Efficient joint two-dimensional angle and polarization estimation with crossed dipoles

Chun-Hung Lin, Wen Hsien Fang, Yie Tarng Chen

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

Abstract

This paper addresses a fast algorithm for joint estimation of the two-dimensional (2-D) angles and polarization of the impinging signals based on a novel hierarchical spacetime decomposition (HSTD) technique. The proposed algorithm makes use of a sequence of one-dimensional (1-D) Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithms to estimate these parameters alternatively in a hierarchical tree structure. Furthermore, a spatial beamforming process is invoked in between the 1-D ESPRIT algorithms to progressively partition signals into finer groups to enhance the estimation accuracy and to mitigate the contaminated noise. With such an ingenious tree-structured estimation scheme, the pairing of these parameters is automatically determined without extra hardware or computational cost. Simulation results show that the new algorithm provides satisfactory performance but calls for drastically reduced computations compared with previous works.

Original languageEnglish
Title of host publicationICICS 2009 - Conference Proceedings of the 7th International Conference on Information, Communications and Signal Processing
DOIs
Publication statusPublished - 2009 Dec 1
Event7th International Conference on Information, Communications and Signal Processing, ICICS 2009 - Macau Fisherman's Wharf, Macao
Duration: 2009 Dec 82009 Dec 10

Publication series

NameICICS 2009 - Conference Proceedings of the 7th International Conference on Information, Communications and Signal Processing

Other

Other7th International Conference on Information, Communications and Signal Processing, ICICS 2009
Country/TerritoryMacao
CityMacau Fisherman's Wharf
Period09-12-0809-12-10

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

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