Randomized Multiple Candidate Iterative Hard Thresholding Algorithm for Direction of Arrival Estimation

Conference: WSA 2018 - 22nd International ITG Workshop on Smart Antennas
03/14/2018 - 03/16/2018 at Bochum, Deutschland

Proceedings: ITG-Fb. 276: WSA 2018

Pages: 4Language: englishTyp: PDF

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Guzman, Yuneisy E. Garcıa (Pontifical Catholic University of Rio de Janeiro, RJ, Brazil)
Lamare, Rodrigo C. de (Department of Electronics, University of York, UK)
Haardt, Martin (Ilmenau University of Technology, Germany)

The sparse recovery problem by l0 minimization which is of central importance in compressed sensing (CS)-based algorithms for direction of arrival (DoA) estimation has attracted considerable interest recently. This paper proposes a greedy algorithm called randomized multiple candidate iterative hard thresholding (RMC-IHT) which generates a set of potential candidates using the iterative hard thresholding algorithm and selects the best candidate based on the a priori knowledge of the distribution of the signal and noise matrices. We also consider the case of correlated sources and develop a version of RMC-IHT for this scenario. Simulation results illustrate the improvement achieved by RMC-IHT.