Bogdan Dolintse

Work place: Institute of Management and Strategies, Kyiv, 02166, Ukraine

E-mail: bogdan.dolintse@gmail.com

Website:

Research Interests: Control Synthesis, Data Processing

Biography

Bogdan Dolintse is currently a researcher at the Institute of Managent and Strategies, where he has gained extensive experience in his field. His areas of interest include data processing, control algorithms, multi-constellation positioning systems, precise positioning, and drone management. A total number of research publications is 19.

Author Articles
Enhancing Data Processing Methods to Improve UAV Positioning Accuracy

By Igor Zhukov Bogdan Dolintse Sergii Balakin

DOI: https://doi.org/10.5815/ijigsp.2024.03.08, Pub. Date: 8 Jun. 2024

UAVs play a crucial role in various applications, but their effective operation relies on precise and reliable positioning systems. Traditional positioning systems face challenges in delivering the required accuracy due to factors such as signal degradation, environmental interference, and sensor limitations. This study proposes the LeGNSS positioning subsystem, which integrates low Earth orbit (LEO) satellite network data with GPS and MEMS-based inertial systems, to enhance UAV positioning accuracy and reliability. The presented in this research LeGNSS system employs sophisticated algorithms for optimal data processing and filtering from various sources. Simulation results demonstrate a 9.02% improvement in positioning estimation accuracy compared to classic GPS/INS integration and a 26.4% improvement compared to the onboard GPS receiver. The integration of inertial and satellite positioning, corrective mechanisms, and optimized filtration has resulted in improved precision of trajectory computations, attenuation of positioning signal anomalies, and a significant decrease in INS inaccuracies. The proposed LeGNSS positioning system presents a solution for precise and reliable UAV positioning in a wide range of applications. By leveraging the unique advantages of LEO satellite networks and advanced data fusion techniques, this system pushes the boundaries of UAV positioning capabilities. The novel integration of multiple data sources and the use of adaptive error correction algorithms set a new standard for accuracy and robustness, paving the way for unprecedented capabilities in fields such as aerial surveying, precision agriculture, infrastructure monitoring, and emergency response. Analysing the impact of complex environmental factors on LeGNSS operation can provide insights into expanding the list of satellite systems or sensors to improve positioning accuracy, particularly in high-latitude regions. The findings of this study contribute to improving the accuracy, reliability, and resilience of UAV positioning systems, with applications in scientific polar research, geomatics data gathering, and other domains. The LeGNSS system has the potential to become a key feature for the next generation of autonomous aerial vehicles, unlocking efficiency, safety, and innovation across industries.

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