Abstract
Radar Cross Section (RCS) is the information available for nearly all types of radar. RCS is related with lots of factors, therefore the value of RCS of single batch fluctuates greatly, so that fails to extract the space target character. How to use RCS data of space target effectively has the vital significance to improve the target recognition ability of active narrow-band radar. The paper adopts target RCS time series to recognize the target. The existed track data is used to form track information base, radar track matching algorithm based on related functions is presented for the real-time matching of the current dynamic track and the previous track data for the purpose of rapidly finding their RCS time series under the same visual directional angle. A new kind of non-linear and non-stationary time frequency analysis approach Hibert-Huang Transform is then introduced in the paper to decompose the above RCS time series, and then the character index for recognition are extracted from independent intrinsic mode function obtained by the decomposition and the effective target recognition standards are set. The effectiveness and stability of the algorithm presented in the paper are verified by simulated data.
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