Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

AAFIYA: Antenna Analysis in Frequency-domain for Impedance and Yield Assessment

Mohammad Ful Hossain Seikh, Rachel Jarvis, James Stiles

TL;DR

AAFIYA addressing the need for reproducible RF antenna characterization, introduces a modular Python toolkit that ingests measurement and simulation data (e.g., Touchstone $S$-parameter files and beam-pattern data) to compute metrics such as $S_{11}$, $S_{21}$, impedance, realized gain, beam patterns, polarization metrics, and calibration-based yield. The approach is validated with LPDA reference antennas and ARA BVPol antennas across 100–850 MHz, showing good agreement with full-wave simulations from HFSS and WIPL-D, and producing publication-ready visualizations. The work provides a flexible, extensible foundation for experimental campaigns and data-driven antenna design, with future directions toward automated optimization and deeper integration with simulation/analysis pipelines.

Abstract

This paper presents AAFIYA (Antenna Analysis in Frequency-domain for Impedance and Yield Assessment), a modular Python toolkit for automated characterization of radio-frequency antennas using measurement and simulation data. The toolkit provides a unified workflow for processing S-parameters, impedance, realized gain, beam patterns, polarization metrics, and calibration-based yield estimation, with support for standard Touchstone files and beam pattern data. AAFIYA is validated using measurements from an electromagnetic anechoic chamber involving Log Periodic Dipole Array (LPDA) reference antennas and Askaryan Radio Array (ARA) Bottom Vertically Polarized antennas over 100-850 MHz. Extracted metrics, including impedance matching, realized gain patterns, vector effective lengths, and cross-polarization ratio, are compared against full-wave simulations from HFSS and WIPL-D, showing good agreement across frequency and angle. The results demonstrate that AAFIYA enables accurate, reproducible, and publication-ready antenna analysis, and provides a flexible foundation for future extensions, including automated optimization and data-driven antenna design.

AAFIYA: Antenna Analysis in Frequency-domain for Impedance and Yield Assessment

TL;DR

AAFIYA addressing the need for reproducible RF antenna characterization, introduces a modular Python toolkit that ingests measurement and simulation data (e.g., Touchstone -parameter files and beam-pattern data) to compute metrics such as , , impedance, realized gain, beam patterns, polarization metrics, and calibration-based yield. The approach is validated with LPDA reference antennas and ARA BVPol antennas across 100–850 MHz, showing good agreement with full-wave simulations from HFSS and WIPL-D, and producing publication-ready visualizations. The work provides a flexible, extensible foundation for experimental campaigns and data-driven antenna design, with future directions toward automated optimization and deeper integration with simulation/analysis pipelines.

Abstract

This paper presents AAFIYA (Antenna Analysis in Frequency-domain for Impedance and Yield Assessment), a modular Python toolkit for automated characterization of radio-frequency antennas using measurement and simulation data. The toolkit provides a unified workflow for processing S-parameters, impedance, realized gain, beam patterns, polarization metrics, and calibration-based yield estimation, with support for standard Touchstone files and beam pattern data. AAFIYA is validated using measurements from an electromagnetic anechoic chamber involving Log Periodic Dipole Array (LPDA) reference antennas and Askaryan Radio Array (ARA) Bottom Vertically Polarized antennas over 100-850 MHz. Extracted metrics, including impedance matching, realized gain patterns, vector effective lengths, and cross-polarization ratio, are compared against full-wave simulations from HFSS and WIPL-D, showing good agreement across frequency and angle. The results demonstrate that AAFIYA enables accurate, reproducible, and publication-ready antenna analysis, and provides a flexible foundation for future extensions, including automated optimization and data-driven antenna design.
Paper Structure (11 sections, 2 equations, 5 figures)

This paper contains 11 sections, 2 equations, 5 figures.

Table of Contents

  1. Introduction
  2. Toolkit Overview
  3. Measurement and Calibration
  4. S-Parameter Measurements
  5. Beam Pattern Measurements
  6. Gain Extraction and Calibration
  7. Results
  8. S-Parameter Analysis
  9. Gain Pattern Analysis
  10. Validation with Simulation
  11. Conclusion

Figures (5)

  • Figure 1: ARA BVPol S-parameter characterization. Top: Measured complex input impedance as a function of frequency. Bottom: Summary of $S_{11}$-derived metrics, including resonance frequency, return loss, bandwidth, VSWR performance, and impedance at resonance.
  • Figure 2: Isolation and reverse isolation as a function of frequency for the Tx–Rx LPDA H-Plane configuration, demonstrating strong port separation across the operational band.
  • Figure 3: ARA BVPol gain characteristics. Top: RVEL as a function of frequency and azimuth. Middle: Cross-polarization ratio (XPR) in the zenith plane, quantifying polarization purity. Bottom: Realized gain pattern in the zenith plane.
  • Figure 4: LPDA reference antenna gain metrics. Top: Co-polarization boresight gain as a function of frequency for the H-, V-, and Z-Planes. Bottom: Front-to-back (F/B) ratio versus frequency for the same Planes.
  • Figure 5: Validation of measurement and simulation. Top: Comparison of measured and HFSS-simulated $|S_{11}|$ for the ARA BVPol antenna. Middle: Measured LPDA realized gain pattern in the H-Plane. Bottom: Corresponding WIPL-D simulated realized gain pattern from NuRadioMC.