Jan Igel

Clutter Modeling for Ground-Penetrating Radar Measurements in Heterogeneous Soils

Ground-penetrating radar (GPR) measurement and its interpretation/analysis are challenging when soil is heterogeneous. Soil heterogeneity causes unwanted reflections (i.e., clutter) that disturb reflections from objects of interest. Thorough investigations on soil heterogeneity and clutter are important in order to understand the influence on GPR and assess the performance. In order to observe the influence of heterogeneous soil, an irrigation test was carried out and GPR data were collected after the irrigation and while the distribution of soil water content varied. The correlation length and variability of the dielectric constant of soil were determined by geostatistical analyses of the GPR data. These two parameters were built into a simple model and the Mie solution was theoretically calculated. From this, the power of the backscattered field due to soil heterogeneity was modeled. The results were in agreement with the power of the clutter extracted from the GPR data. Therefore, clutter can be predicted from soil heterogeneity with a simple model using the Mie solution. Furthermore, the result exhibits that scattering by heterogeneous soil is dominated by Mie scattering, rather than Rayleigh scattering, in the studied frequency range.

Influence of Heterogeneous Soils and Clutter on the Performance of Ground-Penetrating Radar for Landmine Detection

Ground-penetrating radar (GPR) has been studied for landmine detection and identification. Since this application employs higher frequencies as compared to conventional largescale GPR measurements, the GPR performance is greatly influenced by soil properties and their spatial heterogeneity. In order to study the influence of soil heterogeneity on GPR performance, three types of soil were investigated. From the soil heterogeneity, GPR clutter was modeled with the aim of assessing the difficulty encountered in successful GPR performance. A handheld dual-sensor system that combines a metal detector and GPR was tested in these three test soils, and its performance for identifying buried objects was evaluated. The GPR performance obtained from the test showed a clear correlation with the modeled GPR clutter. Hence, the present study illustrates that clutter plays a major role in the detection of small objects in heterogeneous soil by GPR.

Modeling of GPR Clutter Caused by Soil Heterogeneity

In small-scale measurements, ground-penetrating radar (GPR) often uses a higher frequency to detect a small object or structural changes in the ground. GPR becomes more sensitive to the natural heterogeneity of the soil when a higher frequency is used. Soil heterogeneity scatters electromagnetic waves, and the scattered waves are in part observed as unwanted reflections that are often referred to as clutter. Data containing a great amount of clutter are difficult to analyze and interpret because clutter disturbs reflections from objects of interest. Therefore, modeling GPR clutter is useful to assess the effectiveness of GPR measurements. In this paper, the development of such a technique is discussed. This modeling technique requires the permittivity distribution of soil (or its geostatistical properties) and gives a nominal value of clutter power. The paper demonstrates the technique with the comparison to the data from a GPR time-lapse measurement. The proposed technique is discussed in regard to its applicability and limitations based on the results.

Basics and Application of Ground-Penetrating Radar as a Tool for Monitoring Irrigation Process

Ground-penetrating radar (GPR) is a geophysical method that employs an electromagnetic technique. The method transmits and receives radio waves to probe the subsurface. One of the earliest successful applications was measuring ice thickness on polar ice sheets in 1960s (Knodel et al., 2007). Since then, there have been rapid developments in hardware, measurement and analysis techniques, and the method has been extensively used in many applications, such as archaeology, civil engineering, forensics, geology and utilities detection (Daniels, 2004).

Classification of soil magnetic susceptibility and prediction of metal detector performance: case study of Angola

Soil magnetic properties can seriously impede the performance of metal detectors used in landmine clearance operations. For a proper planning of clearance operations pre-existing information on soil magnetic susceptibility can be helpful. In this study we briefly introduce a classification system to assess soil magnetic susceptibilities from geoscientific maps. The classification system is based on susceptibility measurements conducted on archived lateritic soil samples from 15 tropical countries. The system is applied to a soil map of Angola, resulting in a map that depicts soil magnetic susceptibilities as a worst case scenario. An additional layer depicting the surveyed mine affected communities in Angola is added to the map, which demonstrates that a large number of those are located in areas where soil is expected to impede metal detector performance severely.

Small-scale variability of electromagnetic soil properties and their influence on landmine detection: How to measure, how to analyse, and how to interpret?

The small-scale variability of physical soil properties has a negative influence on ground exploration with physical sensors. This particularly holds true for small target objects like landmines. Studies were carried out to determine magnetic susceptibility, electric conductivity and dielectric permittivity of natural soils. The spatial variability of the field data is quantitatively characterised by means of geostatistical analysis. We present field measurements on different soils types in Germany and on former minefields in Mozambique. The spatial distribution of magnetic susceptibility is governed by the mineral composition of the soil and its stone content. The correlation lengths are in the range of a few meters. In contrast, electric conductivity and permittivity is mainly determined by soil moisture. Due to the small-scale variability of topsoil water content, these two electric properties often feature very small correlation lengths in the range of decimeters. By way of example, the influence of soil variability on landmine detection is illustrated for radar sensors. Geostatistical simulation techniques are used to generate random soil models which are used for realistic finite-differences (FD) calculations of electromagnetic wave propagation. Permittivity variations appear to have a greater influence on radar detector performance than conductivity variations and can mask the signals from the mines.

Spectral Decomposition of Soil Electrical and Dielectric Losses and Prediction of In Situ GPR Performance

The performance of high-frequency ground-penetrating radar (GPR) for high-resolution imaging of the near surface can essentially be controlled by the soil electromagnetic (EM) properties. One of these properties influencing sensing depth and image resolution of GPR is the intrinsic attenuation. We investigated the frequency-dependent electrical and dielectric properties of a broad range of soil samples. In order to derive the effective complex dielectric permittivity between 1 MHz and 10 GHz, we applied the coaxial transmission line (CTL) technique. A generalized dielectric response model, consisting of one Debye and one Cole-Cole type relaxation and a constant low-frequency conductivity term was used to analyze the dielectric relaxation behavior. Splitting the spectra into individual loss processes shows that dielectric relaxation mechanisms play a crucial role in most natural soils. Especially for high-frequency applications, attenuation cannot be described by a dielectric constant and dc-conductivity alone. Therefore, a simple conductivity-attenuation relation without dielectric losses can highly overestimate the GPR performance. As an alternative to the CTL technique in the lab, we suggest to use time-domain reflectometry (TDR) for the in Situ assessment of high-frequency electrical properties and deduced prediction of GPR performance.

Sensitivity analysis of soil heterogeneity for ground‐penetrating radar measurements by means of a simple modeling

Higher-frequency ground-penetrating radar (GPR) is becoming more common for various applications. While it can achieve a higher resolution than low-frequency measurements, it also becomes more sensitive to heterogeneous soils. The increased sensitivity in small-scale measurements often creates the problem of unwanted scattering in the data. Unwanted scattering is commonly called clutter. If clutter contaminates the data significantly, data analysis and interpretation become difficult. Our study analyzes the sensitivity of soil heterogeneity by evaluating the amount of clutter caused by soils. Clutter is calculated by simple modeling that takes into account soil heterogeneity. The method constructs a dielectric sphere model that uses statistical properties of permittivity distribution and calculates backscattering power from the sphere that emulates the backscattering observed from heterogeneous soil. The modeling was carried out for a range of heterogeneities. The results show that the level of permittivity variation of soil mostly dominates the clutter power. However, the influence of correlation length becomes greater when the correlation length of soil permittivity distribution is a multiple of wavelength. Therefore, to observe the influence of heterogeneous soils on GPR measurements, the spatial distribution of soil permittivity must be taken into account in addition to the variation.

Performance of demining sensors and soil properties

Metal detector has commonly been used for landmine detection and ground-penetrating radar (GPR) is about to be deployed as dual sensor that is in combination with metal detector. Since both devices employ electromagnetic techniques, they are influenced by magnetic and dielectric properties of soil. To observe the influence, various soil properties as well as their spatial distributions were measured in four types of soil where a field test of metal detectors and GPRs took place. By analyzing soil properties these four types of soil were graded based on the estimated amount of influence on the detection techniques. The classification was compared to the detection performance of devices obtained from the blind test and a clear correlation between the difficulty of soil and the performance was observed; the detection and identification performance were degraded in soils that were classified as problematic. Therefore, it was demonstrated that the performance of metal detector and GPR for landmine detection can qualitatively be assessed by geophysical analyses.

Soil influence on landmine detection—insights from a field study in Mozambique

PurposeElectromagnetic induction based metal detectors are commonly used in landmine clearance operations. Their performance can be seriously deteriorated by magnetic properties of the soil in which the landmines are buried.Materials and methodsSoil magnetic parameters were studied at three locations in Southern Mozambique where soils had caused severe problems during former landmine clearance campaigns. Field work comprised a geological and pedological survey of soils and the parent rock materials. Soil and rock samples were analyzed to determine pedological standard parameters and magnetic susceptibility. Geochemical analysis, scanning electron microscopy, and thermomagnetic analysis helped to clarify the mineral composition and to specify the origin and properties of the magnetic minerals. The spatial distribution of the topsoil magnetic susceptibility was investigated in the field and characterized using geostatistical analyses.Results and discussionDespite different degrees of weathering of the investigated soils, their magnetic mineral composition is dominated by lithogenic (Ti-) magnetites. Moreover, there are clues for the pedogenic neoformation of ultrafine-grained ferrimagnetic minerals in two of the three topsoils. The deterioration of metal detector performance at the sites results from the high frequency dependence of magnetic susceptibility at two locations and from the distinct spatial variability of topsoil magnetic susceptibility at all locations.ConclusionsTo assess soil effects on the performance of modern metal detectors the investigations of frequency-dependent susceptibility and of spatial susceptibility distribution are the most meaningful tools. Summarizing, the topsoil magnetic properties of the investigated sites are predominantly influenced by their parent material and to a minor degree by pedogenic neoformation.