Analytical performance assessment of esprit-type algorithms for coexisting circular and strictly non-circular signals

Estimating the directions of arrival (DOA) of coexisting circular and strictly second-order (SO) non-circular (NC) signals has recently emerged as an active field of research. In previous work, we have proposed two ESPRIT-type algorithms, i.e., C-NC Standard ESPRIT and C-NC Unitary ESPRIT, for this...

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Bibliographic Details
Main Authors: Steinwandt, Jens, Roemer, Florian, Haardt, Martin
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Asymptotic properties
Circularity
Direction-of-arrival estimation
DOA estimation
Electronics
ESPRIT
Estimating
Estimation error
Mathematical analysis
mixture
non-circular sources
Performance assessment
Signal processing algorithms
Signal to noise ratio
Statistical methods
Transmission line matrix methods
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Summary:Estimating the directions of arrival (DOA) of coexisting circular and strictly second-order (SO) non-circular (NC) signals has recently emerged as an active field of research. In previous work, we have proposed two ESPRIT-type algorithms, i.e., C-NC Standard ESPRIT and C-NC Unitary ESPRIT, for this scenario that improve the estimation accuracy of the conventional schemes and increase the number of resolvable signals. In this paper, we present a first-order performance assessment of these two ESPRIT-type algorithms. Specifically, we derive closed-form mean square error (MSE) expressions that are asymptotic in the effective signal-to-noise ratio (SNR), i.e., the approximations become exact for either high SNRs or a large sample size. Apart from a zero mean and finite SO moments, no further assumptions on the noise statistics are required. We show that both algorithms perform identical in the high effective SNR regime. Moreover, the analytical results verify the previously observed property that the presence of strictly non-circular sources improves the estimation accuracy of the circular signals.
ISSN:2379-190X
DOI:10.1109/ICASSP.2016.7472214