Detection-Recognition of Unmanned Aerial Vehicles Using the Composed Auto-Regression Model of Their Acoustic Radiation

Тихонов, В. А.; Карташов, В. М.; Леонидов, В. И.; Тимошенко, Н. В.; Рыбников, Н. В.; Селезнев, И. С.; Олейников, В. Н.

Публікація:
Detection-Recognition of Unmanned Aerial Vehicles Using the Composed Auto-Regression Model of Their Acoustic Radiation

dc.contributor.author	Тихонов, В. А.
dc.contributor.author	Карташов, В. М.
dc.contributor.author	Леонидов, В. И.
dc.contributor.author	Тимошенко, Н. В.
dc.contributor.author	Рыбников, Н. В.
dc.contributor.author	Селезнев, И. С.
dc.contributor.author	Олейников, В. Н.
dc.date.accessioned	2021-06-10T08:05:05Z
dc.date.available	2021-06-10T08:05:05Z
dc.date.issued	2020
dc.description.abstract	When solving the actual task of detecting by its own acoustic emission (AE) unmanned aerial vehicles (UAVs), making a potential threat to various areas of human activity, it becomes necessary to distinguish its signal from all other acoustic noises. The application of the autoregression model, widely used in practice, is complicated by the need to use significantly high orders of the model, since the distinguishing features of the UAV acoustic signal that differ it from other signals are located in the low-frequency region of the spectrum. The article proposes the use of a composite autoregression model that adequately describes the correlation properties of a signal at significant time intervals and provides an increase in spectral resolution in the low-frequency region. Experimental studies carried out on using the proposed mathematical model show significant differences in the spectral power density (SPD) of UAVs AE from SPD of various sources’ noise, which improve the quality characteristics of the UAV detection-recognition problem. A simplified procedure is proposed for determining frequencies of SPD peaks of a long-term autoregression model without spectrum calculation, which is advisable to use when working in real time.	uk_UA
dc.identifier.citation	Detection-Recognition of Unmanned Aerial Vehicles Using the Composed Auto-Regression Model of Their Acoustic Radiation / В. А. Тихонов, В. М. Карташов, В. Н. Олейников, В. И. Леонидов, Л. П. Тимошенко, И. С. Селезнев, Н. В. Рыбников // Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia. – 2020. – № 81.– pp. 38-46.	uk_UA
dc.identifier.other	doi.org/10.20535/RADAP.2020.81.38-46
dc.identifier.uri	https://openarchive.nure.ua/handle/document/16409
dc.language.iso	en	uk_UA
dc.publisher	Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia	uk_UA
dc.subject	recognition	uk_UA
dc.subject	acoustic signal	uk_UA
dc.subject	unmanned aerial vehicle	uk_UA
dc.subject	autoregressive model	uk_UA
dc.subject	power spectral density	uk_UA
dc.subject	detection	uk_UA
dc.title	Detection-Recognition of Unmanned Aerial Vehicles Using the Composed Auto-Regression Model of Their Acoustic Radiation	uk_UA
dc.type	Article	uk_UA
dspace.entity.type	Publication