Modeling of Cavities Detection in The Tree Stemsection Using Radar Vector Network Analyzer (VNA) Elaborating Radon Transform

  • Aldi Rivaldi Dwinanda Telkom University
  • Bambang Setia Nugroho Telkom University
  • Aloysius Adya Pramudita Telkom University

Abstract

Trees are one of the most useful plants for life on earth. However, trees can be harmful due to cavities in the stem sections. Rapid detection is needed to prevent several losses that may arise due to fallen trees. This research identified a hollow and non-hollow tree stem section of flamboyant tree with a sub-surface detection radar system. The sub surface detection radar system was modeled using a Vector Network Analyzer (VNA) connected to a Vivaldi antenna. VNA emitted electromagnetic waves to the tree stem section and subsequently propagated and penetrated hollow tree stem section. The propagation wave met the boundary plane between the wood and the cavity which reflected the electromagnetic waves. The reflected wave was caught by antenna and was display by the VNA as S-Parameter. This research used a Vivaldi antenna with a working frequency of 1 GHz – 10 GHz and a VNA with working frequency 300KHz - 8GHz. The difference in the amplitude of the signal could be seen from the results of cavity measurements made at one point. By implementing circular scanning method with inverse radon transformation, this research could identify a 19 cm diameter wood with a hole of 6 cm and 9.5 cm diameter filled with water, respectively. It was observed that the optimal detection was obtained by placing object between the antennas. This research has signified the application of radar modeled with VNA for detecting the cavities in tree stem section.

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Published
2022-06-30
How to Cite
DWINANDA, Aldi Rivaldi; NUGROHO, Bambang Setia; PRAMUDITA, Aloysius Adya. Modeling of Cavities Detection in The Tree Stemsection Using Radar Vector Network Analyzer (VNA) Elaborating Radon Transform. JMECS (Journal of Measurements, Electronics, Communications, and Systems), [S.l.], v. 9, n. 1, p. 29-38, june 2022. ISSN 2477-7986. Available at: <//journals.telkomuniversity.ac.id/jmecs/article/view/5370>. Date accessed: 25 apr. 2024. doi: https://doi.org/10.25124/jmecs.v9i1.5370.
Section
Radar