Iterative DOA Estimation Using Subspace Tracking Methods and Adaptive Beamforming
Summary :
To understand radio propagation structures and consider signal recovering techniques in mobile communications, it is most effective to estimate the signal parameters (e.g., DOA) of individual incoming waves. Also, in radar systems, it is required to discriminate the desired signal from interference. As one of the high-resolution DOA estimators, MUSIC and ESPRIT have attracted considerable attention in recent years. They need the eigenvectors of the correlation matrix and therefore we have to execute the EVD (eigenvalue decomposition) of correlation matrix. However, the EVD generally brings us a heavy computational load and as a result it is difficult to realize the real-time DOA estimator, which will be useful as a multibeam-forming algorithm for adaptive antennas. This paper focuses on MUSIC and ESPRIT using subspace tracking methods, such as BiSVD, PAST, and PASTd, to carry out iterative DOA estimation. Then, they are compared through computer simulation. Adaptive beamforming based on DCMP and MLM is also mentioned and an example is shown.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E88-B No.5 pp.1818-1828
- Publication Date
- 2005/05/01
- Publicized
- Online ISSN
- DOI
- 10.1093/ietcom/e88-b.5.1818
- Type of Manuscript
- Special Section INVITED PAPER (Special Section on Recent Progress in Antennas and Propagation Researches--Selected Papers Translated from the IEICE Transactions on Communications (Japanese Edition)--)
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Nobuyoshi KIKUMA, "Iterative DOA Estimation Using Subspace Tracking Methods and Adaptive Beamforming" in IEICE TRANSACTIONS on Communications,
vol. E88-B, no. 5, pp. 1818-1828, May 2005, doi: 10.1093/ietcom/e88-b.5.1818.
Abstract: To understand radio propagation structures and consider signal recovering techniques in mobile communications, it is most effective to estimate the signal parameters (e.g., DOA) of individual incoming waves. Also, in radar systems, it is required to discriminate the desired signal from interference. As one of the high-resolution DOA estimators, MUSIC and ESPRIT have attracted considerable attention in recent years. They need the eigenvectors of the correlation matrix and therefore we have to execute the EVD (eigenvalue decomposition) of correlation matrix. However, the EVD generally brings us a heavy computational load and as a result it is difficult to realize the real-time DOA estimator, which will be useful as a multibeam-forming algorithm for adaptive antennas. This paper focuses on MUSIC and ESPRIT using subspace tracking methods, such as BiSVD, PAST, and PASTd, to carry out iterative DOA estimation. Then, they are compared through computer simulation. Adaptive beamforming based on DCMP and MLM is also mentioned and an example is shown.
URL: https://global.ieice.org/en_transactions/communications/10.1093/ietcom/e88-b.5.1818/_p
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@ARTICLE{e88-b_5_1818,
author={Nobuyoshi KIKUMA, },
journal={IEICE TRANSACTIONS on Communications},
title={Iterative DOA Estimation Using Subspace Tracking Methods and Adaptive Beamforming},
year={2005},
volume={E88-B},
number={5},
pages={1818-1828},
abstract={To understand radio propagation structures and consider signal recovering techniques in mobile communications, it is most effective to estimate the signal parameters (e.g., DOA) of individual incoming waves. Also, in radar systems, it is required to discriminate the desired signal from interference. As one of the high-resolution DOA estimators, MUSIC and ESPRIT have attracted considerable attention in recent years. They need the eigenvectors of the correlation matrix and therefore we have to execute the EVD (eigenvalue decomposition) of correlation matrix. However, the EVD generally brings us a heavy computational load and as a result it is difficult to realize the real-time DOA estimator, which will be useful as a multibeam-forming algorithm for adaptive antennas. This paper focuses on MUSIC and ESPRIT using subspace tracking methods, such as BiSVD, PAST, and PASTd, to carry out iterative DOA estimation. Then, they are compared through computer simulation. Adaptive beamforming based on DCMP and MLM is also mentioned and an example is shown.},
keywords={},
doi={10.1093/ietcom/e88-b.5.1818},
ISSN={},
month={May},}
Copy
TY - JOUR
TI - Iterative DOA Estimation Using Subspace Tracking Methods and Adaptive Beamforming
T2 - IEICE TRANSACTIONS on Communications
SP - 1818
EP - 1828
AU - Nobuyoshi KIKUMA
PY - 2005
DO - 10.1093/ietcom/e88-b.5.1818
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E88-B
IS - 5
JA - IEICE TRANSACTIONS on Communications
Y1 - May 2005
AB - To understand radio propagation structures and consider signal recovering techniques in mobile communications, it is most effective to estimate the signal parameters (e.g., DOA) of individual incoming waves. Also, in radar systems, it is required to discriminate the desired signal from interference. As one of the high-resolution DOA estimators, MUSIC and ESPRIT have attracted considerable attention in recent years. They need the eigenvectors of the correlation matrix and therefore we have to execute the EVD (eigenvalue decomposition) of correlation matrix. However, the EVD generally brings us a heavy computational load and as a result it is difficult to realize the real-time DOA estimator, which will be useful as a multibeam-forming algorithm for adaptive antennas. This paper focuses on MUSIC and ESPRIT using subspace tracking methods, such as BiSVD, PAST, and PASTd, to carry out iterative DOA estimation. Then, they are compared through computer simulation. Adaptive beamforming based on DCMP and MLM is also mentioned and an example is shown.
ER -
English
