Target Detection and Classification Using Ground Penetration Radar in a Dense Terrain
Abstract
The problem of explosive object (bomb) has reluctance on the progress of Laos becauseplantation cannot be produced and hence affects to economic situation. The bomb is a metallicmaterial submerged in soil. Generally, people use a handheld metal detector to sense for such bomb and it spends long time in the large area. Hence, an equipment that can sense for bomb in a large area with high speed is desirable.A drone equipped with a ground penetrating radar (GPR) and a geo-positioning system (GPS) is agood option because it can scan for bombs in the large area with high speed. The detectedsignatures of bombs are plotted for the large area and the position of bombs can be identified. Thisresult can assist people to clean the area of interest and it can be useful for agricultural activities.Consequently, economic situation can be improved. To this end, we propose to investigate a GPR that can detect metallic bombs submerged in soil at the depth of around 30 cm from the surface. It is based on a beam-scanning reflectometer wesuccessfully developed for fruit classification. The scattered wave from a bomb will be measured indifferent directions. Then, Rician k-factor will be estimated from the ratio of mean to variance. Thedifferent values of variance indicate the existing of the bomb whereas the different mean valuesindicate different size of the bomb.This project will simulate the scattered wave from a beam-scanning antenna and calculate k-factorsfor different conditions. The results can provide information for optimal design of the light-weightand fast-computation GPR suitable for installing on a drone.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 30, 2018
- Source ID
- FA23861810111
Entities
People
- Monai Krairiksh
Organizations
- Air Force Office of Scientific Research
- United States Air Force