1. A method for automatic target recognition of a target, the method comprising: receiving a sequence of imaging radar images of the target from an imaging radar system; forming a feature vector comprising measured characteristics of the target; performing a first target recognition attempt, the performing of the first target recognition attempt comprising: using a Gaussian mixture model neural network classifier to generate a first plurality of probability likelihoods, each of the first plurality of probability likelihoods corresponding to one of a plurality of candidate target types; and using a first set of class designation rules to produce a first class designation, the first class designation corresponding to one of the plurality of candidate target types; performing a second target recognition attempt, the performing of the second target recognition attempt comprising: using a radial basis function neural network classifier to generate a second plurality of probability likelihoods, each of the second plurality of probability likelihoods corresponding to one of a plurality of candidate target types; and using a second set of class designation rules to produce a second class designation, the second class designation corresponding to one of the plurality of candidate target types; performing a third target recognition attempt, the performing of the third target recognition attempt comprising: using a vector quantization classifier to generate a third plurality of probability likelihoods, each of the third plurality of probability likelihoods corresponding to one of a plurality of candidate target types; and using a third set of class designation rules to produce a third class designation, the third class designation corresponding to one of the plurality of candidate target types; and combining the first class designation, the second class designation and the third class designation to generate an overall class designation.