Increasing the Security Level of Critical Transport Infrastructure Facilities Based on Geospatial Analysis of Acoustic Portraits of Air Threats
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Abstract
The article discusses an approach to improving the safety of facilities that do not interrupt technological processes after an air raid alert, in particular, critical transport infrastructure, based on object-based identification of air hazards. Existing methods for detection and recognition of the air targets, such as attack drones and cruise missiles, are reviewed. It has been determined that for early detection of air hazards at the local level, the acoustic identification method is effective in terms of cost, simplicity and range. To implement it, the structure of the identification system is considered, built on the basis of the use of modern element base, including highly sensitive acoustic sensors capable of distinguishing sounds at a distance of up to 2.5 km and a system for processing and radio transmission of information at the distance of up to 10 km.
To identify various types of air hazards by their acoustic radiation and separate it from extraneous noise, unique acoustic portraits of attack drones and cruise missiles are identified in the research on the base of spectral analysis. For this purpose, a statistical study was carried out of a large volume of data of the acoustic noise of drones and cruise missiles, the information is obtained from the open sources. The resulting acoustic portraits of various types of air hazards in the form of the spectral density of the acoustic signal reflect the significant distinctive features of the amplitude-frequency characteristics of acoustic radiation depending on the type of air hazard.
In order to implement the proposed method, a special device for measuring the acoustic signal and other digital parameters with wireless data transmission based on ZigBee and LoRaWan technologies has been developed. The device can be configured to distinguish between low-intensity sounds and noises in the required frequency ranges inherent in acoustic portraits, after the identification it switches from “sleep mode” to active mode, which ensures its energy efficiency.
