Parameterisation of non-homogeneities in buried object detection by means of thermography

Non-Uniform Temperature Fields and Effects of Steel Structures: Review and Outlook

“…Infrared thermal imaging detects the infrared band signal of the object's thermal radiation through photoelectric technology, and the signal is converted into an image that effectively reflects the distribution of the temperature field for visual discrimination [139,140]. Imaging technology has been widely used in medicine [141][142][143], the military [144][145][146], industry [147][148][149], agriculture [150][151][152], and architecture [153][154][155], but it is rarely used in the measurement of the temperature field of steel structures. A reasonable arrangement of a sufficient number of high-precision thermal imagers can accurately obtain the actual distribution of the temperature field of a steel structure; meanwhile, in combination with the shadow variation captured by an HD camera, the distribution mechanism and time-variance laws of the temperature field of a steel structure can be deeply understood.…”

Buried-object-detection improvements incorporating environmental phenomenology into signature physics

“…Additionally, subsurface object detection is more difficult than surface target detection because of an increase in background noise and reduced spatial information, hindering the ability to develop accurate simulations for empirical comparisons (Stepanić et al 2004). Also, surface targets, such as vehicles, are typically much larger in cross sectional area and mass as compared to buried objects of interest to the military.…”

“…Also, surface targets, such as vehicles, are typically much larger in cross sectional area and mass as compared to buried objects of interest to the military. Some strategies to overcome the background noise include varying the sensor orientation with respect to the soil normal (Stepanić et al 2004) and data fusion of multiple sensor systems (Shrestha and Wontae 2018). Prior knowledge of the properties of the object can enable the application of the inverse problem (Thành 2007) or finite element modeling (Vavilov 2010) to predict temperature flow and ultimately detection.…”

Analysis of a thermal imaging method for landmine detection, using infrared heating of the sand surface

“…An additional objective is the determination of the heating process which gives the greatest mine detection rate. The nature of this study precludes an examination of clutter effects found in the detection system though it is recognised that these effects would need to be considered in any usable field system [14]. Clutter effects have been introduced in some studies when surface roughness [5] and vegetation [4,9] are included within the study.…”