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Broadband ML estima...
Broadband ML estimation under model order uncertainty
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- Chung, P. J. (författare)
- University of Edinburgh
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- Viberg, Mats, 1961 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Mecklenbräuker, Christoph F. (författare)
- Technische Universität Wien,Vienna University of Technology
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(creator_code:org_t)
- Elsevier BV, 2010
- 2010
- Engelska.
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 90:5, s. 1350-1356
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http://dx.doi.org/10...
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Abstract
Ämnesord
Stäng
- The number of signals hidden in data plays a crucial role in array processing. When this information is not available, conventional approaches apply information theoretic criteria or multiple hypothesis tests to simultaneously estimate model order and parameter. These methods are usually computationally intensive, since ML estimates are required for a hierarchy of nested models. In this contribution, we propose a computationally efficient solution to avoid this full search procedure and address issues unique to the broadband case. Our max-search approach computes ML estimates only for the maximally hypothesized number of signals, and selects relevant components through hypothesis testing. Furthermore, we introduce a criterion based on the rank of the steering matrix to reduce indistinguishable components caused by overparameterization. Numerical experiments show that despite model order uncertainty, the proposed method achieves comparable estimation and detection accuracy as standard methods, but at much lower computational expense. (C) 2009 Elsevier B.V. All rights reserved.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
Nyckelord
- Broadband signals
- Direction of arrival
- signals
- maximum-likelihood-estimation
- Unknown number of signals
- number
- Overparameterized models
- Maximum likelihood estimation
Publikations- och innehållstyp
- art (ämneskategori)
- ref (ämneskategori)
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