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This paper presents a method of fusion of identification (attribute) information provided by two types of sensors: combined primary and secondary (IFF) surveillance radars and ESM (Electronic Support Measures). In the first section is adopted the basic taxonomy of attribute identification in accordance with the standards of STANAG 1241 ed. 5 and STANAG 1241 ed. 6 (draft). These standards provide the...
This paper presents a method of determining the basic belief assignment of the identification information provided by combined primary and secondary (IFF) radars. These types of sensors are the primary source of surveillance information about air and maritime objects. The basis of theoretical considerations is Dezert-Smarandache theory of inference. In this paper is adopted the basic taxonomy of attribute...
This paper presents the results of numerical experiments devoted to examination of influence of the target attribute hypotheses definitions on quality of information fusion. The main goal of the research works presented herein was to find answers to the subsequent questions: ‘In the context of attribute information fusion in C2 systems, is it reasonable to extend the information scope of a sensor?’...
This paper describes what particular pieces of information about source should be taken into account to get a reasonable assessment of attribute information based on the sensor data or human originated information. It has been proven that actual sensor weights and hypotheses masses do not change randomly, but they vary in time according to tracked target motion, however not directly to the target...
XML language is a standard for creating rules of designed data formats. Single documents are mostly defined by XML schemas. As the basis for XML information model one can utilize UML class diagram model. This paper presents an example of application of the content description languages XML and XML Schema standards for modeling of information structures of electronic intelligence system. In particular...
A multi-criteria method is presented for comparison of compressed video images. As criteria are used: bit rate of video stream, subjective quality evaluation of compressed video sequence and objective quality evaluation of compressed video sequence using Average Peak Signal-to-Noise Ratio (APSNR) metric.
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