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Translated title of the contribution: A novel approach based on data extrapolation for high resolution direction of arrival estimation

Özgür Gültekin*, Işin Erer

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this work we propose an approach for the direction of arrival (DOA) estimation problem which increases the performance of subspace algorithms . The approach is based on the extrapolation of the data matrix using an autoregressive model. In the proposed method, the AR coefficients are calculated using least square lattice (LSL) structure. In low signal to noise levels the coefficients steming from the LSL structure enable a more efficient modeling of subspaces. Via simulations, it is shown that the estimation performance of subspace algorithms is enhanced compared to non-extrapolated data based estimation and other extrapolated data based estimation methods mentioned in the literature.

Translated title of the contributionA novel approach based on data extrapolation for high resolution direction of arrival estimation
Original languageTurkish
Title of host publication2008 IEEE 16th Signal Processing, Communication and Applications Conference, SIU
DOIs
Publication statusPublished - 2008
Event2008 IEEE 16th Signal Processing, Communication and Applications Conference, SIU - Aydin, Turkey
Duration: 20 Apr 200822 Apr 2008

Publication series

Name2008 IEEE 16th Signal Processing, Communication and Applications Conference, SIU

Conference

Conference2008 IEEE 16th Signal Processing, Communication and Applications Conference, SIU
Country/TerritoryTurkey
CityAydin
Period20/04/0822/04/08

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