In this paper we adapt the matched subspace detectors (MSDs) of [5] and [6] to unknown noise covariance matrices in order to produce adaptive MSDs that may be applied to signal detection in radar, sonar, mobile communication, and DOA estimation. A special case of the adaptive MSD uses the Reed ratio statistic [4], and a special case of the adaptive CFAR MSD uses an adaptive coherence estimator (ACE). We compare and contrast the invariances and performances of the two detectors and discuss extensions of them that make them maximum likelihood MSDs. In a companion paper [3], we apply the adaptive CFAR MSD to simulated data and to data recorded from the Mountaintop radar.
机构:
Air Force Early Warning AcademyCollege of Electronic Science and Engineering, National University of Defense Technology
Wenchong Xie
Haibo Tong
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机构:
College of Electronic Science and Engineering, National University of Defense TechnologyCollege of Electronic Science and Engineering, National University of Defense Technology
Haibo Tong
Honglin Wang
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机构:
Air Force Early Warning AcademyCollege of Electronic Science and Engineering, National University of Defense Technology
Honglin Wang
Cui Zhou
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Air Force Early Warning AcademyCollege of Electronic Science and Engineering, National University of Defense Technology
Cui Zhou
Yongliang Wang
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Air Force Early Warning AcademyCollege of Electronic Science and Engineering, National University of Defense Technology
机构:
Wuhan Elect Informat Inst, Wuhan 430019, Hubei, Peoples R ChinaWuhan Elect Informat Inst, Wuhan 430019, Hubei, Peoples R China
Liu, Weijian
Wang, Yong-Liang
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Wuhan Elect Informat Inst, Wuhan 430019, Hubei, Peoples R ChinaWuhan Elect Informat Inst, Wuhan 430019, Hubei, Peoples R China
Wang, Yong-Liang
Liu, Jun
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机构:
Xidian Univ, Natl Lab Radar Signal Proc, Xian 710071, Shaanxi, Peoples R China
Xidian Univ, Collaborat Innovat Ctr Informat Sensing & Underst, Xian 710071, Shaanxi, Peoples R ChinaWuhan Elect Informat Inst, Wuhan 430019, Hubei, Peoples R China
Liu, Jun
Huang, Lei
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机构:
Shenzhen Univ, Coll Informat Engn, Shenzhen 518060, Peoples R ChinaWuhan Elect Informat Inst, Wuhan 430019, Hubei, Peoples R China
Huang, Lei
Hao, Chengpeng
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机构:
Chinese Acad Sci, Inst Acoust, State Key Lab Acoust, Beijing 100190, Peoples R ChinaWuhan Elect Informat Inst, Wuhan 430019, Hubei, Peoples R China
机构:
UCL, Dept Secur & Crime Sci, London WC1E 6BT, England
UCL, Dept Stat Sci, London WC1E 6BT, EnglandUCL, Dept Secur & Crime Sci, London WC1E 6BT, England
Wang, Ziyu
Xue, Jing-Hao
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UCL, Dept Stat Sci, London WC1E 6BT, EnglandUCL, Dept Secur & Crime Sci, London WC1E 6BT, England