A MSWF root‐MUSIC based on Pseudo‐noise resampling technique
Abstract This paper uses the shift‐invariance property of uniform linear array in root‐MUSIC estimator for obtaining signal and noise subspaces by applying multistage Wiener filter (MSWF) procedure. Also, the MSWF root‐MUSIC based on the pseudo‐noise resampling process for estimating the direction o...
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Series: | Electronics Letters |
Online Access: | https://doi.org/10.1049/ell2.12220 |
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doaj-72534487e68d4a9fb3aaf9b29953e7ae2021-08-11T03:06:51ZengWileyElectronics Letters0013-51941350-911X2021-08-01571767567810.1049/ell2.12220A MSWF root‐MUSIC based on Pseudo‐noise resampling techniqueM. Johnny0M. R. Aref1Department of electrical Engineering Islamic Azad University, Science and Research Branch Tehran IranDepartment of electrical Engineering Sharif University of Technology Tehran IranAbstract This paper uses the shift‐invariance property of uniform linear array in root‐MUSIC estimator for obtaining signal and noise subspaces by applying multistage Wiener filter (MSWF) procedure. Also, the MSWF root‐MUSIC based on the pseudo‐noise resampling process for estimating the direction of arrival (DOA) of signals is proposed. By this process, a root estimator bank and a corresponding DOA estimator bank are constructed. Then, a hypothesis test is applied to the DOA estimator bank to detect the normal DOA estimators from abnormal DOA estimators called outliers. By averaging the corresponding root estimators of normal DOA estimators, the final DOAs can be determined more accurately. When all the DOA estimators fail to pass the hypothesis test, the criterion based on the Gaussian weight average of the root estimator bank is introduced. By applying this criterion, better outlier‐free performance of MSWF root‐MUSIC can be obtained. Simulations show that our method can improve the DOA estimations, especially in small sample sizes and low signal‐to‐noise ratios.https://doi.org/10.1049/ell2.12220 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
M. Johnny M. R. Aref |
spellingShingle |
M. Johnny M. R. Aref A MSWF root‐MUSIC based on Pseudo‐noise resampling technique Electronics Letters |
author_facet |
M. Johnny M. R. Aref |
author_sort |
M. Johnny |
title |
A MSWF root‐MUSIC based on Pseudo‐noise resampling technique |
title_short |
A MSWF root‐MUSIC based on Pseudo‐noise resampling technique |
title_full |
A MSWF root‐MUSIC based on Pseudo‐noise resampling technique |
title_fullStr |
A MSWF root‐MUSIC based on Pseudo‐noise resampling technique |
title_full_unstemmed |
A MSWF root‐MUSIC based on Pseudo‐noise resampling technique |
title_sort |
mswf root‐music based on pseudo‐noise resampling technique |
publisher |
Wiley |
series |
Electronics Letters |
issn |
0013-5194 1350-911X |
publishDate |
2021-08-01 |
description |
Abstract This paper uses the shift‐invariance property of uniform linear array in root‐MUSIC estimator for obtaining signal and noise subspaces by applying multistage Wiener filter (MSWF) procedure. Also, the MSWF root‐MUSIC based on the pseudo‐noise resampling process for estimating the direction of arrival (DOA) of signals is proposed. By this process, a root estimator bank and a corresponding DOA estimator bank are constructed. Then, a hypothesis test is applied to the DOA estimator bank to detect the normal DOA estimators from abnormal DOA estimators called outliers. By averaging the corresponding root estimators of normal DOA estimators, the final DOAs can be determined more accurately. When all the DOA estimators fail to pass the hypothesis test, the criterion based on the Gaussian weight average of the root estimator bank is introduced. By applying this criterion, better outlier‐free performance of MSWF root‐MUSIC can be obtained. Simulations show that our method can improve the DOA estimations, especially in small sample sizes and low signal‐to‐noise ratios. |
url |
https://doi.org/10.1049/ell2.12220 |
work_keys_str_mv |
AT mjohnny amswfrootmusicbasedonpseudonoiseresamplingtechnique AT mraref amswfrootmusicbasedonpseudonoiseresamplingtechnique AT mjohnny mswfrootmusicbasedonpseudonoiseresamplingtechnique AT mraref mswfrootmusicbasedonpseudonoiseresamplingtechnique |
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1721211712765427712 |