Efficiency criteria for digital adaptive systems for remote detection and recognition of dangerous objects

Keywords: adaptation, antenna array, training sample, detection, recognition, interference

Abstract

The article pays special attention to increasing the requirements for the security of objects of special importance, the state border, water and air transport in the face of growing high-tech terrorist threats. The achievement of these requirements is inextricably linked with the provision of quality indicators of technical means of remote monitoring of dangerous objects, the complexity and intellectualization of location systems, sensor networks with the functions of network-centric interaction. The use of electronic countermeasures by the enemy, the rapid change of scenarios of combined interference determine trends that are aimed at increasing the probability of obtaining information in location systems, adaptation to the interference of various origins at short intervals. Lack of reliable information about the presence of the object can lead to unacceptable environmental and material losses, and false alarms – to unjustified additional costs. In this regard, an important area is to provide the most reliable information in the face of interference of various origins. The urgency of the problem is related to the search for a compromise between costs (cost and time of development) to build adaptive detection and recognition systems, and on the other hand, efficiency (simulation probability, implementation complexity), which is achieved by developing optimization criteria. At the same time, special attention is paid to ensuring high-quality indicators of detection and recognition in the conditions of changing and a priori unknown noise situation.

An approach and criteria for the synthesis and analysis of digital adaptive detection and recognition systems have been developed. The criteria are based on the decomposition of the average risk and the probability of errors in the decisions made, due to: the final size of the system, the size of the training sample and the bit count. This approach allows you to consistently solve the problem of synthesis and analysis of optimal systems.

Downloads

Download data is not yet available.

References

Identification of Potential Terrorists and Adversary Planning. Emerging Technologies and New Counter-Terror Strategies / Editors Gordon, T. J., Florescu, E., Glenn, J. C., Sharan, Y. Proceedings of the NATO Advanced Research Workshop. Washington : 2017. 196 p.

Shults V. L. (Ed.) (2012). Otsenka krizisnyih situatsiy i terroristicheskih ugroz natsionalnoy bezopasnosti: monografiya: v 2 kn., Kn. 2. Moscow, Russia : Nauka. 139 s. [In Russian].

Repin V. G., Tartakovskiy G. P. (1977). Statisticheskiy sintez pri apriornoy neopredelennosti i adaptatsiya informatsionnyih sistem. Moscow, Russia : Sov.radio 432 s. [In Russian].

Shirman Ya. D. (Ed.) (2007). Radioelektronnyie sistemyi. Osnovyi postroeniya i teoriya. Moscow, Russia : Radiotehnika, 512 s. [In Russian].

Fomin Ya. A., Tarlovskiy G. R. (1986). Statisticheskaya teoriya raspoznavaniya obrazov. Moscow, Russia: Radio i svyaz. 264 s. [In Russian].

Zaytsev A. I. (2018). Terrorizm – voyna buduschego. Tehniko-tehnologicheskie problemyi servisa №1(43) S. 126-133. [In Russian].

Zagorka O. M., Koval V. V., Zharik O. M. (2013). Do pitannya obgruntuvannya pokaznikIv I kriteriyiv efektivnosti protipovitryanoyi oboroni // Nauka i tehnika Povitryanih Sil Zbroynih Sil Ukrayini. № 2. S. 35-40. Available from: http://nbuv.gov.ua/ UJRN/Nitps_2013_2_8. [In Ukrainian].

Zharik A. N. (2011). Vyibor edinyih pokazateley i kriteriev effektivnosti funktsionirovaniya sistem PVO vazhnyih gosudarstvennyih ob'ektov. Sistemi ozbroennya i viyskova tehnika. №2 (26), S. 199–204. [In Russian].

Shinkaruk O. N., Lenkov E. S., Semibalamut K. M. (2011). Effektivnost obnaruzhitelya na osnove algoritma Keypona pri mnogokanalnom priyome signalov bolshoy dlitelnosti. Visnik Hmelnitskogo natsionalnogo universitetu. №5. S. 217–221. [In Russian].

Ksendzuk A. V., Kozlov K. O. (2019). Adaptivnyiy korrelyator v neizluchayuschey radiolokatsionnoy sisteme // Voprosyi radioelektroniki. № 3. S. 41–45. DOI: 10.21778/2218-5453-2019-3-41-45. [In Russian].

Popov D. I. (2018). Adaptivnoe obnaruzhenie gruppovyih mnogochastotnyih signalov. Visnyk NTUU KPI Seriia – Radiotekhnika Radioaparatobuduvannia, № 74, S. 44–50. [In Russian].

Ezuma M., Erden F., Anjinappa C. K., (et al.). (2019). Micro-UAV Detection and Classification from RF Fingerprints Using Machine Learning Techniques, 2019 IEEE Aerospace Conference, 2019, pp. 1-13, DOI: 10.1109/AERO.2019.8741970.

Catalin Dumitrescu, Marius Minea, Ilona Madalina Costea, Ionut Cosmin Chiva, Augustin Semenescu (2020). Development of an Acoustic System for UAV Detection. Journal Sensors, Sep; 20(17): 4870; Pp. 1-27. DOI: 10.3390/s20174870.

Pyatakovich V. A. (2017). Metodologiya otsenki effektivnosti radiogidroakusticheskih sredstv v strukture neyro-ekspertnoy sistemyi monitoringa morskih akvatoriy gosudarstva. Internet-zhurnal «Naukovedenie». Vol 9, №5. Available from: https://naukovedenie.ru/PDF/24TVN517.pdf

Koce G., Yegin K. Footstep and Vehicle Detection Using Slow and Quick Adaptive Thresholds Algorithm. International Journal of Distributed Sensor Networks. 2013. 9 pages. URL: 10.1155/2013/783604.


Abstract views: 172
PDF Downloads: 121
Published
2021-10-28
How to Cite
Orlov , V., Demianchuk , B., Klimenko , V., Serhii , Y., Tarasov, O., & Semenenko , L. (2021). Efficiency criteria for digital adaptive systems for remote detection and recognition of dangerous objects. Journal of Scientific Papers ʽʽSocial Development and Security’’, 11(5), 119-132. https://doi.org/10.33445/sds.2021.11.5.12
Section
Articles

Most read articles by the same author(s)