Blind Separation for Estimation of Near-Surface Interface by GPR with Time-Frequency Distribution
Summary :
In this paper, the time-frequency separation algorithm (TFS) proposed by Belouchrani and Amin is applied to ground penetrating radar (GPR) data to reduce ground clutter, that hides reflected waves from a near-surface planar interface. We formulated the problem with several assumptions so that narrow band signals, whose center frequency and baseband signal depend on propagation paths, are received at the receiver, when a wideband signal is radiated from a transmitter. These phenomena can be clearly seen in time-frequency distribution (TFD) of the received signal. In this paper, we adopted the TFS utilizing the TFD signature as a blind separation technique to separate the ground clutter from the target signals. We show numerical and experimental results in order to verify the validity of the problem formulation and the TFS. We carried out GPR measurements to measure permafrost in Yakutsk, Russia. We found the difference in TFD signatures between the ground clutter and the target signal in the experimental data. We could detect the upper boundary of the permafrost with the TFS in spite of the unstable ground clutter.
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- IEICE TRANSACTIONS on Communications Vol.E86-B No.10 pp.3071-3081
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- 2003/10/01
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Satoshi EBIHARA, "Blind Separation for Estimation of Near-Surface Interface by GPR with Time-Frequency Distribution" in IEICE TRANSACTIONS on Communications,
vol. E86-B, no. 10, pp. 3071-3081, October 2003, doi: .
Abstract: In this paper, the time-frequency separation algorithm (TFS) proposed by Belouchrani and Amin is applied to ground penetrating radar (GPR) data to reduce ground clutter, that hides reflected waves from a near-surface planar interface. We formulated the problem with several assumptions so that narrow band signals, whose center frequency and baseband signal depend on propagation paths, are received at the receiver, when a wideband signal is radiated from a transmitter. These phenomena can be clearly seen in time-frequency distribution (TFD) of the received signal. In this paper, we adopted the TFS utilizing the TFD signature as a blind separation technique to separate the ground clutter from the target signals. We show numerical and experimental results in order to verify the validity of the problem formulation and the TFS. We carried out GPR measurements to measure permafrost in Yakutsk, Russia. We found the difference in TFD signatures between the ground clutter and the target signal in the experimental data. We could detect the upper boundary of the permafrost with the TFS in spite of the unstable ground clutter.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e86-b_10_3071/_p
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@ARTICLE{e86-b_10_3071,
author={Satoshi EBIHARA, },
journal={IEICE TRANSACTIONS on Communications},
title={Blind Separation for Estimation of Near-Surface Interface by GPR with Time-Frequency Distribution},
year={2003},
volume={E86-B},
number={10},
pages={3071-3081},
abstract={In this paper, the time-frequency separation algorithm (TFS) proposed by Belouchrani and Amin is applied to ground penetrating radar (GPR) data to reduce ground clutter, that hides reflected waves from a near-surface planar interface. We formulated the problem with several assumptions so that narrow band signals, whose center frequency and baseband signal depend on propagation paths, are received at the receiver, when a wideband signal is radiated from a transmitter. These phenomena can be clearly seen in time-frequency distribution (TFD) of the received signal. In this paper, we adopted the TFS utilizing the TFD signature as a blind separation technique to separate the ground clutter from the target signals. We show numerical and experimental results in order to verify the validity of the problem formulation and the TFS. We carried out GPR measurements to measure permafrost in Yakutsk, Russia. We found the difference in TFD signatures between the ground clutter and the target signal in the experimental data. We could detect the upper boundary of the permafrost with the TFS in spite of the unstable ground clutter.},
keywords={},
doi={},
ISSN={},
month={October},}
Copy
TY - JOUR
TI - Blind Separation for Estimation of Near-Surface Interface by GPR with Time-Frequency Distribution
T2 - IEICE TRANSACTIONS on Communications
SP - 3071
EP - 3081
AU - Satoshi EBIHARA
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E86-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2003
AB - In this paper, the time-frequency separation algorithm (TFS) proposed by Belouchrani and Amin is applied to ground penetrating radar (GPR) data to reduce ground clutter, that hides reflected waves from a near-surface planar interface. We formulated the problem with several assumptions so that narrow band signals, whose center frequency and baseband signal depend on propagation paths, are received at the receiver, when a wideband signal is radiated from a transmitter. These phenomena can be clearly seen in time-frequency distribution (TFD) of the received signal. In this paper, we adopted the TFS utilizing the TFD signature as a blind separation technique to separate the ground clutter from the target signals. We show numerical and experimental results in order to verify the validity of the problem formulation and the TFS. We carried out GPR measurements to measure permafrost in Yakutsk, Russia. We found the difference in TFD signatures between the ground clutter and the target signal in the experimental data. We could detect the upper boundary of the permafrost with the TFS in spite of the unstable ground clutter.
ER -
English
