IEICE TRANSACTIONS on Fundamentals
On the Kernel MUSIC Algorithm with a Non-Redundant Spatial Smoothing Technique
Summary :
We propose the Kernel MUSIC algorithm as an improvement over the conventional MUSIC algorithm. This algorithm is based on the orthogonality between the image and kernel space of an Hermitian mapping constructed from the received data. Spatial smoothing, needed to apply the MUSIC algorithm to coherent signals, is interpreted as constructing procedure of the Hermitian mapping into the subspace spanned by the constituent vectors of the received data. We also propose a new spatial smoothing technique which can remove the redundancy included in the image space of the mapping and discuss that the removal of redundancy is essential for improvement of resolution. By computer simulation, we show advantages of the Kernel MUSIC algorithm over the conventional one, that is, the reduction of processing time and improvement of resolution. Finally, we apply the Kernel MUSIC algorithm to the Laser Microvision, an optical misroscope we are developing, and verify that this algorithm has about two times higher resolution than that of the Fourier transform method.
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- IEICE TRANSACTIONS on Fundamentals Vol.E79-A No.8 pp.1225-1231
- Publication Date
- 1996/08/25
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- Type of Manuscript
- Special Section PAPER (Special Section on Digital Signal Processing)
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Hiroshi SHIMOTAHIRA, Fumie TAGA, "On the Kernel MUSIC Algorithm with a Non-Redundant Spatial Smoothing Technique" in IEICE TRANSACTIONS on Fundamentals,
vol. E79-A, no. 8, pp. 1225-1231, August 1996, doi: .
Abstract: We propose the Kernel MUSIC algorithm as an improvement over the conventional MUSIC algorithm. This algorithm is based on the orthogonality between the image and kernel space of an Hermitian mapping constructed from the received data. Spatial smoothing, needed to apply the MUSIC algorithm to coherent signals, is interpreted as constructing procedure of the Hermitian mapping into the subspace spanned by the constituent vectors of the received data. We also propose a new spatial smoothing technique which can remove the redundancy included in the image space of the mapping and discuss that the removal of redundancy is essential for improvement of resolution. By computer simulation, we show advantages of the Kernel MUSIC algorithm over the conventional one, that is, the reduction of processing time and improvement of resolution. Finally, we apply the Kernel MUSIC algorithm to the Laser Microvision, an optical misroscope we are developing, and verify that this algorithm has about two times higher resolution than that of the Fourier transform method.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e79-a_8_1225/_p
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@ARTICLE{e79-a_8_1225,
author={Hiroshi SHIMOTAHIRA, Fumie TAGA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={On the Kernel MUSIC Algorithm with a Non-Redundant Spatial Smoothing Technique},
year={1996},
volume={E79-A},
number={8},
pages={1225-1231},
abstract={We propose the Kernel MUSIC algorithm as an improvement over the conventional MUSIC algorithm. This algorithm is based on the orthogonality between the image and kernel space of an Hermitian mapping constructed from the received data. Spatial smoothing, needed to apply the MUSIC algorithm to coherent signals, is interpreted as constructing procedure of the Hermitian mapping into the subspace spanned by the constituent vectors of the received data. We also propose a new spatial smoothing technique which can remove the redundancy included in the image space of the mapping and discuss that the removal of redundancy is essential for improvement of resolution. By computer simulation, we show advantages of the Kernel MUSIC algorithm over the conventional one, that is, the reduction of processing time and improvement of resolution. Finally, we apply the Kernel MUSIC algorithm to the Laser Microvision, an optical misroscope we are developing, and verify that this algorithm has about two times higher resolution than that of the Fourier transform method.},
keywords={},
doi={},
ISSN={},
month={August},}
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TY - JOUR
TI - On the Kernel MUSIC Algorithm with a Non-Redundant Spatial Smoothing Technique
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1225
EP - 1231
AU - Hiroshi SHIMOTAHIRA
AU - Fumie TAGA
PY - 1996
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E79-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 1996
AB - We propose the Kernel MUSIC algorithm as an improvement over the conventional MUSIC algorithm. This algorithm is based on the orthogonality between the image and kernel space of an Hermitian mapping constructed from the received data. Spatial smoothing, needed to apply the MUSIC algorithm to coherent signals, is interpreted as constructing procedure of the Hermitian mapping into the subspace spanned by the constituent vectors of the received data. We also propose a new spatial smoothing technique which can remove the redundancy included in the image space of the mapping and discuss that the removal of redundancy is essential for improvement of resolution. By computer simulation, we show advantages of the Kernel MUSIC algorithm over the conventional one, that is, the reduction of processing time and improvement of resolution. Finally, we apply the Kernel MUSIC algorithm to the Laser Microvision, an optical misroscope we are developing, and verify that this algorithm has about two times higher resolution than that of the Fourier transform method.
ER -
English
