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ANALYTICAL PERFORMANCE ASSESSMENT OF 1-D STRUCTURED LEAST SQUARES

Full Paper at IEEE Xplore

Detection and Estimation

Presented by: Florian Roemer, Author(s): Florian Roemer, Martin Haardt, Ilmenau University of Technology, Germany

In this paper, we derive the analytical performance of 1-D standard ESPRIT and 1-D Unitary ESPRIT using one iteration of Structured Least Squares to solve the shift invariance equations. First, we provide the estimation error of the k-th spatial frequency as an explicit expression of the noise realization, which requires no assumptions about the statistics of the noise. Then, we compute the statistical expectation over zero mean circularly symmetric white noise and provide explicit formulas for the resulting mean square errors. All expressions are asymptotic in the effective SNR, i.e., they become exact as either the number of snapshots or the SNR tends to infinity.


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Recorded: 2011-05-24 17:35 - 17:55, Club E
Added: 22. 6. 2011 04:46
Number of views: 53
Video resolution: 1024x576 px, 512x288 px
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Audio track: MP3 [7.31 MB], 0:21:36