No abstract

The focus of this paper is an empirical study conducted to determine how imaging modes for ground penetrating radar (GPR) affect buried object detection performance. GPR data were collected repeatedly over lanes whose buried objects were mostly nonmetallic. This data were collected and processed with a GPR antenna array, system hardware, and processing software developed by the authors and their colleagues. The system enables GPR data to be collected, imaged, and processed in realtime on a moving vehicle. The images are focused by applying multistatic and synthetic aperture imaging techniques either separately or jointly to signal scans acquired by the GPR antenna array. An image-based detection statistic derived from the ratio of buried object energy in the foreground to energy of soil in the background is proposed. Detection-false alarm performance improved significantly when the detection algorithm was applied to focused multistatic synthetic aperture radar (SAR) images rather than to unfocused GPR signal scans.Index Terms-Ground penetrating radar (GPR), multistatic imaging, synthetic aperture radar (SAR).

In contrast to standard reflection ultrasound (US), transmission US holds the promise of more thorough tissue characterization by generating quantitative acoustic parameters. We compare results from a conventional US scanner with data acquired using an experimental circular scanner operating at frequencies of 0.3 -1.5 MHz. Data were obtained on phantoms and a normal, formalin-fixed, excised breast. Both reflection and transmission-based algorithms were used to generate images of reflectivity, sound speed and attenuation.. Images of the phantoms demonstrate the ability to detect sub-mm features and quantify acoustic properties such as sound speed and attenuation. The human breast specimen showed full field evaluation, improved penetration and tissue definition. Comparison with conventional US indicates the potential for better margin definition and acoustic characterization of masses, particularly in the complex scattering environments of human breast tissue. The use of morphology, in the context of reflectivity, sound speed and attenuation, for characterizing tissue, is discussed.

A multistatic ground penetrating radar system is described, capable of real-time imaging and object detection. The radar consists of 16 transmitter and receiver pairs mounted across the front of a vehicle. The transmitters operate sequentially with all receivers activated for each transmit pulse. The resulting frame of 256 multistatic time signals is processed into an image using a tomographic reconstruction technique. In this paper we describe the system architecture, signal conditioning, and reconstruction algorithm for producing a sequence of images in real time as the vehicle travels across the ground. We demonstrate a robust image post-processing method that separates the bright spot corresponding to the dominant buried object in an image frame from the background. This is essential before calculating an energy-based statistic for automatic detection of buried objects. This spot ratio detection statistic, based on energy both inside and outside the spot, is shown to be not only more stationary than spot energy (i.e. mostly free of localized trends due to changing ground conditions), but also more powerful as a detection statistic. Finally, we demonstrate that multistatic imaging significantly improves the detection performance over more conventional monostatic array processing.

In this paper we present results from a three-dimensional image reconstruction algorithm for impulse radar operating in monostatic pulse-echo mode. The application of interest to us is the nondestructive evaluation of civil structures such as bridge decks. We use a multi-frequency diffraction tomography imaging technique in which coherent backward propagations of the received reflected wavefleld form a spatial image of the scattering interfaces within the region of interest. This imaging technique provides highresolution range and azimuthal visualization of the subsurface region. We incorporate the ability to image in planarly layered conductive media and apply the algorithm to experimental data from an offset radar system in which the radar antenna is not directly coupled to the surface of the region. We present a rendering in three-dimensions of the resulting image data which provides high-detail visualization.