The Experts below are selected from a list of 12015 Experts worldwide ranked by ideXlab platform
Zhimin Zhou - One of the best experts on this subject based on the ideXlab platform.
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extraction of Landmine features using a forward looking ground penetrating radar with mimo array
IEEE Transactions on Geoscience and Remote Sensing, 2012Co-Authors: Zhimin ZhouAbstract:A vehicle-mounted forward-looking ground-penetrating radar (GPR) with multiple-input and multiple-output (MIMO) array can obtain the high-resolution image of its front area to perform the standoff detection of Landmines. The major challenge for the GPR Landmine detection over wide areas is the very high false alarm rate when maintaining a high detection probability. In this paper, a novel feature extraction method is proposed to obtain the bistatic scattering information from the MIMO array image to discriminate Landmines from clutter. To realize the goal, an imaging model of the MIMO array is firstly developed. Based on the imaging model, the bistatic scattering function of a suspected object is estimated from its MIMO array image using the space-wavenumber processing. Images of different incident angles and bistatic angles at some resonance frequencies are selected from the estimated bistatic scattering function to represent the scattering characteristics. In order to obtain the scale, rotation, and translation invariant feature vector, Hu moment invariants of the selected images are calculated to form the low-dimensional feature vector. The experimental results show that the proposed method can offer an efficient feature vector for the Landmine discriminator to improve the detection performance.
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UWB SAR Landmine Feature Extraction via a Scale Space Method
2012 Second International Conference on Intelligent System Design and Engineering Application, 2012Co-Authors: Zhimin ZhouAbstract:Ultra wide band synthetic aperture radar(UWB SAR) is an alternative way to detect Landmines because of its ground-penetrating capability. In this paper, a UWB SAR Landmine feature extraction method via a scale space method is proposed, based on witch an efficient feature vector is obtained to discriminate Landmines from clutter. The real date results show the validity of the new method.
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Landmine feature extraction in UWB SAR based on sparse representation
2012 International Conference on Image Analysis and Signal Processing, 2012Co-Authors: Zhimin ZhouAbstract:Ultrawide Band Synthetic Aperture Radar (UWB SAR) is an alternative to detect Landmines. The echo of a Landmine has “double-hump” signature, which corresponds to the returns of front and rear edges of the top of the Landmine. However, their echo traces do not fit with the corresponding integral traces of the SAR imaging model, which can lead to defocusing in the SAR image. In this paper, we construct two dictionaries for the front peak and rear peak, respectively. Then we find the optimally sparse representation of each peak of the double-hump signature via basis pursuit algorithm. The results of the real data experiment show the validity of the method.
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Landmine detection using FLGPVAR images
2011Co-Authors: Qian Song, Zhimin ZhouAbstract:Landmine detection is a challenging problem remains to be solved. Forward-Looking Ground Penetrating Virtual Aperture Radar (FLGPVAR) is a popular method to detect Landmines that are made of plastic or have little metal content. And Landmine detection using FLGPVAR is actually an object recognition problem. This paper proposes to use the AdaBoost algorithm added with feature selection in the iterations. The motivation comes from the fact that the feature selection can decrease the training error and increase the margins of training data. And the training error is divided into the probability and the false alarm rate. Minimizing the false alarm rate with constant probability of detection can decrease the probability of missing in the testing data. Experiment results based on clutter lane data collected at a test site corroborate the effectiveness of the proposed classification algorithm to increase the accuracy for Landmine detection.
Jean Marc Sabatier - One of the best experts on this subject based on the ideXlab platform.
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nonlinear acoustic techniques for Landmine detection
Journal of the Acoustical Society of America, 2004Co-Authors: Murray S. Korman, Jean Marc SabatierAbstract:Measurements of the top surface vibration of a buried (inert) VS 2.2 anti-tank plastic Landmine reveal significant resonances in the frequency range between 80 and 650 Hz. Resonances from measurements of the normal component of the acoustically induced soil surface particle velocity (due to sufficient acoustic-to-seismic coupling) have been used in detection schemes. Since the interface between the top plate and the soil responds nonlinearly to pressure fluctuations, characteristics of Landmines, the soil, and the interface are rich in nonlinear physics and allow for a method of buried Landmine detection not previously exploited. Tuning curve experiments (revealing “softening” and a back-bone curve linear in particle velocity amplitude versus frequency) help characterize the nonlinear resonant behavior of the soil-Landmine oscillator. The results appear to exhibit the characteristics of nonlinear mesoscopic elastic behavior, which is explored. When two primary waves f1 and f2 drive the soil over the mine ...
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Laser doppler vibrometer-based acoustic Landmine detection using the fast M-sequence transform
IEEE Geoscience and Remote Sensing Letters, 2004Co-Authors: Ning Xiang, Jean Marc SabatierAbstract:Acoustic Landmine detection using a laser Doppler vibrometer (LDV) has demonstrated success in recent field tests. However, low detector signals and speckle noise are still challenging problems in the LDV-based acoustic-to-seismic detection of buried Landmines. This letter describes the use of binary maximum-length sequences as the acoustic excitation for achieving high SNRs of scanning results. Some relevant issues associated with the detection system design and experimental field results are discussed.
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Nonlinear acoustic techniques for Landmine detection
The Journal of the Acoustical Society of America, 2004Co-Authors: Murray S. Korman, Jean Marc SabatierAbstract:Measurements of the top surface vibration of a buried ?inert? VS 2.2 anti-tank plastic Landmine reveal significant resonances in the frequency range between 80 and 650 Hz. Resonances from measurements of the normal component of the acoustically induced soil surface particle velocity ?due to sufficient acoustic-to-seismic coupling? have been used in detection schemes. Since the interface between the top plate and the soil responds nonlinearly to pressure fluctuations, characteristics of Landmines, the soil, and the interface are rich in nonlinear physics and allow for a method of buried Landmine detection not previously exploited. Tuning curve experiments ?revealing ‘‘softening’’ and a back-bone curve linear in particle velocity amplitude versus frequency? help characterize the nonlinear resonant behavior of the soil-Landmine oscillator. The results appear to exhibit the characteristics of nonlinear mesoscopic elastic behavior, which is explored. When two primary waves f1 and f2 drive the soil over the mine near resonance, a rich spectrum of nonlinearly generated tones is measured with a geophone on the surface over the buried Landmine in agreement with Donskoy ?SPIE Proc. 3392, 221–217 ?1998?; 3710, 239–246 ?1999??. In profiling, particular nonlinear tonals can improve the contrast ratio compared to using either primary tone in the spectrum.
Motoyuki Sato - One of the best experts on this subject based on the ideXlab platform.
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CMP Antenna Array GPR and Signal-to-Clutter Ratio Improvement
IEEE Geoscience and Remote Sensing Letters, 2009Co-Authors: Xuan Feng, Motoyuki Sato, Yan Zhang, Cai Liu, Fusheng Shi, Yonghui ZhaoAbstract:Ground-penetrating radar (GPR) is recognized as a promising sensor for detecting buried Landmines. In this case, the GPR antenna(s) must be elevated above the ground. However, this requirement results in heavy surface clutter. It is therefore necessary to overcome the effect. A commonly used procedure of time gating and background averaging cannot suit to small shallow nonmetallic Landmine beneath a rough ground surface. In this letter, we proposed techniques to enhance the target signal through common midpoint (CMP) antenna array and data processing techniques, including velocity spectrum and CMP multifold stacking. The method has been tested using experiment data over a rough ground under which small plastic antipersonnel Landmines is shallowly buried. The result shows the signal-to-clutter ratio was dramatically improved.
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investigation of time frequency features for gpr Landmine discrimination
IEEE Transactions on Geoscience and Remote Sensing, 2007Co-Authors: T G Savelyev, L Van Kempen, Hichem Sahli, Jurgen Sachs, Motoyuki SatoAbstract:Ground-penetrating radar (GPR) is capable to detect plastic antipersonnel Landmines as well as other subsurface targets. In order to reduce false alarms, an option of automatic Landmine discrimination from neutral minelike targets would be very useful. This paper presents a possibility for such discrimination and analyzes it experimentally. The authors investigate time-frequency features of an ultrawideband (UWB) target response for the discrimination between buried Landmines and other objects. The discrimination method includes the extraction of an early-time target impulse response, its time-frequency transformation, and the extraction of time-frequency features based on a singular value decomposition of the transformed image. In order to take into account the changes in the UWB target signals, the experimental conditions are completely controlled to focus on the behavior of the target's response with respect to its depth and the horizontal position of the GPR above it. The dependence of the features on the GPR bandwidth is analyzed as well. The Mahalanobis distance is used as a criterion for optimal discrimination. The obtained results define the best features and conditions when the Landmine discrimination is successful. For comparison, the discriminant power of the proposed features has been tested on a dataset, acquired during a field campaign in Angola
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pre stack migration applied to gpr for Landmine detection
Inverse Problems, 2004Co-Authors: Xuan Feng, Motoyuki SatoAbstract:Detection of buried Landmines by ground penetrating radar (GPR) normally suffers from very strong clutter that will decrease the image quality in GPR data. Problems are also encountered when imaging steeply dipping Landmines by GPR. To solve these problems, we have developed a stepped-frequency continuous-wave array antenna ground penetrating radar system, called SAR-GPR, that can acquire common middle point multi-offset data. As an approximate solution to the general wavefield inversion problem, migration algorithms were used to refocus the scattered Landmine information to improve signal–clutter ratio and re-construct the Landmine image. Also, pre-stack migration was found to efficiently deal with the steeply dipping Landmine problem. Before migration processing, subtracting antenna coupling was used. The SAR-GPR system was tested under two conditions. The first condition is designed to simulate inhomogeneous soil under rough ground conditions and the second condition is to simulate steeply dipping buried Landmine. Very strong clutter in the GPR data was exhibited in the first condition. After pre-stack migration, strong clutter was efficiently suppressed and a high quality Landmine image was re-constructed in both experiments.
Massimo Zucchetti - One of the best experts on this subject based on the ideXlab platform.
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A survey of Landmine detection using hyperspectral imaging
ISPRS Journal of Photogrammetry and Remote Sensing, 2017Co-Authors: Imad Makki, Clovis Francis, Tiziano Bianchi, Rafic Younes, Massimo ZucchettiAbstract:Hyperspectral imaging is a trending technique in remote sensing that finds its application in many different areas, such as agriculture, mapping, target detection, food quality monitoring, etc. This technique gives the ability to remotely identify the composition of each pixel of the image. Therefore, it is a natural candidate for the purpose of Landmine detection, thanks to its inherent safety and fast response time. In this paper, we will present the results of several studies that employed hyperspectral imaging for the purpose of Landmine detection, discussing the different signal processing techniques used in this framework for hyperspectral image processing and target detection. Our purpose is to highlight the progresses attained in the detection of Landmines using hyperspectral imaging and to identify possible perspectives for future work, in order to achieve a better detection in real-time operation mode.
Olga Lopera - One of the best experts on this subject based on the ideXlab platform.
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prediction of the effects of soil and target properties on the antipersonnel Landmine detection performance of ground penetrating radar a colombian case study
Journal of Applied Geophysics, 2007Co-Authors: Olga Lopera, Nada MilisavljevicAbstract:The performance of ground-penetrating (GPR) radar is determined fundamentally by the soil electromagnetic (EM) properties and the target characteristics. In this paper, we predict the effects of such properties on the antipersonnel (AP) Landmine detection performance of GPR in a Colombian scenario. Firstly, we use available soil geophysical information in existing pedotransfer models to calculate soil EM properties. The latter are included in a two-dimensional (21)), finite-difference time-domain (FDTD) modeling program in conjunction with the characteristics of AP Landmines to calculate the buried target reflection. The approach is applied to two soils selected among Colombian mine-affected areas, and several local improvised explosive devices (IEDs) and AP Landmines are modeled as targets. The signatures from such targets buried in the selected soils are predicted, considering different conditions. Finally, we show how the GPR can contribute in detecting Iow- and non-metallic targets in these Colombian soils. Such a system could be quite adequate for complementing humanitarian Landmine detection by metal detectors. (c) 2007 Elsevier B.V. All rights reserved.
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time frequency domain signature analysis of gpr data for Landmine identification
International Workshop on Advanced Ground Penetrating Radar, 2007Co-Authors: Olga Lopera, N Milisavljevie, David J Daniels, Benoit MacqAbstract:In this paper, the problem of detecting buried antipersonnel (AP) Landmines is tackled in the broader context of target identification: determining relevant features, extracted from impulse ground-penetrating radar (GPR) signals, which can be used to classify Landmines. These features are extracted in the time-frequency domain using the Wigner-Ville distribution (WVD) and the wavelet transform (WT). Radar data are collected using the MINEHOUNDTM hand-held dual-sensor system over two types of soil and for different Landmines and objects. The Wilk's lambda value is used as a criterion for optimal discrimination. Results show that time-frequency signatures from WVD contain more valuable information than the features extracted using WT. Therefore, they could improve Landmine and false alarm classification and help to differentiate between two different Landmines.
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filtering soil surface and antenna effects from gpr data to enhance Landmine detection
IEEE Transactions on Geoscience and Remote Sensing, 2007Co-Authors: Olga Lopera, Evert Slob, Nada Milisavljevic, Sebastien LambotAbstract:The detection of antipersonnel Landmines using ground-penetrating radar (GPR) is particularly hindered by the predominant soil surface and antenna reflections. In this paper, we propose a novel approach to filter out these effects from 2-D off-ground monostatic GPR data by adapting and combining the radar antenna subsurface model of Lambot with phase-shift migration. First, the antenna multiple reflections originating from the antenna itself and from the interaction between the antenna and the ground are removed using linear transfer functions. Second, a simulated Green's function accounting for the surface reflection is subtracted. The Green's function is derived from the estimated soil surface dielectric permittivity using full-wave inversion of the radar signal for a measurement taken in a local Landmine-free area. Third, off-ground phase-shift migration is performed on the 2-D data to filter the effect of the antenna radiation pattern. We validate the approach in laboratory conditions for four differently detectable Landmines embedded in a sandy soil. Compared to traditional background subtraction, this new filtering method permits a better differentiation of the Landmine and estimation of its depth and geometrical properties. This is particularly beneficial for the detection of Landmines in low-contrast conditions
