An automatic target recognition system for locating and tracking a target, said system being resident in a seeker object and utilizing synthetic discriminant function to combine passive and active target imageries to produce an accurate target location and enable precise tracking thereof, said system comprising:
- a tracker for tracking a detected target;
- a plurality of image data sensors, said sensors being capable of sensing and collecting passive infrared, active LADAR range and active LADAR intensity digitized image data of a potential target and surrounding scenery;
- a plurality of pre-processors, said pre-processors being coupled to said sensors on one-to-one correspondence, each pre-processor receiving from said corresponding sensor the digitized image data and performing convolution on the image data to produce an image filter of the target;
- a plurality of correlators, said correlators being coupled to said pre-processors on one-to-one correspondence;
- a plurality of classifiers for classifying any target detected in the scenery;
- a plurality of synthetic discriminant function (SDF) memory modules, said SDF memory modules being coupled between said correlators and said classifiers on one-to-one correspondence, each SDF memory module holding therein a multiplicity of reference synthetic discriminant function filters that are descriptive of various targets likely to be found in the scenery, each reference SDF filter describing a target from a given perspective and a pre-selected reference SDF filter from each of said SDF memory modules being input to said corresponding correlator wherein said pre-selected reference SDF filter is correlated with the filter image of the live potential target to produce a correlation surface;
- a plurality of normalizers, said normalizers being coupled simultaneously to said sensors, said correlators and said classifiers on one-to-one correspondence, each normalizer receiving said correlation surface and digitized image data from said corresponding correlator and sensor, respectively, and normalizing said correlation surface and producing therefrom detection areas;
- a plurality of statistics generators being coupled between said normalizers and said classifiers on one-to-one correspondence, each of said statistics generators receiving said detection areas from said corresponding normalizer and computing the mean and standard deviation of said areas and inputing said mean and standard deviation to said corresponding classifier, said classifier, in response, correlating inputs from said statistics generator, said SDF memory module and said normalizer to produce a correlated target image;
- and a means for fusing, said fusing means being simultaneously coupled to said plurality of classifiers and to said tracker, said fusing means further being capable of receiving and fusing said correlated target image from each of said classifiers to determinine the target location and classification with greater reliability and thereby enable said tracker to track a classified target with greater accuracy.