Multi-Step Knowledge-Aided Iterative MUSIC for Direction Finding using Nested Arrays
Conference: WSA 2019 - 23rd International ITG Workshop on Smart Antennas
04/24/2019 - 04/26/2019 at Vienna, Austria
Proceedings: ITG-Fb. 286: WSA 2019
Pages: 5Language: englishTyp: PDFPersonal VDE Members are entitled to a 10% discount on this title
Pinto, Silvio F. B. (Center for Telecommunications Studies (CETUC), Pontifical Catholic University of Rio de Janeiro, RJ, Brazil)
Lamare, Rodrigo C. de (Center for Telecommunications Studies (CETUC), Pontifical Catholic University of Rio de Janeiro, RJ, Brazil & Department of Electronics, University of York, UK)
In this work, we propose a subspace-based algorithm for direction-of-arrival (DOA) estimation using nested sensor arrays, referred to as multi-step knowledge-aided iterative nested MUSIC method (MS-KAI-MUSIC). Differently from existing knowledge-aided methods applied to uniform linear arrays (ULAs), which make use of available known DOAs to improve the estimation of the covariance matrix of the input data, the proposed MS-KAI-MUSIC employs knowledge of the structure of the augmented sample covariance matrix, which is also obtained by exploiting a difference co-array structure, and the gradual incorporation of prior knowledge, which is obtained on line. Simulations show that MS-KAI-MUSIC significantly outperforms existing techniques.