Space object identification based on narrowband radar cross section

A space object identification method based on narrowband radar cross section (RCS) is proposed in this paper. With RCS sequences, statistical features are extracted, the two-dimensional sizes of the object are estimated by adopting an improved size estimation model (SEM) and the attitude stability of the object is determined by periodicity analysis. Feature templates are constructed in matrix form with those three kinds of features of the training sample set and especially when constructing the template for a large number of statistical features, dynamic fuzzy clustering technology is used. The k-nearest neighbor fuzzy classifier is adopted to accomplish the identification. At the end, experiments with the measured data are conducted to confirm the effectiveness of the method.