LoRa-Based Localization for Drones: Methodological Enhancements Explored Through Simulations and Real-World Experiments

As the use of drones escalates, ensuring their reliable and accurate localization, especially in potential GPS-compromised situations is crucial. This paper introduces a cutting-edge localization method for drones, leveraging LoRa's long-range, low-power capabilities, ideal for drone communication. We especially focus on enhancing RSSI-based localization, commonly used for its simplicity yet prone to inaccuracies due to the large variance in received signal strength. By integrating sensor-derived altitude data and applying the Huber loss function in the optimization process of multilateration, our approach not only outperforms traditional RSSI-based techniques in accuracy but also scales better with an increasing number of beacons as demonstrated through comprehensive simulations and real-world experiments. These results highlight our method's applicability in various scenarios, such as emergency response, environmental monitoring, or delivering in dense urban environments, where GPS reliability is uncertain. This research makes a substantial contribution to the field of drone navigation, offering a robust alternative to GPS-reliant systems and paving the way for enhanced autonomous drone operations in challenging environments.