Ground Penetrating Radar Signal Processing Research Articles

GPR Signal Processing with Geography Adaptive Scanning using Vector Radar for Antipersonal Landmine Detection

Ground Penetrating Radar (GPR) is a promising sensor for landmine detection, however there are two major problems to overcome. One is the rough ground surface. The other problem is the distance between the antennas of GPR. It remains irremovable clutters on a sub-surface image output from GPR by first problem. Geography adaptive scanning is useful to image objects beneath rough ground surface. Second problem makes larger the nonlinearity of the relationship between the time for propagation and the depth of a buried object, imaging the small objects such as an antipersonnel landmine closer to the antennas. In this paper, we modify Kirchhoff migration so as to account for not only the variation of position of the sensor head, but also the antennas alignment of the vector radar. The validity of this method is discussed through application to the signals acquired in experiments.

Ground penetrating radar signal processing improves mapping accuracy of underground voids and seawater table: an application in deteriorating coastal structure, Nanfangao Port, Taiwan

Efficient restoration of deteriorating coastal structures requires an accurate picture of both above ground and underground features. Although ground penetrating radar (GPR) can map underground features, it creates reflection artifacts. Here, a model for deconvolution calibration was developed in an outdoor small-scale experiment. GPR parameters were established, then applied at a deteriorating fishing port in northeast Taiwan. The deconvolution filter removed repetitive reflection patterns under the lowest part of the void creating a more accurate map. A 3D-map was created from interpolated sketched void boundaries. Due to its high lossy nature at radar frequencies and large contrasting relative dielectric permittivity (RDP) to the upper medium, the seawater table (SWT) is easily identified. The upper boundary of reflection-free area in the deconvoluted radargram, therefore, indicates the SWT. The methods developed here are easily modified to fit a wide range of situations.

GPR Signal Processing on Geography Adaptive Scanning with Vector Radar

Ground Penetrating Radar (GPR) is a promissing sensor for landmine detection, however there are two major problems to overcome. One is the non-planer (e.g. rough and/or undulating) ground surface. It remains unremovable clutters on a sub-surface image output from GPR. Geography adaptive scanning is useful to image objects beneath non-planer ground surface. The other problem is the distance between the antennas of GPR. When imaging the small objects such as an anti-personnel landmine buried in shallow depth, it increases the nonlinearity of the relationship between the time for propagation and the depth of a buried object. In this paper, we modify Kirchoff migration so as to account for not only the variation of height and pose of the sensor head, but also the antennas alignment of the vector radar. The validity of this method is discussed through application to the signals acquired in experiments.

Multi-frequency synthetic-aperture imaging with a lightweight ground penetrating radar system

The detection of buried objects, particularly hazardous waste containers and unexploded ordnance (UXO), has gained significant interest in the Unites States in the late 1990s. The desire to remediate the thousands of sites worldwide has become an increasing concern and the application of radar to this problem has received renewed attention. The US Department of Energy's Special Technologies Laboratory (STL), operated by Bechtel Nevada, has developed several frequency-modulated, continuous-wave (FM-CW) ground penetrating radar (GPR) units. To meet technical requirements for higher-resolution data, STL and the University of California, Santa Barbara (UCSB) is investigating advanced GPR hardware, signal processing, and synthetic-aperture imaging with the development of an innovative system. The goal is to design and fabricate a lightweight, battery-operated unit that does not require surface contact, can be operated by a novice user, and can achieve improved resolution. The latter is accomplished by using synthetic-aperture imaging, which forms the subsurface images by fully utilizing the data sequences collectively along a scan path. We also present the backward propagation algorithm as the basic structure of the multiple-frequency tomographic imaging technique, and the conventional fast Fourier transform (FFT) method which can be described as a degenerated case of the model where the computation procedure is approximated under the narrow-beam assumption.

Acquisition and Signal Processing of Ground-Penetrating Radar for Shallow Exploration and Open-Pit Mining

The Australian Mineral Industries Research Association (AMIRA) has sponsored Monash University to investigate the acquisition and signal processing of ground-penetrating radar (GPR) for shallow exploration and open-pit mining. This project had three objectives: (1) to acquire high-quality GPR data sets for shallow exploration and surface mining applications under a variety of geological conditions; (2) to develop signal-processing techniques to enhance radar profiles prior to detailed interpretation; (3) to assess the accuracy of GPR and associated processing techniques through comparisons with independent measurements.Over one hundred kilometres of data were recorded at the various sponsors sites in a wide variety of geological conditions for different economic targets. Several examples are presented to demonstrate:1) the hand-carried and vehicle-towed acquisition techniques,2) target detection at depths down to 25 m,3) the benefits of signal processing for good and poor quality data,4) the use of dielectric measurements, petrophysical modelling and frequency-dependent synthetic radargrams,5) the application of seismic interpretation concepts.The project has demonstrated commercially acceptable rates of GPR data acquisition where the penetration is satisfactory. Some of the unfavourable Australian geological conditions for radar have also been identified. Although signal processing techniques have extended the applicable range of the radar technique, additional hardware enhancements have been identified to improve the commercial application of radar. The next stage is to assess the economic feasibility of radar by comparison with competing techniques such as drilling.