Ground penetrating radar and thermal sensors hold much promise for the detection of non-metallic land mines. In previous work we have shown that the performance of ground penetrating radar strongly depends on field soil conditions such as texture, water content, and soil-water salinity since these soil parameters determine the dielectric soil properties. From soil physics and field measurements we know that the performance of thermal sensors also strongly depends on soil texture and water content. There is it critical that field soil conditions are taken into account when radar and thermal sensors are employed. The objectives of this contribution are (i) to make an inventory of readily available soil data bases world wide and (ii) to investigate how the information contained in these data bases can be used for derivation of soil dielectric and thermal properties relevant for operation of land mine sensors.
Random noise polarimetry is a new radar technique for high-resolution probing of subsurface objects and interfaces. Detection of buried targets is accomplished by cross-correlating the reflected signal by a time-delayed replica of the transmitted waveform. A unique signal processing scheme is used to inject coherent in the system to permit extraction of the wideband polarimetric scattering response of the buried object. This facilitates computation of the Stokes matrices of the target response which enhances the detection and identification process. Random noise polarimetry also possesses additional desirable features for subsurface probing such as immunity from detection and jamming. The paper discusses the theoretical foundations of random noise polarimetry and presents data acquired from various targets using a 1 - 2 GHz radar system fabricated by the University of Nebraska under contract to the U.S. Army Waterways Experiment Station. In addition, various signal processing algorithms used to analyze the polarimetric data are presented.
A novel polarimetric ultra-wideband radar system operating in the 1-2 GHz frequency for subsurface probing applications is currently under development at the University of Nebraska. The radar system transmits white Gaussian noise. Detection and localization of buried objects is accomplished by correlating the reflected waveform with a time-delayed replica of the transmitted waveform. Broadband dual-polarized log-periodic antennas are used for transmission and reception. A unique signal processing scheme is used to obtain the target's polarimetric amplitude and phase response by frequency translation of the high depth resolution, low bandwidth-duration product, as well as simplified signal processing. This paper describes the unique design features of the radar system, develops the theoretical foundations of noise polarimetry, and provides experimental evidence of the polarimetric and resolution capabilities of the system.
A statistical approach is taken to present and analyze large amounts of physical and radiometric temperature data for structural materials as well as weather data collected over a period of several years at sites in both the United States and Europe. Diurnal temperature curves are presented as a function of time-of-year, surface material type, and surface orientation. Empirical temperature prediction models for different surface types as a function of weather parameters are developed for a given set of data to demonstrate the utility of maintaining large temperature/weather data bases in support of first-principles thermal modeling.