Abstract

Beneath the soil, there exist numerous concealed objects, some of which, like landmines, pose a considerable threat to human life. Infrared detection serves as a swift and secure method for detecting such hazards. However, in many current studies, the soil is often oversimplified as a single entity, overlooking the crucial internal moisture transport and phase transitions. In this paper, we propose a soil heat and moisture migration model, along with a ground infrared radiation model. Our comparisons with previous research reveal that the internal water movement, evaporation, and condensation processes in the soil have a profound influence on the soil's temperature field and infrared signature. To validate our model's reliability, we conducted three experiments with metal blocks buried 1 cm deep, having initial moisture contents of 0 %, 10 % and 20 %. A comparison of the simulation and experimental results confirms the credibility of our proposed model. Through simulations, we analyzed the daily variations in ground surface IR radiation, the effect of varying burial depths, and the influence of differing initial moisture contents. Our findings reveal that, when starting with zero initial soil moisture content, an increase in burial depth from 1 cm to 5 cm results in a substantial decrease in the peak difference between the surface center temperature and ambient temperature, dropping from 20.91 K to 5.35 K. Consequently, the optimal detection time shifts from 12:00 to 14:00 On the other hand, keeping the burial depth constant at 1 cm and increasing the initial soil moisture content from 5 % to 20 % leads to a reduction in the maximum temperature difference from 17.54 K to 12.48 K, while the optimal detection time remains unaffected. This study can provide data support for underground buried object detection and improve the accuracy of detection.

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