TARGET CLASSIFICATION WITH LOW-RESOLUTION SURVEILLANCE RADARS BASED ON MULTIFRACTAL FEATURES
The multifractal characteristics of return signals from aircraft targets in conventional radars ofier a flne description of dynamic characteristics which induce the targets' echo structure; therefore they can provide a new way for aircraft target classiflcation and recognition with low-resolution surveillance radars. On basis of introducing the mathematical model of return signals from aircraft targets in conventional radars, the paper analyzes the multifractal characteristics of the return signals as well as the extraction method of their multifractal features by means of the multifractal analysis of measures, and puts forward a multifractal-feature-based classiflcation method for three types of aircraft targets (including jet aircrafts, propeller aircrafts and helicopters) from the viewpoint of pattern classiflcation. The analysis shows that the conventional radar return signals from the three types of aircraft targets have signiflcantly difierent multifractal characteristics, and the deflned characteristic parameters can be used as efiective features for aircraft target classiflcation and recognition. The results of classiflcation experiments validate the proposed method.