The Processing of Signals from Sensors to Observe Objects in Various Physical Fields

被引：0

作者：

Lutin, Vladimir I. ^{[1
]}

Desyatirikova, Elena N. ^{[2
]}

Kuripta, Oksana V. ^{[2
]}

Akamsina, Nadezhda V. ^{[2
]}

Mager, Vladimir E. ^{[3
]}

机构：

[1] Air Force Acad, Mil Educ & Sci Ctr Air Force, Voronezh, Russia

[2] Voronezh State Tech Univ, Voronezh, Russia

[3] Peter Great St Petersburg State Polytech Univ, Inst Comp Sci & Technol, Highest Sch Cyberphys Syst & Control, St Petersburg, Russia

来源：

PROCEEDINGS OF THE 2018 IEEE CONFERENCE OF RUSSIAN YOUNG RESEARCHERS IN ELECTRICAL AND ELECTRONIC ENGINEERING (EICONRUS) | 2018年

关键词：

theory of hypothesis discrimination; Bayesian risk; likelihood ratio; sufficient statistics; simulation modeling;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Based on the theory of distinguishing statistical hypotheses, an algorithm for detecting objects based on the results of joint observation in several physical fields was synthesized. The quality of the work of the synthesized algorithm is analyzed and comparison results with heuristic algorithms are shown, which show the advantage of complex processing of signals from image sensors. The algorithm was developed within the framework of the theory of distinguishing statistical hypotheses. The efficiency of complex signal processing by simulation is estimated. It is established that an increase in observation media leads to an improvement in the quality of the discrepancy between hypotheses.

引用

页码：1113 / 1116

页数：4

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