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Exact Unconditional ML Estimation of DOA
Title: | Exact Unconditional ML Estimation of DOA |
Authors: | Suzuki, Masakiyo Browse this author | Chen, Haihua Browse this author |
Issue Date: | 4-Oct-2009 |
Publisher: | Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference, International Organizing Committee |
Journal Title: | Proceedings : APSIPA ASC 2009 : Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference |
Start Page: | 876 |
End Page: | 882 |
Abstract: | This paper presents an exact formulation of Stochastic or Unconditional Maximum Likelihood (UML) estimation for directions-of-arrival (DOA) finding. In the previous formulation of UML estimation, an important condition is missing. That is the non-negative definiteness of the covariance matrix of signal components without additive noises. Because of the lack of the important condition, inadequate global solution appears in the solution space and global search fails to find adequate solution. We have derived an exact formulation including this important condition. Then the inadequate global solution disappears and global search finds adequate solution. |
Description: | APSIPA ASC 2009: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference. 4-7 October 2009. Sapporo, Japan. Oral session: Signal Processing Theory and Methods II (7 October 2009). |
Conference Name: | APSIPA ASC 2009: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference | 2009年アジア太平洋信号情報処理連合学会アニュアルサミット・国際会議 |
Conference Place: | Sapporo |
Type: | proceedings |
URI: | http://hdl.handle.net/2115/39826 |
Appears in Collections: | 北海道大学サステナビリティ・ウィーク2009 (Sustainability Weeks 2009) > 2009年アジア太平洋信号情報処理連合学会アニュアルサミット・国際会議 (2009 APSIPA Annual Summit and Conference)
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