Asymptotic Analysis of the Total Least Squares ESPRIT Algorithm
1989 (English)In: Proceedings of the 33rd SPIE International Technical Symposium: Advanced Algorithms and Architectures for Signal Processing, 1989, 146-157 p.Conference paper (Refereed)
This paper considers the problem of estimating the parameters of multiple narrowband signals arriving at an array of sensors. Modern approaches to this problem often involve costly procedures for calculating the estimates. The ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm was recently proposed as a means for obtaining accurate estimates without requiring a costly search of the parameter space. This method utilizes an array invariance to arrive at a computationally efficient multidimensional estimation procedure. Herein, the asymptotic distribution of the estimation error is derived for the Total Least Squares (TLS) version of ESPRIT. The Cramer-Rao Bound (CRB) for the ESPRIT problem formulation is also derived and found to coincide with the variance of the asymptotic distribution through numerical examples. The method is also compared to least squares ESPRIT and MUSIC as well as to the CRB for a calibrated array. Simulations indicate that the theoretic expressions can be used to accurately predict the performance of the algorithm.
Place, publisher, year, edition, pages
1989. 146-157 p.
Asymptotic analysis, ESPRIT algorithm, Cramer-Rao Bound
IdentifiersURN: urn:nbn:se:liu:diva-100542DOI: 10.1117/12.962273OAI: oai:DiVA.org:liu-100542DiVA: diva2:663059
33rd SPIE International Technical Symposium, August, 1989, San Diego, USA