目標(ET)的擴展和量測數(shù)目分別為橢圓和泊松模型,高斯逆威沙特概率假設密度(GIW-PHD)能夠估計擴展目標的運動和擴展狀態(tài)。然而,該濾波器對空間鄰近目標的數(shù)目、非橢圓目標和受到遮擋目標的擴展估計不夠準確。針對這些問題,該文提出一種改進的GIW-PHD。首先,假設目標擴展為一個相同尺寸的參考橢圓,通過設計新的散射矩陣得到改進的隨機矩陣(RM)方法。然后,將改進的RM方法與假設量測數(shù)目服從多伯努利分布的ET-PHD結(jié)合,得到改進的GIW-PHD濾波器。仿真和實驗結(jié)果表明,與傳統(tǒng)GIW-PHD相比,改進的GIW- PHD估計的目標數(shù)目和量測數(shù)目較多,擴展較大的橢圓和非橢圓目標的擴展更準確。
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出版歷程
  • 收稿日期:  2017-09-19
  • 修回日期:  2018-03-16
  • 刊出日期:  2018-06-19

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