Recognition techniques and feature extraction for space targets based on RCS

Radar recognition of space targets has gained popularity for space surveillance and peaceful uses of outer space. RCS of Space Object is nonstationary time-series, feature extracting and identification from RCS is difficult using commonly methods. Considering the changing regular of RCS reflecting figure of space target, this paper presents a novel method of space target recognition for attitude characteristics. The method makes use of CWT and fuzzy Decision to extract feature of RCS and classificate. The result shows that 90% of recognition rate is achieved when this method is applied to practical data.