In this article a new neural network based method for automatic classification of ground penetrating radar (GPR) traces is proposed. The presented approach is based on a new representation of GPR signals by polynomials approximation. The coefficients of the polynomial (the feature vector) are neural network inputs for automatic classification of a special kind of geologic structure—a sinkhole. ...

Multimodal detection of subsurface targets such as tunnels, pipes, reinforcement bars, and structures has been investigated using both ground-penetrating radar (GPR) and seismic sensors with signal processing techniques to enhance localization capabilities. Both systems have been tested in bi-static configurations but the GPR has been expanded to a multi-static configuration for improved perfor...

A Kalman filter (KF) enhanced by the Gaussian process regression (GPR) technique is suggested to bridge GPS-outages in navigation solutions where inertial navigation systems (INS) and GPS are integrated. A KF utilises linearised dynamic models. If a low-cost MEMS-based INS with complex stochastic nonlinearity is considered, performance degrades significantly during short periods of GPSoutages o...

This paper illustrates a prototype system, called GPRS, supporting the Generalized Production Rules (GPR) database language. The GPR language integrates, in a uniied framework, active rules, which allow the speciica-tion of event driven computations on data, and deductive rules, which can be used to derive intensional relations in the style of logic programming. The prototype realizes the opera...

Bridge decks deteriorate over time as a result of freezing-and-thawing, heavy use, and water penetration resulting in internal defects. Ground penetrating radar (GPR) can be used as a non-destructive method for detecting such defects. Unfortunately, reflections from closely spaced objects overlap which prevents the accurate estimation of the round-trip travel time of GPR waves to the closely sp...

Abstract—This paper describes the use of the correlation maps in the Ground Penetrating Radar (GPR) for the detection of near surface objects. This method is based on the definition of bi-dimensional maps that describe the level and the nature of coherence between the received electromagnetic signals. The technique proposed provides the detection of objects, reducing the impact of the clutter a...

GPR (Ground Penetrating Radar) is one of subsurface sensing technologies, which has been used intensively since 1980s. Due to rapid development of both hardware and software, its possibilities have been considerably extended resulting in widening the area of its applications. While such applications as to detection of buried pipes and cables, archaeology and geology are established category, ne...

This paper proposes an inductive data mining technique (named GPR) based on genetic programming. Unlike other mining systems, the particularity of our technique is its ability to discover business rules that satisfy multiple (and possibly conflicting) decision or search criteria simultaneously. We present a step-by-step method to implement GPR, and introduce a prototype that generates productio...

We present a novel approach for non-stationary Gaussian process regression (GPR), where the three key parameters – noise variance, signal variance and lengthscale – can be simultaneously input-dependent. We develop gradient-based inference methods to learn the unknown function and the non-stationary model parameters, without requiring any model approximations. For inferring the full posterior d...

Crack detection is an important application for Ground penetrating radar (GPR) to examine the concrete road or building structure conditions. The layer of rebars or utility pipes that typically exist inside the concrete structure can generate stronger scattering than small concrete cracks to affect detection effectiveness. In GPR image, the signature patterns of regularly distributed rebars or ...