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Influence of IQT on research in ICT. Part 2

Suszyński Piotr, Dubiński Jan, Ignaciuk Adam, Jimenez-Soler Pedro, Pituła Emil W., Wójtowicz Piotr, Romaniuk Ryszard S.

International Journal of Electronics and Telecommunications

2025

Vol. 71, No. 1

225-234

The advanced Quantum Information Technologies subject for Ph.D. students in Electronics Engineering and ICT consists of three parts. A few review lectures concentrate on topics which may be of interest for the students due to their fields of research done individually in their theses. The lectures indicate the diversity of the QIT field, resting on physics and applied mathematics, but possessing wide application range in quantum computing, communications and metrology. The individual IQT seminars prepared by Ph.D. students are as closely related to their real theses as possible. Important part of the seminar is a discussion among the students. The task was to enrich, possibly with a quantum layer, the current research efforts in ICT. And to imagine, what value such a quantum enrichment adds to the research. The result is sometimes astonishing, especially in such cases when quantum layer may be functionally deeply embedded. The final part was to write a short paragraph to a common paper related to individual quantum layer addition to the own research. The paper presents some results of such experiment and is a continuation of previous papers of the same style.

Mitigating sensor quality issues in UAV system identification through wavelet decomposition

Jimenez-Soler Pedro, Lichota Piotr

Bulletin of the Polish Academy of Sciences. Technical Sciences

2025

Vol. 73, nr 1

art. no. e152216

Unmanned aerial vehicles (UAVs) require precise system identification for optimal performance and safety, yet sensor noise and signal distortion frequently compromise data quality. Recent studies have explored various approaches to mitigate these issues. However, this study introduces a novel method that utilizes wavelet transform techniques, distinctively enhancing UAV sensor signal processing. Unlike conventional methods that primarily focus on noise reduction, this approach employs multi-resolution wavelet decomposition to denoise and align signals effectively, crucial for accurate system identification. This systematic exploration of various wavelet bases and the application of the output error method for correlating signals provide a unique combination not extensively covered in current literature. The technique was validated using simulated sensor data at 50 Hz from a small UAV platform, the Multiplex®Fun Cub, specifically targeting longitudinal dynamics response. Results demonstrated substantial improvements in signal quality, with significantly enhanced correlation coefficients, showcasing the potential of our wavelet techniques to refine UAV system analysis. This paper presents a comprehensive framework for applying wavelet-based techniques in UAV system identification, significantly advancing the robustness and reliability of identification processes and distinguishing our work from existing methods by its integration of wavelet decomposition and advanced system identification techniques.