KEYWORDS: Image registration, Land mines, Mining, General packet radio service, Radar, Night vision, Ground penetrating radar, Sensors, Antennas, Phase shifts
SRI International is investigating change detection for the US Army Night Vision Laboratory using a forward-looking ground-penetrating radar (GPR) sensor as a technique for monitoring cleared roadways against further emplacement of landmines. In the course of evaluating the utility of the technique against buried mines, we have noted that the sensitivity of GPR change detection appears to be sufficient to discern small changes in a scene (footprints, soil disturbance, etc.). Experiments have shown that this sensitivity can decrease significantly over a period of several hours. We have undertaken to learn whether this temporal degradation is because of system and processing artifacts or the inherent temporal change of the clutter field. We have found that the degradation appears to be related to a nonzero phase of the correlation peak observed when the 'before' and 'after' images are cross correlated. This behavior suggests that the images may be misregistered. A simple subpixel registration algorithm was formulated to correct the misregistation. The differencing of two nominally identical images finds the clutter suppression, as determined from the ratio of mean pixel magnitudes in difference and sum images, to have been improved by 7 to 10 dB following subpixel registration. In this paper we present results form recent experiments and improvements to our processing algorithms demonstrating the utility of GPR change detection.
A series of forward-looking ground penetrating radar measurements were taken that bracketed the emplacement of mines at a controlled test site. Fully polarimetric data were collected over a broad rang of frequencies at several times that spanned placement of the mines. These data have been used as input to chagne-detection processing both to examine the overall improvement in signal-to-clutter ratio provided by change detection and to begin assessment of the effects of weather and other relatively long-term variables on its effectiveness. Measurements have been performed initially with the system in a fixed position in order to determine base signal-to-clutter levels given ideal image registration. Under these controlled conditions, change detection is shown to be very effective over the short term in an application such as this. Changes in surface texture are also evident following the emplacement of mines. Morphological closing is shown to be a useful technique for delimiting such regions.
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