Currently, the task of recognizing air objects is of increasing interest, especially for air traffic control and air defense system developers, since the realization of recognition modes ensures an increase in the adequacy of radar information received from radars at control points of various degrees of hierarchy in an actual situation, decisions made, and also to automate the process of their adoption and create the conditions for the introduction of elements of an action sstvennogo intelligence in the operation of the relevant systems.

The article is devoted to an estimation of quality of recognition of classes and types of air objects in survey radars. Recognition is carried out by statistical methods using the features extracted from two-dimensional radar images, using the known method of generalized voting. Recognition features are polygonal area formed by a two-dimensional image; the number of resolved scattering centers on two-dimensional images; distance between the most distant scattering centers; the effective scattering surface, as the sum of the effective scattering surface of all scattering centers.

The results of the evaluation of the quality of class recognition (large, medium and small-sized goal) and types in classes of large and medium-sized objectives are presented.

The obtained results can be used for developing and assessing the quality of class recognition systems and types of air assets based on signal attributes in existing and prospective radars, as well as by the person making the decision when choosing a radar recognition system and comparing alternative options.