Synthesis of algorithm of unmanned aerial vehicle detection by acoustic noise

Abstract

 The algorithm of detection of acoustic noise provided by an unmanned aerial vehicle (UAV) in the noise background due to wind is synthesized in the article. Creation of the algorithm has been carried out using the Neyman – Pearson lemma. The algorithm assumes a combination of the stages of wind noise coherent compensation and coherent accumulation of UAV’s acoustic noise sound pressure impulses. The coherent accumulation time matches doubled time of fluctuation correlation resulted by experimental research of acoustic noise of different types of  UAVs. Efficiency of the developed algorithm of UAV detection depends on flight velocity, foreshortening, amount of blades and rotor turnovers of UAV as well as weather conditions. For the probability of a false alarm value of 10–4, the probability of correct UAV detection value of 0.9 is provided wherein signal-to-noise ratio has a value of 8 dB. These indicators correspond the detection range of 200 to 300 meters. The obtained results allow discussions about perspective of acoustic UAVs detection systems adaptation.