Recent advances in high-resolution Ground Penetrating Radar on board an Unmanned Aerial Vehicle

European Conference on Antennas and Propagation (EuCAP) (13th. 2019. Krakow, Poland

Assessing the internal structure of hollow trees using GPR and microwave tomography

Trees and woodlands are nowadays threatened by variety of aggressive diseases and fungal infections. As a result, internal decays in trees, can lead to the creation of cavities and large holes inside the trunks, which in turn can seriously undermine the stability and the integrity of the tree. In this regard, ground-penetrating radar (GPR) has recently proven to be an effective non-destructive testing (NDT) method, with the potential of providing information about the internal structure of trees. However, the particular shape of tree trunks prevents the use of traditional data processing techniques, and only limited information can be collected for tree health assessment purposes. This study shows the potential of GPR enhanced by a microwave tomography inversion approach in detecting tree cavities and hollows. A hollow tree was investigated by performing a set of circular GPR scans, and the internal structure of the trunk was reconstructed via tomographic imaging. The achieved results were validated by way of comparison with real sections cut from the tree and prove the validity of the proposed methodology in identifying the dimension and shape of cavities and hollows in tree trunks

Critical Analysis of Background Subtraction Techniques on Real GPR Data

Ground penetrating radar (GPR) is used to detect the underground buried objects for civil as well as defence applications under varying conditions of soil moisture content. The capability of detection depends upon soil moisture, target characteristics and subsurface characteristics, which are mainly responsible for contaminating the GPR images with clutter. Researchers earlier have used averaging, mean, median, Eigen values, etc. for subtracting the background from GPR images. To analyse the background subtraction or clutter reduction problems, in this paper, we have experimentally reviewed background subtraction techniques with or without target conditions to enhance the target detection under variable soil moisture content. Indigenously developed GPR has been used to collect the data for different soil conditions and several background subtraction signal processing techniques were critically reviewed like, mean, median, singular value decomposition (SVD), principal component analysis (PCA), independent component analysis (ICA) and training methods. The signal to clutter ratio (SCR) measurement has been used for performance evaluation of each technique. The relative merits and demerits of each technique has also been analysed. The background subtraction techniques have been appliedto experimental GPR data and it is observed that in comparison of mean, SVD, median, ICA, PCA, the training method shows the highest SCR with buried target. Finally, this review helps to select the comparatively better background subtraction technique to enhance the detection capability in GPR

Performance Analysis of Tomographic Methods against Experimental Contactless Multistatic Ground Penetrating Radar

Ground-penetrating radar (GPR) technology for underground exploration consists of the transmission of an electromagnetic signal in the ground for sensing the presence of buried objects. While monostatic or bistatic configurations are usually adopted, a limited number of multistatic GPR systems have been proposed in the scientific literature. In this article, we investigate the recovery performance of a specific and unconventional contactless multistatic GPR system, designed at the Georgia Institute of Technology for the subsurface imaging of antitank and antipersonnel plastic mines. In particular, for the first time, tomographic approaches are tested against this experimental multistatic GPR system, while most GPR processing in the scientific literature processes multimonostatic experimental data sets. First, by mimicking the system at hand, an accurate theoretical as well as numerical analysis is performed in order to estimate the data information content and the performance achievable. Two different tomographic linear approaches are adopted, i.e., the linear sampling method and the Born approximation (BA) method, this latter enhanced by means of the compressive sensing (CS) theoretical framework. Then, the experimental data provided by the Georgia Institute of Technology are processed by means of a multifrequency CS- and BA-based method, thus generating very accurate 3D maps of the investigated underground scenario

Synthetic aperture radar imaging system for landmine detection using a ground penetrating radar on board a unmanned aerial vehicle

This paper presents a novel system to obtain images from the underground based on ground penetrating radar (GPR). The proposed system is composed by a radar module mounted on board an unmanned aerial vehicle (UAV), which allows the safe inspection of difficult-to-access areas without being in direct contact with the soil. Therefore, it can be used to detect dangerous buried objects, such as landmines. The radar measurements are coherently combined using a synthetic aperture radar (SAR) algorithm, which requires cm-level accuracy positioning system. In addition, a clutter removal technique is applied to mitigate the reflection at the air-soil interface (which is caused by impedance mismatching). Besides the aforementioned advantages, the system can detect both metallic and dielectric targets (due to the use of a radar instead of a metal detector) and it allows to obtain high-resolution underground images (due to the SAR processing). The algorithms and the UAV payload are validated with measurements in both controlled and real scenarios, showing the feasibility of the proposed system.Ministerio de Economía y Competitividad | Ref. TEC2014-54005-PMinisterio de Economía y Competitividad | Ref. TEC2014-55290-JINMinisterio de Economía y Competitividad | Ref. TEC2015-73908-JINMinisterio de Economía y Competitividad | Ref. TEC2015-65353-RAgencia Estatal de Investigación | Ref. RYC-2016-20280Ministerio de Educación | Ref. FPU15/06341Gobierno del Principado de Asturias | Ref. PCTI 2013-2017Gobierno del Principado de Asturias | Ref. FC-15-GRUPIN14-114Gobierno del Principado de Asturias | Ref. IDI/2017/000095Xunta de Galicia | Ref. GRC2015/01

Clutter removal of near-field UWB SAR imaging for pipeline penetrating radar

Recently, ultrawideband (UWB) near-field synthetic aperture radar (SAR) imaging has been proposed for pipeline penetrating radar applications thanks to its capability in providing suitable resolution and penetration depth. Because of geometrical restrictions, there are many complicated sources of clutter in the pipe. However, this issue has not been investigated yet. In this article, we investigate some well-known clutter removal algorithms using full-wave simulated data and compare their results considering image quality, signal to clutter ratio and contrast. Among candidate algorithms, two-dimensional singular spectrum analysis (2-D SSA) shows a good potential to improve the signal to clutter ratio. However, basic 2-D SSA produces some artifacts in the image. Therefore, to mitigate this issue, we propose “modified 2-D SSA.” After developing the suitable clutter removal algorithm, wepropose a complete algorithm chain for pipeline imaging. An UWB nearfieldSARmonitoring system including anUWBM-sequence sensor and automatic positioner are implemented and the image of drilled perforations in a concrete pipe mimicking oil well structure as a case study is reconstructed to test the proposed algorithm. Compared to the literature, a comprehensive near-field SAR imaging algorithm including new clutter removal is proposed and its performance is verified by obtaining high-quality images in experimental results

The Use of GPR and Microwave Tomography for the Assessment of the Internal Structure of Hollow Trees

Peer reviewedPostprin

Performance Analysis of Tomographic Methods Against Experimental Contactless Multistatic Ground Penetrating Radar

Ground-penetrating radar (GPR) technology for underground exploration consists of the transmission of an electromagnetic signal in the ground for sensing the presence of buried objects. While monostatic or bistatic configurations are usually adopted, a limited number of multistatic GPR systems have been proposed in the scientific literature. In this article, we investigate the recovery performance of a specific and unconventional contactless multistatic GPR system, designed at the Georgia Institute of Technology for the subsurface imaging of antitank and antipersonnel plastic mines. In particular, for the first time, tomographic approaches are tested against this experimental multistatic GPR system, while most GPR processing in the scientific literature processes multimonostatic experimental data sets. First, by mimicking the system at hand, an accurate theoretical as well as numerical analysis is performed in order to estimate the data information content and the performance achievable. Two different tomographic linear approaches are adopted, i.e., the linear sampling method and the Born approximation (BA) method, this latter enhanced by means of the compressive sensing (CS) theoretical framework. Then, the experimental data provided by the Georgia Institute of Technology are processed by means of a multifrequency CS- and BA-based method, thus generating very accurate 3D maps of the investigated underground scenario