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UAV-based near-field to far-field transformation for a detailed characterization of large outdoor emitters in operation

Subject Area Measurement Systems
Communication Technology and Networks, High-Frequency Technology and Photonic Systems, Signal Processing and Machine Learning for Information Technology
Term since 2024
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 541019206
 
The description of wave propagation in the atmosphere is of great interest to scientists in various fields of physics. Characterizing emitters is particularly crucial in this regard. Although small emitters can usually be examined in specialized laboratory measurements, characterizing large emitters using conventional methods often proves inadequate. Such large emitters can be of acoustic or electromagnetic nature, including examples such as wind turbines, biogas power plants, antennas, and radar systems. In this project, we are developing an innovative measurement method that allows for the characterization of the performance and directional characteristics of large emitters during their operation without modification. This method is based on the use of drones equipped with modern measurement equipment, that can move freely in the proximity of the emitters. Subsequently, we apply a special transformation calculation to extract the characteristics of the emitters from discrete measurement data on their surfaces. These acquired data are of particular importance, as they enable reconstruction of the far field of the emitters. The principles of wave propagation are subject to similar mathematical laws in different disciplines. Therefore, our method is easily transferable from electromagnetic to acoustic fields. In our project, we demonstrate this interdisciplinary applicability and expect results that are of significant interest in various ways. Furthermore, we examine the uncertainties associated with our method, particularly concerning the challenging measurement conditions on a flying platform. To do this, we use the numerical, analytical, and experimental data collected within the project and incorporate them into statistical models to determine the uncertainty of the measurement. On the basis of these investigations, we develop measurement platforms of varying complexity in regard to position, time, and measurement variables, weighing them against the expected accuracies. Upon completing the project, we present a flying measurement platform and demonstrate the effectiveness of our method. Additionally, we discuss potential weaknesses and the scalability of the method in terms of the number of drones used and the measurement equipment employed. We are confident that such flying measurement platforms will contribute to more accurate far-field predictions and improved calibration of large emitters in the future.
DFG Programme Priority Programmes
 
 

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