RCS feature extraction from simple targets using time-frequency analysis

Radar target identification requires the processing of a large amount of data Radar cross section alone is a function of time/frequency, aspect angle, and polarization. Storing all this data as well as processing it for identification is an extremely difficult task. The goal of this research is to analyze the RCS of simple targets in the time/frequency domain to identify which time/frequency algorithms best highlight distinguishing target characteristics. We have taken extensive RCS measurements on simple objects, such as spheres, cubes, pyramids and corner reflectors, and processed the data using Fourier and wavelet transforms. In most instances, the data can be significantly compressed.