Multistep Knowledge-Aided Iterative ESPRIT: Design and Analysis

• Published in: IEEE transactions on aerospace and electronic systems Vol. 54; no. 5; pp. 2189 - 2201
• Main Authors: Pinto, Silvio F. B., de Lamare, Rodrigo C.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Arrays; Computational complexity; Computer simulation; Covariance matrices; Covariance matrix; direction finding; Direction of arrival; Direction-of-arrival estimation; Economic models; Error analysis; Estimation; high-resolution parameter estimation; Iterative methods; knowledge-aided techniques; Large sensor arrays; Signal processing algorithms; Signal to noise ratio
• ISSN: 0018-9251; 1557-9603
• DOI: 10.1109/TAES.2018.2811098

In this work, we propose a subspace-based algorithm for direction-of-arrival (DOA) estimation that iteratively reduces the disturbance factors of the estimated data covariance matrix and incorporates prior knowledge which is gradually obtained on line. An analysis of the mean squared error of the reshaped data covariance matrix is carried out along with comparisons between computational complexities of the proposed and existing algorithms. Simulations focusing on closely-spaced sources, where they are uncorrelated and correlated, illustrate the improvements achieved.