Imaging Of Land Mines Research Articles

3D Migration Depth Focus Velocity Analysis of Hand-Held Ground Penetrating Radar

Hand-held ground penetrating radar (GPR) systems have been widely applied to landmine detections during recent decades. The accuracy of an imaging result by migration for a hand-held GPR is strongly related to the accuracy of subsurface velocity distribution obtained from multi offset data. For shallow targets like landmines, the hyperbolas are usually not distinct in 2D slices and are masked by the surface reflections. In this article, we propose a 3D migration depth focus velocity analysis method for hand-held GPRs to estimate the background velocity of the subsurface. This method is performed based on the images generated by migrations. The objective function is defined as the proportion of the target on the depth slice containing the target. After migrating a GPR radargram with different velocities, the background velocity, which minimizes the objective function, can be determined by comparing the imaging results by migration using different velocities. To test the proposed method, we apply this procedure to experimental GPR data collected with an advanced landmine imaging system (ALIS) in the laboratory. Subsequently, the velocity of the background is obtained, 3D diffraction migration with the obtained velocity achieves subsurface imaging with high quality. The accurate position and depth of the target are obtained from the optimal migration image.

Robust landmine detection from thermal image time series using Hough transform and rotationally invariant features

ABSTRACT Automated detection of buried anti-personnel landmines using remote sensing techniques is very important for clearing minefields without putting lives in danger. Although thermal infrared imaging is promising, it is far from applicable to the real world in its current state-of-the-art. The most serious problem is that experiments are generally held using sandboxes or levelled and cleared soil, but real fields are, at least partially, covered with plants. In this study, we present an algorithm for landmine detection that is robust enough to detect beyond the clutter caused by partial plant cover. The first part is a hypothesis generator based on circular Hough Transform applied to images that are filtered to enhance circular structures. The second part tests the candidate landmine coordinates using rotationally invariant features, including modified Histogram of Oriented Gaussians (HOG), over multiple images taken at different times after Wiener filtering to maximize signal-to-clutter ratio. The performances of various features and classifiers are compared. The overall performance of the algorithm is demonstrated on a dataset of real-world landmine images contaminated by simulated plants. Satisfactory results are obtained up to 40% equivalent plant coverage where more than 65% of the pixels are fully or partially covered by plants.

Convexification of restricted Dirichlet-to-Neumann map

Abstract By our definition, “restricted Dirichlet-to-Neumann (DN) map” means that the Dirichlet and Neumann boundary data for a coefficient inverse problem (CIP) are generated by a point source running along an interval of a straight line. On the other hand, the conventional DN data can be generated, at least sometimes, by a point source running along a hypersurface. CIPs with restricted DN data are non-overdetermined in the n-dimensional case, with n ≥ 2 {n\geq 2} . We develop, in a unified way, a general and radically new numerical concept for CIPs with restricted DN data for a broad class of PDEs of second order, such as, e.g., elliptic, parabolic and hyperbolic ones. Namely, using Carleman weight functions, we construct globally convergent numerical methods. Hölder stability and uniqueness are also proved. The price we pay for these features is a well-acceptable one in the numerical analysis, that is, we truncate a certain Fourier-like series with respect to some functions depending only on the position of the point source. At least three applications are imaging of land mines, crosswell imaging and electrical impedance tomography.

Efficient Algorithm Design for GPR Imaging of Landmines

Ground-penetrating radar (GPR) is used to image and detect subterranean objects, for example, in landmine detection. Although full 3-D inversion of GPR measurements is possible for simple algorithms such as backprojection, it is impractical when using more advanced algorithms that involve $\ell_1$ -minimization. Many of the algorithms used for GPR imaging involve the storage, or online generation, of a huge dictionary matrix created from discretizing a high-dimensional nonlinear model. This parametric model includes all the target features that need to be extracted, including 3-D location, object orientation, and target type. As more parameters are added to the model, the dimensionality increases. If uniform sampling is done over high-dimensional parameter space, the size of the dictionary and the complexity of the inversion algorithms rapidly grow, exceeding the capability of real-time processors. This paper shows that strategic structuring of the dictionary, which takes advantage of translational invariance in the model, can reduce the dictionary storage by several orders of magnitude and exploit the fast Fourier transform for fast computation of previously highly impractical, bordering on impossible, 3-D GPR imaging problems.

Hand-Held GPR Imaging Using Migration for Irregular Data

Handheld ground-penetrating radar (GPR) system is one of a number of technologies that has been researched as a means of improving landmine detection efficiency. But it is difficult to display landmine imaging in horizontal slices, because human being operator cannot collect regular GPR data along the survey line and the measurement positions are random. Also detection of buried landmines by GPR normally suffers from very strong clutter that will decrease the image quality. So we proposed two processing procedures to achieve hand-held GPR subsurface imaging. One processing procedure is composed of interpolation and migration algorithm. The interpolation is chosen to produce the regular grid data set. The migration is used to improve signal-clutter ratio and reconstruct subsurface imaging. In the other processing procedure we developed a simply modified migration algorithm that can directly processes irregular GPR data. Two processing procedures, migration with interpolation and modified migration without interpolation, were applied to a field experiment data respectively. Both of processing procedures can efficiently process irregular GPR data and achieve subsurface imaging of high quality. The imaging processed by migration with interpolation is used in the dual sensor, advanced landmine imaging system (ALIS), and two sets of ALIS have detected more than 80 AP-mines since 2009. Also the modified migration algorithm can save the processing time, which is important for field real-time signal processing. We concluded that to achieve clear hand-held GPR imaging, the interpolation is not necessary algorithm and the migration is the key algorithm.

A neutron Albedo system with time rejection for landmine and IED detection

Abstract A neutron Albedo system has been developed for imaging of buried landmines and improvised explosive devices (IEDs). It involves irradiating the ground with fast neutrons and subsequently detecting the thermalized neutrons that return. A scintillating 6Li loaded ZnS(Ag) screen with a sensitive area of 40 cm×40 cm is used as a thermal neutron detector. Scintillation light is captured by orthogonal arrays of wavelength-shifting fibers placed on either side of the scintillator surface and then transferred to X and Y multi-pixel PMTs. A timing circuit, used with pulsed neutron sources, records the time when a neutron detection takes place relative to an external synchronization pulse from the pulsed source. Experimental tests of the Albedo system performance have been done in a sand box with a 252Cf neutron source (no time gating) and with pulsed D–D (2.6 MeV) neutrons from the Defense R&D Ottawa Van de Graaff accelerator (with time gating). Information contained in the time evolution of the thermal neutron field provided improved detection capability and image reconstruction. The detector design is described and experimental results are discussed.

Picosecond scale experimental verification of a globally convergent algorithm for a coefficient inverse problem

A globally convergent algorithm by the first and third authors for a 3D hyperbolic coefficient inverse problem is verified on experimental data measured in the picosecond scale regime. Quantifiable images of dielectric abnormalities are obtained. The total measurement timing of a 100 ps pulse for one detector location was 1.2 ns with 20 ps (=0.02 ns) time step between two consecutive readings. Blind tests have consistently demonstrated an accurate imaging of refractive indexes of dielectric abnormalities. At the same time, it is shown that a modified gradient method is inapplicable to this kind of experimental data. This inverse algorithm is also applicable to other types of imaging modalities, e.g. acoustics. Potential applications are in airport security, imaging of land mines, imaging of defects in non-distractive testing, etc.

Global convergence for a 1-D inverse problem with application to imaging of land mines

A new globally convergent numerical method is developed for a 1-D coefficient inverse problem for a hyperbolic partial differential equation (PDE). The back reflected data are used. A version of the quasi-reversibility method is proposed. A global convergence theorem is proven via a Carleman estimate. The results of numerical experiments are presented.

Detection of Landmines from Acoustic Images Based on Cepstral Coefficients

This paper introduces a cepstral approach for the automatic detection of landmines from acoustic images. This approach is based on treating the problem of landmine detection as a pattern recognition problem. Cepstral features are extracted from a group of landmine images which are transformed first to 1-D signals by lexicographic ordering. Mel frequency cepstral coefficients (MFCCs) and polynomial shaping coefficients are extracted from these 1-D signals to form a database of features, which can be used to train a neural network with the landmine features. The landmine detection can be performed by extracting features from any new image with the same method used in the training phase. These features are tested with the neural network to decide whether a landmine exists or not. The different domains are tested and compared for efficient feature extraction from the lexicographically ordered 1-D signals. Experimental results show the success of the proposed cepstral approach for landmine detection at low as well as high signal to noise ratios. Results also show that the discrete cosine transform is the most appropriate domain for feature extraction.

Numerical implementation of the convexification algorithm for an optical diffusion tomograph

A globally convergent (the so-called convexification) algorithm was previously developed for coefficient inverse problems (CIPs) with the time/frequency-dependent data. In this publication the convexification is extended to the case of a CIP for an elliptic equation with the data generated by the source running along a straight line. The data are incomplete, since they are given only at a part of the boundary. Applications to both electrical impedance and optical tomographies are feasible, which include, in particular, imaging of land mines and underground bunkers, as well as diffuse optical imaging of targets on battlefields through smogs and flames. However, our numerical setup is intended for medical applications to small animals. Numerical experiments in the 2D case are presented.

Imaging of land mines by the globally convergent convexification method using a simplified mathematical model

A new 2-D implementation of the globally convergent convexification numerical method for coefficient inverse problems is described. Based on a simplified mathematical model, numerical results from imaging of targets which mimic antipersonnel land mines demonstrate that the algorithm can detect the location(s) of the inclusion(s) from the background medium, as well as identify the material property of the inclusion(s) and the background. With the ‘tails’ incorporated in the new development, the computational efficiency of the algorithm is dramatically improved relatively to the previous ‘tail-free’ implementation.

Time-frequency analysis for radar classification of land-mine images

We use time-frequency (t-f) analysis techniques to examine the echo returns present in synthetic aperture radar (SAR) images of land-mine fields. A flying platform illuminates a mine field containing various types of mines and confusers, with an ultra-wideband radar. A number of familiar time-frequency distributions are used to inspect the various possible mine locations above and below the ground surface. The 2-dimensional plots generated by these distributions offer a larger variety of features and clues that facilitate the discrimination of each mine from the others and from possible confusers. Conclusions emerge that confirm that the pseudo-Wigner–Ville and the Choi–Williams distributions provide the best discrimination results, as was pointed out in earlier work. Larger mines such as the ones denoted here as type 1 are the easiest to discriminate. Comparison of mines to clutter objects (confusers) shows that such objects are clearly distinguishable from all the present metal mines.

Investigation of microphones as near-ground sensors for seismic detection of buried landmines

Commercially available microphones were investigated as near-ground sensors to measure the acoustic pressure and the vertical pressure gradient of evanescent air-acoustic waves associated with audio-frequency seismic waves. Measurements in close proximity to the surface and the use of waveguides were found to improve the microphone signal's quality, the comparison of its seismic sensitivity to its sensitivity to propagating sound (ambient acoustic noise and nonseismic reverberation). Landmine images formed using microphone data collected in a laboratory experimental model clearly locate buried inert landmines but exhibit more clutter than images of the same objects formed with seismic displacement data collected using other techniques.

Electrical Impedance Tomographic Imaging of Buried Landmines

A prototype confirmation landmine detector, based on electrical impedancetomography (EIT), which can operate under realistic environmental conditions, has been developed. Laboratory and field experiments demonstrated that it is possible to reliably reconstruct, on the scale of the electrode spacing (ES) (in width and depth), conductivity perturbations due to a shallow buried antitank mine or a similar object in a variety of soils (black earth, clay, sand) down to depths equal to the dimensions of the object (1-1.5 ES, equivalent to 14-21 cm for a 64-electrode 1 m times 1 m array). These represent the first EIT images of real landmines computed from measured data. Occasional problems were encountered with the electrical contact in very dry soils, with excessive insertion pressure being required for reliable electrode contact. However, poor contacts could be detected, and the offending probe was either reinserted or compensation was applied. A matched filter detection algorithm based on a replica of the object of interest was developed and shown to effectively reduce the false alarm rate of the detector. EIT is especially suited for wet lands and underwater, where other mine detectors perform poorly. Experiments in a water-and sediment-filled tank have demonstrated that detection of minelike objects in such an environment with a submerged array is feasible. These experiments represent the first EIT measurements of targets using an electrode array submerged underwater. EIT may also have an application in locating intact mines in the berms formed by mine-clearing equipment. The EIT sensor head could be made cheaply enough to be disposable and remotely inserted to improve safety

Ground‐penetrating radar land mine imaging: Two‐dimensional seismic migration and three‐dimensional inverse scattering in layered media

This paper presents two methods for ground‐penetrating radar (GPR) imaging of land mines: a two‐dimensional (2‐D) seismic migration method and a 3‐D nonlinear inverse scattering method. The seismic migration technique has been successfully applied to processing field data sets collected at a test site. The results show that the seismic migration technique is a useful real‐time imaging method. To image the 3‐D structure of the land mine, we have developed a full 3‐D nonlinear inverse scattering algorithm on the basis of the contrast source inversion method. To account for the ground surface and potentially other subsurface layers, the inverse scattering method uses a multilayered medium as a background. Preliminary results demonstrate that the 3‐D inverse scattering method can successfully provide high‐resolution reconstruction of high‐contrast buried objects.

Pre-stack migration applied to GPR for landmine detection

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.

Two numerical methods for an inverse problem for the 2-D Helmholtz equation

Two solution methods for the inverse problem for the 2-D Helmholtz equation are developed, tested, and compared. The proposed approaches are based on a marching finite-difference scheme which requires the solution of an overdetermined system at each step. The preconditioned conjugate gradient method is used for rapid solutions of these systems and an efficient preconditioner has been developed for this class of problems. Underlying target applications include the imaging of land mines, unexploded ordinance, and pollutant plumes in environmental cleanup sites, each formulated as an inverse problem for a 2-D Helmholtz equation. The images represent the electromagnetic properties of the respective underground regions. Extensive numerical results are presented.

Field site evaluation for seismic mine detection

A system has been developed that uses audio-frequency surface seismic waves for the detection and imaging of buried landmines. The system is based on the measurement of seismic displacements immediately above buried mines using noncontacting vibrometers that interrogate the surface motion with either radar or ultrasonic signals. In laboratory tests and limited field tests the system has demonstrated the ability to detect a variety of inert antipersonnel and antitank mines with background contrast in excess of 20 dB. Current work on the system is focused on the transition from the laboratory into the field. To facilitate this, a series of experiments has been undertaken to measure the characteristics of several field test sites. The tradeoff between image contrast and scanning speed is of primary concern in evaluating the features of these sites. The field experiments have investigated the nature of ambient seismic noise, input impedance at the seismic source (a ground contacting shaker), modal content of the seismic interrogation signal, and the nature of the nonlinearities in the soil. Observed nonlinear phenomena have included harmonic generation, phase speed slowing, dispersion and spall. Although interesting, the differences between the field sites and the laboratory model do not appear to pose problems for seismic mine detection.

Multiresolution feature detection using a family of isotropic bandpass filters

Presents a novel method which uses a special type of multi-scale isotropic band-pass filters to detect image landmark and corner features. This paper mainly contributes to the solutions of the following problems: (1) defining a general family of feature detectors under a unified framework that are able to enhance and detect the desired features; (2) explaining theoretically and experimentally why these feature points can be detected by the proposed detectors; and (3) extending the detectors to multi-scale versions for jointly achieving good detectability and localization where an automatic scale selection method is applied. The paper then presents several applications for detecting landmarks and corners using the proposed methods, in order to illustrate their usage. These include detecting landmarks from gesture images (of the face and hand), from airborne and vehicle-borne IR landmine images, and from images containing object corners. Experiments have been performed using the proposed detectors to these applications. Some comparisons and evaluations have also been performed. The results have demonstrated the effectiveness of the proposed detectors in terms of feature detectability and localization.

Numerical Solution of a Subsurface Imaging Inverse Problem

In this paper a new solution method for an inverse problem for the two-dimensional (2D) Helmholtz equation is developed. The underlying application area which motivated this work is the imaging of land mines using ground penetrating radar, formulated as an inverse problem for the Helmholtz equation. A second generation version of the elliptic systems method is developed to numerically solve this problem. Uniqueness and convergence theorems and a variety of numerical results are presented.