A CRITERION FOR REMOTE SENSING OBJECTS DISCRIMINATION IN CASE OF NON-GAUSSIAN DISTRIBUTION OF SIGNATURES

A.V. Popov

The error probability is the conventional criterion used in objects recognition while working with radar data. It is shown that in case of non-Gaussian distribution of the objects’ signatures the error probability criterion may result in “masking” some objects by some others. Therefore, a new criterion for signatures informativity estimation is suggested. The given criterion is based on Kulback’s divergence applied to the case of big amount of objects’ classes. Results of comparative analyses of the discrimination criterion and the error probability in case of non-Gaussian distribution of recognition-informative signatures are presented.

Key words: remote sensing, target recognition, error probability, Kulback’s divergence, non-Gaussian probability distribution.