| Title |
Artificial Intelligent (AI) Signal Processing Approach of Subsurface Electromagnetic Radar |
|
Authors |
Ylaya,Vrian Jay ; Alvarez,Anna Ruth ; Benasing, Potrinordidan ; Gerasta,Olga Joy ; Caberos,Aileen ; Pandian,Najie |
|
Publication date |
2019/11/21 |
|
Conference |
2019 19th International Symposium on Communications and Information Technologies (ISCIT) |
| Issue |
19172031 |
| Pages |
6 |
| Publisher |
IEEE |
| Abstract |
Identification of buried objects using power spectral density spectrum depends on the experienced and trained professionals. The objective of the study is to test artificial intelligent (AI) signal processing in discriminating buried objects such as metallic, plastic, and water using a software-defined radio SDR electromagnetic radar. Pulse modulated continuous wave radar is implemented in software-defined radio (SDR) where power spectral density of reflected signal is analyzed. The analysis was performed in the test site were metallic, plastic, and water are buried in sandy soil with varying depths while capturing their respective power spectral density spectrum. The power spectral density spectrum is converted to CSV format which will be utilized to train the artificial neural network. The artificial intelligent signal processing system was able to detect 99.85% accuracy from different objects at various depths which makes convenient identification of buried objects for any user for geotechnical studies. |
| Index terms / Keywords |
artificial intelligence , buried object detection , CW radar , electromagnetic wave reflection , geophysical techniques , neural nets , radar detection , radar signal processing , software radio |
| DOI |
DOI: 10.1109/ISCIT.2019.8905214 |
| URL |
|
Mindanao State
University - Iligan Institute of Technology