KEYWORDS: Electromagnetic coupling, General packet radio service, Magnetism, Sensors, Feature extraction, Electromagnetism, Data processing, Data modeling, Polarization, Ground penetrating radar
In highly contaminated unexploded ordnance (UXO) cleanup sites, multiple metallic subsurface objects may appear within the field of view of the sensor simultaneously, both for electromagnetic induction (EMI) and ground penetrating radar (GPR). Sensor measurements consist of an a priori unknown mixture of the objects' responses. The two sensing systems can provide different kinds of information, which are complementary and could together produce enhanced UXO discrimination in such cases. GPR can indicate the number of objects and their approximate locations and orientations. This data can then serve as prior information in EMI modeling based on the standardized excitation approximation (SEA). The method is capable of producing very fast, ultra-high fidelity renderings of each object’s response, including all effects of near and far field observation, non-uniform excitation, geometrical and material heterogeneity, and internal interactions. Given good position information, the SEA formulation inverts successfully for EMI parameters for each of the two objects, using EMI data in which their signals overlap. The values of the inferred parameters, in terms of their frequency and spatial patterns for an object's response to each basic excitation, are unique characteristics of the object and could thus serve as a basis for classification.
Electromagnetic induction sensing (EMI), between ~ 10's of Hz and 100's of kHz, may show the strongest promise for discrimination of subsurface, shallow metallic objects such as unexploded ordnance (UXO). While EMI signals penetrate the soil readily, resolution is low and responses are sometimes ambiguous. For crucial discrimination progress, maximum data diversity is desirable in terms of look angles, frequency spectrum, and full vector scattered field data. Newly developed instrumentation now offers the possibility of full vector UWB EMI data with flexible look angle and sensor distance/sweep, defined by precise laser positioning. Particulars of the equipment and resulting data are displayed. An indication is given of potential advantages for reducing the chronic ill-conditioning of inversion calculations with EMI data, when one takes advantage of the data diversity made possible by the instrumental advances. Some EMI measurement issues cannot be solved by EMI data diversity, as when small surface clutter above a much larger UXO effectively blinds an EMI sensor. EMI surveying must be supplemented by or sometimes replaced by ground penetrating radar (GPR) approaches in such instances.
This paper presents an automatic UXO classification system using neural network and fuzzy inference based on the classification rules developed by the OSU. These rules incorporate scattering pattern, polarization and resonance features extracted from an ultra-wide bandwidth, fully polarimetric radar system. These features allow one to discriminate an elongated object. The algorithm consists of two stages. The first-stage classifies objects into clutter (group-A and D), a horizontal linear object (group-B) and a vertical linear object (group-C) according to the spatial distribution of the Estimated Linear Factor (ELF) values. Then second-stage discriminates UXO-LIKE targets from clutters under groups B and C. The rule in the first-stage was implemented by neural network and rules in the second-stage were realized by fuzzy inference with quantitative variables, i.e. ELF level, flatness of Estimated Target Orientation (ETO), the consistency of the target orientation, and the magnitude of the target response. It was found that the classification performance of this automatic algorithm is comparable with or superior to that obtained from a trained expert. However, the automatic classification procedure does not require the involvement of the operator and assigns a unbiased quantitative confidence level (or quality factor) associated with each classification. Classification error and inconsistency associated with fatigue, memory fading or complex features should be greatly reduced.
It is widely acknowledged that tree roots and other forms of buried biomass have an adverse effect on the performance of ground-penetrating radars (GPRs). In this work we present experimental and theoretical work that quantifies that effect. Test sites containing extensive root infiltration at Eglin Air Force Base, FL were probed with a GPR. After completing the measurements, the sites were excavated, and the root structure and soil were thoroughly characterized. Supplemental GPR measurements of simple cylindrical objects in a laboratory setting were performed to investigate basic scattering behavior of buried roots. A numerical simulator based on the Discrete Dipole Approximation (DDA), an integral-equation-based method, was developed, validated and subsequently used to compute scattering from root structures modeled by an ensemble of buried cylinders. A comparison of the measurements and numerical calculations is presented that quantifies the potential for false alarms and increased clutter due to buried roots.
KEYWORDS: Neural networks, Target detection, General packet radio service, Antennas, Binary data, Signal to noise ratio, Ground penetrating radar, Detector development, Monte Carlo methods, Roads
Ground penetrating radar (GPR) has been widely used for the detection and location of buried objects. However, the detection method is often subjected to operator's interpretation due to large quantities of data and undesired clutter and noise. Such a detection method is neither reliable nor efficient.
This paper presents a non-destructive procedure to determine the surface hardness of the soil using an elevated radar system equipped with a focused-beam antenna. The complete system consists ofthe focused beam antenna, a network analyzer, a computer, and control software that process the data. The surface dielectric constant calculated from the radar data based on reflection measurement was compared with the surface hardness measured directly from a homemade hardness meter. A sand pit was used as test bed that was frozen by liquid nitrogen. It was found that there is a simple and direct relationship between the surface hardness and the measured dielectric constant in our case.
The OSU/ESL GPR systems have been applied to the detection and classification of buried unexploded ordnance (UXO) for years. It has evolved from an impulse and single-polarization (cross-polarization) system utilizing complex natural resonance (CNR) feature to the recent step-frequency and fully polarimetric system utilizing CNR, polarization and scattering features. Significant progresses in measurement techniques, feature extraction algorithms and classification rules have been made during the past three years under the support US DoD ESTCP program. These important progresses were motivated by field data collected at government test sites such as Tyndall AFB (1999), Blossom Point (2000) and Jefferson Proving Ground (2001). This paper briefly describes these progresses and the motivations behind them.
KEYWORDS: Antennas, General packet radio service, Dielectrics, Finite-difference time-domain method, Numerical modeling, 3D modeling, Polarimetry, Resistance, 3D acquisition, Transmission electron microscopy
Finite Differencing Time Domain (FDTD) modeling technique was developed as a tool to study GPR problem that could be very complex due to the antenna design, inhomogeneous soil and varieties of target types. The broadband, fully polarimetric horn-fed bowtie (HFB) antenna design (Chen, 1 997) was modeled as an example. Feeding cables, 3D antenna structure and tapered resistive loading were included. Calculated characteristics of the electrical properties of the HFB antenna in the entire 10 - 800 MHz range was obtained. Various technical issues involved in numerical modeling will be discussed.
An ultra-wide bandwidth (UWB) dielectric rod antenna modified from its previous version developed by Chen (1999) is presented. Such antenna is useful in detecting shallowly buried targets, such as anti-personnel (AP) mines. Broad bandwidth electromagnetic energy is launched, guided and radiated from a dielectric rod that has a constant cross- section area and low-loss permittivity except at the end where the permittivity is gradually reduced to match to that of free air. The electromagnetic waves radiated out from rod end have field behavior similar to that of a Hertzian dipole. The low antenna clutter and weak antenna-ground interaction are two unique features. Its near-field radiation properties are investigated using three-dimensional finite difference time domain (FDTD) simulation technique. Some measurement and numerical simulation results are also included.
A novel but intuitive antenna design to achieve both broad frequency bandwidth as well as good efficiency is presented. This design utilizes unfurlable folded-dipole with its length mechanically tuned to specified operational frequency. Such antenna has been proposed for subsurface sensing on Mars surface and its prototype was built and tested. The test results verified the desired bandwidth and efficiency feature.
KEYWORDS: Antennas, General packet radio service, Finite-difference time-domain method, Interfaces, Data modeling, Dielectrics, Solids, Signal attenuation, Geometrical optics, Wavefronts
GPR dipole antenna patterns can be described by the interference of space and lateral waves. Because this is an interference phenomenon, antenna patterns are a function of frequency, distance, and electrical properties. Traditional far-field criteria based on dipoles in a whole-space are insufficient to describe dipole antennas on a half-space boundary. Whole-space criteria fail because they do not take into account the interference of space and lateral waves. The travel time difference between space and lateral waves increases as the angle of observation from vertical increases, or with increasing distance from the source. The result is increased interference and more abundant lobes with increasing distance and observation angle. Since GPR investigations are limited by attenuation and many environmental and engineering targets of interest are located within a few wavelengths of the antenna, asymptotic solutions do not accurately describe antenna patterns for most GPR applications. The exclusion of lateral waves in geometric optics solutions is another source of error for many GPR applications. Data were measured over a water filled tank to verify FDTD antenna pattern models. Asymptotic solutions predict H-plane peaks at an angular distance equal to the critical angle. Measured and modeled antenna patterns are broader and have peaks located at a larger angular distance, than predicted from asymptotic solutions. The peaks approach and decrease the rate of convergence toward the asymptotic solution with increasing distance from the source, and data modeled over water demonstrate that the peaks still do not converge to the asymptotic solution at a distance of 24 wavelengths. The low directivity of dipole antennas explains why out of the plane reflections are commonly observed in GPR data.
A novel broad bandwidth dual-polarization GPR antenna was also developed for collecting fully polarimetric data over a wide frequency range (20 MHz to approximately 800 MHz). This new design was improved from its single-polarization version introduced by Chen (1997). The new design features improved stability and directivity over conventional surface-based GPR antennas. Such antenna is currently applied to discriminate buried UXO's from other false alarm reduction.
Previous electromagnetic scattering result have been presented for the ramp response profile functions for Anti- Personnel (A-P) Mines in lossless, homogeneous media. 3D images have been generated using such profile functions for three orthogonal incidence angles. The purpose of this present paper is to provide techniques for generating profile functions for lossy dispersive media. This procedure has been quite successful, provided the electrical properties of the ground are known, and the radar is calibrated. Under these conditions, these profile functions would provide valid radar images of the A-P mines.
Early time returns affect the estimation of complex natural resonance (CNR) frequencies associated with a target. This is especially true when there is a small separation between the early time returns and the late time response of the target and the CNRs are low Q mechanisms. A good example of this scenario is antipersonnel mines. In this situation, it helps to remove the early time returns from the total scattered field. A new technique to accomplish this is presented here. Using some numerical data and some experimental data, it is demonstrated that this technique is very effective in removing the early time returns. The modified scattered field data then yields better estimates of CNR frequencies.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.