Remote characterization of chloride content in oven-dried concrete specimens by using synthetic aperture radar image models

Abstract Synthetic aperture radar (SAR) imaging is a remote sensing technique capable of performing noncontact subsurface inspection of dielectric materials like Portland cement concrete. Such techniques can be applied to field inspection of concrete structures and laboratory material characterization. The objective of this paper is to demonstrate the application of SAR imaging on characterizing chloride content inside oven-dried concrete specimens, using a 10-GHz central frequency SAR imaging sensor. Twelve concrete panel specimens (0.3x0.3x0.05 m3) with a 0.45 water-to-cement ratio were manufactured in six groups of different chloride contents (0%, 2%, 4%, 6%, 8% and 10% of cement weight). Five SAR image-based parameters were developed from each SAR image of concrete specimens for chloride, including integrated SAR amplitude of back reflection I int b , integrated amplitude I int , average maximum amplitude I - max , critical contour area A c , and average Gaussian curvature of critical contour K avg . A parametric analysis on the combined use of different numbers of SAR image parameters was carried out to determine the optimal application of SAR image parameters on the chloride detection problem in this paper. From our result, it is found that, for the purpose of chloride detection inside concrete specimens using single SAR parameter, integrated amplitude I int shows the best performance. When using two SAR image parameters, combination of integrated amplitude I int and critical contour area A c shows the best performance among other two-parameter combinations. When using three SAR image parameters, combination of integrated amplitude I int , critical contour area A c , and average maximum amplitude I - max shows the best performance among other three-parameter combinations. Furthermore, it is interesting to report that combination of three SAR image parameters ( I int , A c , and I - max ) provides the overall best performance among all other combinations for the chloride detection problem in oven-dried concrete specimens.