DocumentCode :
1914276
Title :
Direction-of-arrival estimation with single-RF ESPAR antennas via sparse signal reconstruction
Author :
Rongrong Qian ; Sellathurai, Mathini ; Chambers, Jonathon
Author_Institution :
Sch. of Eng. & Phys. Sci., Heriot-Watt Univ., Edinburgh, UK
fYear :
2015
fDate :
June 28 2015-July 1 2015
Firstpage :
485
Lastpage :
489
Abstract :
In this paper, a direction-of-arrival (DoA) estimation method based on compressive sensing is proposed for an electronically steerable parasitic array radiator (ESPAR) antenna, which uses only a single radio frequency (RF) chain, and is thereby suited for application in compact wireless terminals. Unlike a conventional multi-active antenna array, signals impinging on parasitic elements in an ESPAR array cannot be processed, and only the output of the sole active element can be processed. In this context, for an ESPAR array, a sparse representation of the DoA estimation problem is formulated by first using an overcomplete dictionary composed of samples from the array manifold and then projecting them onto a set of directional beampatterns. The projection matrix is designed to divide the angle space of the receive antenna array into sectors which are accessed via their corresponding sector beampatterns formed on a time division basis. The sparse signal spectrum is reconstructed by the l1-SVD (singular value decomposition) method [1], where the sparsity is enforced by the l1-norm penalty. Simulation results are presented to demonstrate the efficiency of the proposed method.
Keywords :
antenna arrays; compressed sensing; direction-of-arrival estimation; signal reconstruction; singular value decomposition; DoA estimation method; SVD method; compressive sensing; direction-of-arrival estimation; electronically steerable parasitic array radiator antenna; radio frequency chain; single-RF ESPAR antennas; singular value decomposition method; sparse signal reconstruction; sparse signal spectrum; Antenna arrays; Arrays; Direction-of-arrival estimation; Estimation; Receiving antennas; Signal processing algorithms; DoA estimation; ESPAR; compressive sensing; sparsity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Advances in Wireless Communications (SPAWC), 2015 IEEE 16th International Workshop on
Conference_Location :
Stockholm
Type :
conf
DOI :
10.1109/SPAWC.2015.7227085
Filename :
7227085
Link To Document :
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