A linear inversion scheme for microwave imaging of buried objects is presented in which arbitrary antennas are accounted for through their plane-wave transmitting and receiving spectra. INTRODUCTION Ground penetrating radar (GPR) is an efficient tool for microwave imaging of buried objects. Within the concept of diffraction tomography, as proposed by Devaney [1], several linear inversion scheme...

In this paper we propose an integrated approach to diagnostic prospecting applied to the cathedral of Matera, in Southern Italy. In particular, we have performed both an ultrasonic tomography and a high frequency GPR prospecting on some pillars of the Church to investigate about possible structural yielding and a GPR prospecting at lower frequencies on the floor, where also a linear inversion a...

This paper describes a new approach to object recognition by using ground-penetrating radar (GPR) imaging systems. The recognition procedure utilizes the spectral content instead of the object shape in traditional methods. To produce the identification feature of an object, the most common spectral component is obtained by singular value decomposition (SVD) of the training sets. The identificat...

This paper provides a comparative study between microwave tomography and synthetic time-reversal imaging techniques as applied to ground penetrating radar (GPR) surveys. The comparison is carried out by processing experimental data collected at a controlled test site, with different types of buried targets at given subsurface depths and representative soil conditions. It is shown that the two t...

In this paper, a comparison of two ground penetrating radar (GPR) systems is presented, the classical bi-static one and the Multiple Input Multiple Output (MIMO) system both using N Vivaldi antennas. For both configurations a Linear Sampling Metthod (LSM) imaging algorithm and Kirchhoff migration technique are used for target detection and localization. The performance of both systems are compa...

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...