401. Geometric Parameter Estimation of Buried Objects in Near-Field Microwave Images
- Author
-
Kai Ren and Robert J. Burkholder
- Subjects
Computer science ,Estimation theory ,business.industry ,Orientation (computer vision) ,Near and far field ,Geotechnical Engineering and Engineering Geology ,Object (computer science) ,Radar imaging ,Shadow ,Computer vision ,Artificial intelligence ,Electrical and Electronic Engineering ,Projection (set theory) ,business ,Microwave - Abstract
We present a method to estimate and quantify geometric parameters of a buried object in near-field microwave images. These parameters are shape, location, size, and orientation. Unlike the parameter estimation based on a conventional ground-penetrating radar image, a 3-D well-focused coherent image is generated. Instead of choosing a z-slice of the 3-D image, both 2-D projection and shadow projection images are used to perform the parameter estimation. The shape of the buried object is determined based on both x- and y-polarized images. Other geometric parameters, such as location, size, and orientation, are estimated by the method of spatial moments. Both numerical and experimental data of an object buried in a dielectric slab are used to demonstrate the efficacy of the proposed geometric parameter estimation algorithm.
- Published
- 2022