A feature for classification of shallowly buried landmine-like objects using a ground penetrating radar (GPR) measurement system is proposed and its performance is evaluated. The feature for classification employed here is a time interval between two pulses reflected from top and bottom sides of landmine-like objects. First, we estimate a time resolution required to detect object thickness from GPR data, and check the actual time resolution through laboratory experiment. Next, we evaluate the classification performance using Monte Carlo simulations from dataset generated by a two-dimensional finite difference time domain (FDTD) method. The results show that good classification performance is achieved even for landmine-like objects buried at shallow depths under rough ground surfaces. Furthermore, we also estimate the effects of ground surface roughness, soil inhomogeneity, and target inclination on the classification performance.
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Masahiko NISHIMOTO, Keiichi NAGAYOSHI, Shuichi UENO, Yusuke KIMURA, "Classification of Landmine-Like Objects Buried under Rough Ground Surfaces Using a Ground Penetrating Radar" in IEICE TRANSACTIONS on Electronics,
vol. E90-C, no. 2, pp. 327-333, February 2007, doi: 10.1093/ietele/e90-c.2.327.
Abstract: A feature for classification of shallowly buried landmine-like objects using a ground penetrating radar (GPR) measurement system is proposed and its performance is evaluated. The feature for classification employed here is a time interval between two pulses reflected from top and bottom sides of landmine-like objects. First, we estimate a time resolution required to detect object thickness from GPR data, and check the actual time resolution through laboratory experiment. Next, we evaluate the classification performance using Monte Carlo simulations from dataset generated by a two-dimensional finite difference time domain (FDTD) method. The results show that good classification performance is achieved even for landmine-like objects buried at shallow depths under rough ground surfaces. Furthermore, we also estimate the effects of ground surface roughness, soil inhomogeneity, and target inclination on the classification performance.
URL: https://globals.ieice.org/en_transactions/electronics/10.1093/ietele/e90-c.2.327/_p
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@ARTICLE{e90-c_2_327,
author={Masahiko NISHIMOTO, Keiichi NAGAYOSHI, Shuichi UENO, Yusuke KIMURA, },
journal={IEICE TRANSACTIONS on Electronics},
title={Classification of Landmine-Like Objects Buried under Rough Ground Surfaces Using a Ground Penetrating Radar},
year={2007},
volume={E90-C},
number={2},
pages={327-333},
abstract={A feature for classification of shallowly buried landmine-like objects using a ground penetrating radar (GPR) measurement system is proposed and its performance is evaluated. The feature for classification employed here is a time interval between two pulses reflected from top and bottom sides of landmine-like objects. First, we estimate a time resolution required to detect object thickness from GPR data, and check the actual time resolution through laboratory experiment. Next, we evaluate the classification performance using Monte Carlo simulations from dataset generated by a two-dimensional finite difference time domain (FDTD) method. The results show that good classification performance is achieved even for landmine-like objects buried at shallow depths under rough ground surfaces. Furthermore, we also estimate the effects of ground surface roughness, soil inhomogeneity, and target inclination on the classification performance.},
keywords={},
doi={10.1093/ietele/e90-c.2.327},
ISSN={1745-1353},
month={February},}
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TY - JOUR
TI - Classification of Landmine-Like Objects Buried under Rough Ground Surfaces Using a Ground Penetrating Radar
T2 - IEICE TRANSACTIONS on Electronics
SP - 327
EP - 333
AU - Masahiko NISHIMOTO
AU - Keiichi NAGAYOSHI
AU - Shuichi UENO
AU - Yusuke KIMURA
PY - 2007
DO - 10.1093/ietele/e90-c.2.327
JO - IEICE TRANSACTIONS on Electronics
SN - 1745-1353
VL - E90-C
IS - 2
JA - IEICE TRANSACTIONS on Electronics
Y1 - February 2007
AB - A feature for classification of shallowly buried landmine-like objects using a ground penetrating radar (GPR) measurement system is proposed and its performance is evaluated. The feature for classification employed here is a time interval between two pulses reflected from top and bottom sides of landmine-like objects. First, we estimate a time resolution required to detect object thickness from GPR data, and check the actual time resolution through laboratory experiment. Next, we evaluate the classification performance using Monte Carlo simulations from dataset generated by a two-dimensional finite difference time domain (FDTD) method. The results show that good classification performance is achieved even for landmine-like objects buried at shallow depths under rough ground surfaces. Furthermore, we also estimate the effects of ground surface roughness, soil inhomogeneity, and target inclination on the classification performance.
ER -