Performance analysis of ESPRIT-type algorithms for strictly non-circular sources using structured least squares | IEEE Conference Publication | IEEE Xplore

Performance analysis of ESPRIT-type algorithms for strictly non-circular sources using structured least squares


Abstract:

This paper presents a first-order analytical performance assessment of the 1-D non-circular (NC) Standard ESPRIT and the 1-D NC Unitary ESPRIT algorithms both using struc...Show More

Abstract:

This paper presents a first-order analytical performance assessment of the 1-D non-circular (NC) Standard ESPRIT and the 1-D NC Unitary ESPRIT algorithms both using structured least squares (SLS) to solve the set of augmented shift invariance equations. These high-resolution parameter estimation algorithms were designed for strictly second-order (SO) non-circular sources and provide a reduced estimation error as well as an increased identifiability of twice as many sources. Our results are based on a first-order approximation of the estimation error that is explicit in the noise realizations and asymptotic in the effective signal-to-noise ratio (SNR), i.e., the approximation becomes exact for either high SNRs or a large sample size. We also find mean squared error (MSE) expressions, where only the assumptions of a zero mean and finite SO moments of the noise are required. Simulations show that the asymptotic performance of both algorithms is asymptotically identical in the high effective SNR.
Date of Conference: 15-18 December 2013
Date Added to IEEE Xplore: 20 January 2014
ISBN Information:
Conference Location: St. Martin, France

References

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