To solve the problem that traditional method can't detect the small objects whose local SNR is less than 2 in IR images,
a Danger Theory-based model to detect infrared small target is presented in this paper. First, on the analog with
immunology, the definition is given, in this paper, to such terms as dangerous signal, antigens, APC, antibodies. Besides,
matching rule between antigen and antibody is improved. Prior to training the detection model and detecting the targets,
the IR images are processed utilizing adaptive smooth filter to decrease the stochastic noise. Then at the training process,
deleting rule, generating rule, crossover rule and the mutation rule are established after a large number of experiments in
order to realize immediate convergence and obtain good antibodies. The Danger Theory-based model is built after the
training process, and this model can detect the target whose local SNR is only 1.5.