INDICATORS OF INFORMATION FEATURES FOR RECOGNISING THE STATE OF SOURCES AND OBJECTS OF TELECOMMUNICATION NETWORKS AND SYSTEMS

Abstract

Background. The majority of modern procedures for the recognition of radio sources and objects are based on the use of binary and multivalued logic, which have low specific features. The essence of the issues is to compare a priori knowledge and a posteriori data coming from the surveillance means and to make a decision on the recognition of a radio emission object. A priori knowledge and a posteriori data are formed both before and during the recognition process on the basis of sets of information features or information signatures. At the same time, when constructing an integral indicator for determining the affiliation and status of sources and objects, it is necessary to know the weighting coefficients of information features, the determination of which is a rather difficult task. Therefore, the issue of determining the weighting coefficients that characterise information features remains an urgent task in the field of statistical radio engineering. Objective. The purpose of the paper is to select and substantiate a simple and effective method for calculating the weighting coefficients of information features for the implementation of the methodology for recognising radio sources and objects. Methods. Decision-making on the value of the weighting coefficients of information features of the recognition objects belonging to a certain class is based on the results of calculations using one of the three Fishburne formulae, which, in comparison with the known methods of expert assessments, are very simple and understandable, do not require any additional research and complex calculations. Results. The procedure is proposed and an example of using the Fishburne method (three formulae) in calculating the value of the weighting coefficients of information features for recognising sources and objects of radio monitoring is considered. Conclusions. Comparison of the method of calculating the weighting coefficients using Fishburne's formulae with other known methods of expert assessments shows that there is no need to interview experts and process their analysis results; there are no restrictive implementation conditions; it is easy to take into account additional information about the indicators, if necessary; no software implementation with a complex search algorithm is required; it is easy to make any changes as additional information indicators.