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Energy and Nvidia Sionna-Based Signal Integrity: Selection Design for Off-the-Shelf Synthetic Aperture Radar-Capable Unmanned Aerial Vehicles

Victor B. Calinao Jr. 1*, Edwin Sybingco 1, Argel A. Bandala 1, and Lawrence Materum 1,2
1. Department of Electronics and Computer Engineering, Gokongwei College of Engineering, De La Salle University, Philippines
2. Tokyo City University, Japan

Abstract—This paper presents the relationship between energy and signal integrity of Unmanned Aerial Vehicles (UAVs) with Synthetic Aperture Radar (SAR) capabilities for a more informed off-the-shelf selection design. The energy is expressed in the UAV and SAR power consumption, whereas signal integrity is expressed in Bit-Error Rate (BER). Low-end, mid-end, and highend—categorized in terms of their market cost—commercial UAVs and SAR modules were considered. The energy relations are based on the UAV flight path and power ratings. The signal processing and decomposition of the reconstructed objects for the model simulations are based on a transmit channel-receive chain of 16-quadrature-amplitude, low-density parity check, Rayleigh response, and single-antenna directivity done through Nvidia Sionna. The results indicate that far-reaching flight spatial path scanning is achieved with high-end UAVs and low-cost SARs, but the accuracy is relatively low. Higher accuracy is achieved with low-end UAVs with high-cost SARs. Further, the results point out that selecting UAV-SAR is critical in terms of energy and accuracy for a specific target application. The outcomes show tradeoffs in the selection design.
 
Index Terms—Synthetic Aperture Radar (SAR), Unmanned Aerial Vehicles (UAV), Bit-Error Rate (BER), rayleigh fading, nvidia sionna, energy, signal integrity, selection design

Cite: Victor B. Calinao Jr., Edwin Sybingco, Argel A. Bandala, and Lawrence Materum, "Energy and Nvidia Sionna-Based Signal Integrity: Selection Design for Off-the-Shelf Synthetic Aperture Radar-Capable Unmanned Aerial Vehicles," Journal of Communications vol. 18, no. 1, pp. 29-35, January 2023. Doi: 10.12720/jcm.18.1.29-35
 
Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.