Mathematical modelling of unmanned aerial vehicle based wideband spectrum sensing
DOI:
https://doi.org/10.30837/rt.2024.4.219.09Keywords:
mathematical model, unmanned aerial vehicle, spectrum sensing, signal source, signal strengthAbstract
The number of low-power radio electronic devices is constantly increasing in modern information society. The detection of such radio frequency sources (RFS), their localization and parameters estimation using stationary radio monitoring equipment, especially in cities, is ineffective. By placing a sensor on an unmanned aerial vehicle (UAV), it is possible to collect data about spatial, frequency and time parameters of RFS in a certain volume by flying around it and analyzing received signals. The absence or incompleteness of a priori information about the RFS and the radio wave propagation medium requires the creation of an appropriate mathematical model that will take into account the unknown parameters of RFS and the radio wave propagation medium, as well as the movement of radio sensor. The aim of the article is to optimize the process of analyzing the electromagnetic environment using a panoramic spectrum sensor placed on UAVs by developing a mathematical model of the received signal that takes into account the effects of radio wave propagation caused by UAVs’ movement. It was found that the change of received signal strength depends on distance between the transmitter and the receiver is determined by propagation losses, shadowing, fading due to multipath propagation and the non-isotropy of the directional patterns of the RFS. Processing received signal strength, taking into account the terrain and the location of other objects on the UAV flight trajectory, will allow us to approximately estimate the location of RFS provided that its position remains unchanged. An increase in the number of flights along different routes will increase the accuracy of estimating the coordinates of RFS. In result of the research, a mathematical model was obtained that describes the received signal strength under the influence of multi-scale fading and takes into account the scanning mode of the radio sensor, its movement, and unknown shape of the RFS antenna pattern. in modern information society, Proposals were made to separate fading components using low-pass filtering. This will make it possible to estimate the location of the RFS in the case of joint processing of the measured values of the received signal strength and the UAV flight trajectory.
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