Научный вестник МГТУ ГА (Oct 2018)
Information indicators of radar portraits of air objects and generalized indicators of the ability of recognition systems to extract information
Abstract
To improve the quality of recognition of air objects, it is proposed to use a priori information contained in reference portraits, which are formed adaptively to the conditions of observation. A decisive rule is formulated on the assignment of the observed target to the k-th group under the assumption that the signal and background are normal stationary random processes with zero mean values and the covariance matrices of portraits are known. The quality criterion of recognition is proposed, the result of which implementation is a decision with a probability not below the required Ptr. The price for the implementation of this criterion is the decision content change. For the implementation of the radar recognition system (HRD) with structural-parametric adaptation of the radar it is proposed to introduce into the system a device of the quality and control forecast, which conducts the assessment (forecast) of the amount of information and change the decisive rule of the HRD system in accordance with the received assessment. An indicator of the amount of information extracted by the recognition system from the radar portrait (RLP) is introduced, which is thought as a measure of reducing uncertainty in the decision-making process on the target group with the help of the RLR system. It is shown that the amount of extracted information depends not only on the parameters of the RLP, but also on the algorithm of its processing. The potential amount of information about the goal of the k-th information group contained in the RLP is determined, the concept of a sufficiently informative portrait with the recognition of the goals of all groups is introduced. The concepts of differential and integral contrast are formalized in the case of arbitrarily correlated RLP. The introduced concepts of differential and integral contrasts for the special case of uncorrelated RLP are extended to the General case of arbitrarily correlated RLP.
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