Artificial Intelligent (AI) Signal Processing Approach of Subsurface Electromagnetic Radar
| Autor: | Anna Ruth Alvarez, Potrinordid'dan Benasing, Vrian Jay V. Ylaya, Aileen B. Caberos, Olga Joy L. Gerasta, Najie M. Pandian |
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| Rok vydání: | 2019 |
| Předmět: |
Signal processing
Artificial neural network business.industry Computer science 010401 analytical chemistry 0211 other engineering and technologies Spectral density 02 engineering and technology 01 natural sciences Signal Physics::Geophysics 0104 chemical sciences Pulse (physics) law.invention Continuous-wave radar Identification (information) law Artificial intelligence Radar business 021101 geological & geomatics engineering |
| Zdroj: | ISCIT |
| DOI: | 10.1109/iscit.2019.8905214 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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