An Iterative Dictionary Learning-Based Algorithm for DOA Estimation

This letter proposes a dictionary learning algorithm for solving the grid mismatch problem in direction of arrival (DOA) estimation from both the array sensor data and from the sign of the array sensor data. Discretization of the grid in the sparsity-based DOA estimation algorithms is a problem, whi...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE communications letters 2016-09, Vol.20 (9), p.1784-1787
Hauptverfasser: Zamani, Hojatollah, Zayyani, Hadi, Marvasti, Farrokh
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This letter proposes a dictionary learning algorithm for solving the grid mismatch problem in direction of arrival (DOA) estimation from both the array sensor data and from the sign of the array sensor data. Discretization of the grid in the sparsity-based DOA estimation algorithms is a problem, which leads to a bias error. To compensate this bias error, a dictionary learning technique is suggested, which is based on minimizing a suitable cost function. We also propose an algorithm for the estimation of DOA from the sign of the measurements. It extends the iterative method with adaptive thresholding algorithm to the 1-b compressed sensing framework. Simulation results show the effectiveness of the dictionary learning-based algorithms in comparison with the counterpart algorithms in DOA estimation both from the sensors' data and from the sign of the sensors' data.
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2016.2587674