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http://hdl.handle.net/11375/8636
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DC Field | Value | Language |
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dc.contributor.advisor | Wong, K.M. | en_US |
dc.contributor.author | Gu, Xiaodong | en_US |
dc.date.accessioned | 2014-06-18T16:43:30Z | - |
dc.date.available | 2014-06-18T16:43:30Z | - |
dc.date.created | 2011-01-16 | en_US |
dc.date.issued | 1992-12 | en_US |
dc.identifier.other | opendissertations/3825 | en_US |
dc.identifier.other | 4842 | en_US |
dc.identifier.other | 1730639 | en_US |
dc.identifier.uri | http://hdl.handle.net/11375/8636 | - |
dc.description.abstract | This thesis has been directed toward the problem of deriving a computable tight lower bound on the error of DOA estimation with the array processing. This work is developed based on the logic implied in Ziv-Zakai's idea and the work for Cramer-Rao lower bound (CRLB). A profound understanding of Ziv-Zakai's idea is presented. The lowest bound on the variance of DOA estimate with one incoming signal is derived applying the logic of Ziv and Zakai. Then the modified Ziv-Zakai lower bound (MZLB) on the covariance matrix of the multiple DOA estimates is developed. The theoretic analysis and the simulation results show that MZLB is a tight lower bound over a wide range of signal-noise ratio. It follows the SNR-threshold phenomenon occurring in the performance of the DOA estimation well, and it is easily computable. It is proved that, the maximum-likelihood estimation of DOA parameters based on Data Model(2) discussed in this thesis is asymptotically efficient. | en_US |
dc.subject | Electrical and Computer Engineering | en_US |
dc.subject | Electrical and Computer Engineering | en_US |
dc.title | Modified Ziv-Zakai lower bound on the errors of the estimation of DOA | en_US |
dc.type | thesis | en_US |
dc.contributor.department | Electrical and Computer Engineering | en_US |
dc.description.degree | Doctor of Philosophy (PhD) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Size | Format | |
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fulltext.pdf | 2.28 MB | Adobe PDF | View/Open |
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