Citation: Marzioli, P.; Garofalo, R.; Frezza, L.; Nyawade, A.; Santilli, G.; JahJah, M.; Santoni, F.; Piergentili, F. Performance Analysis of a Wildlife Tracking CubeSat Mission Extension to Drones and Stratospheric Vehicles. Drones 2024, 8, 129. https://doi.org/ 10.3390/drones8040129 Academic Editors: Kate Brandis and Roxane Francis Received: 11 July 2023 Revised: 22 March 2024 Accepted: 26 March 2024 Published: 29 March 2024 Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). drones Article Performance Analysis of a Wildlife Tracking CubeSat Mission Extension to Drones and Stratospheric Vehicles Paolo Marzioli 1, * , Riccardo Garofalo 2 , Lorenzo Frezza 2 , Andrew Nyawade 3 , Giancarlo Santilli 4 , Munzer JahJah 4 , Fabio Santoni 2 and Fabrizio Piergentili 1 1 Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy 2 Department of Astronautics, Electrical and Energy Engineering, Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy 3 Kenya Space Agency, Pitman House, Jakaya Kikwete Rd, Nairobi, Kenya 4 Italian Space Agency (ASI), Via del Politecnico, 00133 Rome, Italy * Correspondence: paolo.marzioli@uniroma1.it Abstract: This study presents a performance analysis for an Internet-of-Things wildlife radio-tracking mission using drones, satellites and stratospheric platforms for data relay with Spread Spectrum Modulation devices. The performance analysis is presented with link and data budgets, calculations of the area coverage, an estimation of the time resolution and allowable data amount of each collar, a power and energy budget and consequent battery pack and collar weight estimations, cost budgets, and considerations on synergetic approaches to incorporate more mission segments together. The paper results are detailed with example species to target with each collar weight range, and with design drivers and guidelines to implement improved mission segments. Keywords: CubeSat; stratosphere; drone; UAV; wildlife tracking; human–wildlife conflict; satellite; radio; tracking 1. Introduction In recent years, the need for more thorough wildlife tracking and management [1], with a focus on the growing urbanization [2,3], agricultural advancement [4–9] and defor- estation [10] of countries hosting richer biodiversity and a wider variety of animal species, has met the opportunities provided by rising technologies such as remote sensing, artificial intelligence, satellite navigation and tracking. Animal tracking technologies are in general relying on a multiplicity of engineering disciplines to carry out feasible and affordable methods for monitoring and tracing animals. Wildlife radio-tracking has been developed since the 1960s with simple methods retrieved from standard aeronautics and space methodologies and techniques. As an example, radio-tracking was at first performed with direction tracking [11], as per elder aircraft radio-navigation techniques. The transition to a broader utilization of GNSS (Global Navigation Satellite Systems) chips within collars has been progressively improved since the 1990s [12,13], allowing for better tracking of far-ranging species and for resolution improvement in the collected data [14]. UAV-based tracking for wildlife [15,16] is usually based on optical or radar-based monitoring techniques [17–22]. However, an evolution from “traditional” hand-held radio- tracking methodologies to drone-based radio-tracking [14] can significantly increase the capacity and performance of these tracking methods and they are under testing. In general, autonomous wildlife radio-tracking can save manpower, adopt more comprehensive ap- proaches and improve accuracy and precision in tracking, justifying the generally higher costs of implementation of such systems with respect to hand-held devices. Drones 2024, 8, 129. https://doi.org/10.3390/drones8040129 https://www.mdpi.com/journal/drones