Direction-of-arrival estimation with single-RF ESPAR antennas via sparse signal reconstruction

Rongrong Qian, Mathini Sellathurai, Jonathon Chambers

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationIEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2015
PublisherIEEE
Pages485-489
Number of pages5
ISBN (Print)9781479919307
DOIs
Publication statusPublished - Aug 2015
Event16th IEEE International Workshop on Signal Processing Advances in Wireless Communications 2015 - Stockholm, Sweden
Duration: 28 Jun 20151 Jul 2015

Conference

Conference16th IEEE International Workshop on Signal Processing Advances in Wireless Communications 2015
Abbreviated titleSPAWC 2015
Country/TerritorySweden
CityStockholm
Period28/06/151/07/15

Keywords

  • compressive sensing
  • DoA estimation
  • ESPAR
  • sparsity

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Information Systems

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