Numerical Modeling and Measurement of Apis Mellifera Radar Scattering Properties

Omar Alzaabi, Mohammad M. Al-Khaldi, Kenneth Ayotte, Diego Penaloza, Julio Urbina, James K. Breakall, Michael Lanagan, Harland M. Patch, Christina M. Grozinger

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This study investigates a means through which commercially available computational electromagnetic modeling software can be used to predict radar cross sections (RCSs) of airborne organisms of interest as a preliminary step toward enabling detection and tracking of these organisms. This work aims to analyze this framework for the specialized case of the honey bee (Apis mellifera), given its critical role in food security as a major pollinator of agricultural crops. A Method-of-Moment (MoM) solver made available by Altair's FEKO is used to conduct the analysis over varying frequencies, illumination angles, and polarizations. A high degree of correlation between measured and modeled cross sections is noted. Maximum RCS root-mean-square errors (RMSEs) between the two are approximately 4 and 5 dB relative to 1 $\text{m}^{2}$ (dBsm) for Horizontal polarization (H-pol) and Vertical polarization (V-pol) X-band measurements, respectively. Findings of this study also highlight the sensitivity of both modeled and measured RCS estimates to the dielectric properties of honey bees and the corrupting effects that this may have if not accounted for accurately, where errors are shown to increase from 2 to 5 dBsm, but without significantly corrupting the overall RCS azimuth profile.

Original languageBritish English
JournalIEEE Geoscience and Remote Sensing Letters
Volume19
DOIs
StatePublished - 2022

Keywords

  • Dielectric characterization
  • FEKO
  • method of moments
  • radar cross section (RCS)

Fingerprint

Dive into the research topics of 'Numerical Modeling and Measurement of Apis Mellifera Radar Scattering Properties'. Together they form a unique fingerprint.

Cite this