Comparison of experimental three-band IR detection of buried objects and multiphysics simulations

A buried-object detection system composed of a LWIR, a MWIR and a SWIR camera, along with a set of ground and ambient temperature sensors was constructed and tested. The objects were buried in a 1.2x1x0.3 m 3 sandbox and surface temperature (using LWIR and MWIR cameras) and reflection (using SWIR camera) were recoded throughout the day. Two objects (aluminum and Teflon) with volume of about 2.5x10 -4 m 3 , were placed at varying depths during the measurements. Ground temperature sensors buried at three different depths measured the vertical temperature profile within the sandbox, while the weather station recorded the ambient temperature and solar radiation intensity. Images from the three cameras were simultaneously acquired in five-minute intervals throughout many days. An algorithm to postprocess and combine the images was developed in order to maximize the probability of detection by identifying thermal anomalies (temperature contrast) resulting from the presence of the buried object in an otherwise homogeneous medium. A simplified detection metric based on contrast differences was established to allow the evaluation of the image processing method. Finite element simulations were performed, reproducing the experiment conditions and, when possible, incorporated with data coming from actual measurements. Comparisons between experiment and simulation results were performed and the simulation parameters were adjusted until images generated from both methods are matched, aiming at obtaining insights of the buried material properties. Preliminary results show a great potential for detection of shallowburied objects such as land mines and IEDs and possible identification using finite element generated maps fitting measured surface maps.