Aerospace Technic and Technology

Due to the impossibility of hiding the unmanned aerial vehicles (UAV) own radiothermal radiation or reducing its contrast against the background of atmospheric radiation, it is advisable to use highly sensitive radiometric receivers to solve the detection problem. The optimal method for complexing the results of measurements in multichannel radiometric receivers and identifying different types and classes of UAV against the sky in X, Ka, and W wave ranges under different meteorological conditions has been developed. end-to-end optimization of methods and algorithms will reveal the theoretical foundations of the construction of radiometric systems, ranging from the field of registration of electromagnetic fields to the final stages. In cloudless and clear weather, radiometric measurements in the W range will allow to obtain high-precision estimates of the spatial position of UAVs, in the X range of reliable observations in rain, snow, fog. The use of the Ka-band receiver in the radiometric complex will allow to realize the best sensitivity due to the technical achievements of domestic production in the creation of broadband radiometric receivers in this waveband. Studies of the main parameters of UAV detection have been conducted, namely, the probability of erroneous detection alarm and the probability of correct detection. The obtained theoretical results allow to determine signal processing algorithms and optimal structures of radiometric receivers, to analyze the maximum measurement error and to develop recommendations for experiments. Having received a database of radiometric contrasts, it is possible to further implement technical solutions to increase the capabilities of airspace monitoring for UAV detection. Recommendations are given for the practical choice of the UAV detection threshold to ensure the probability of correct detection is not worse than 0.9 for different angles of observation, atmospheric state, size and material of manufacture.

radiometry; UAV detection; optimization of algorithms; probabilistic characteristics

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