Polarimetric Feature Analysis As Applied to Automatic Target Recognition

Recent developments in target decomposition theorems indicates that the polarimetric signature of a target describes scattering mechanisms, such as depolarization, even bounce, or odd bounce, that may assist in the differentiation of a man-made targets from natural clutter, a critical first step in Automatic Target Recognition (ATR). Cloude’s alpha-entropy decomposition of the coherency matrix, similar to Mueller matrix, was developed to classify natural terrain, but contains features which should make it useful for ATR. The alpha-entropy decomposition finds the entropy, a parameter describing the uniformity or purity of the scattering mechanisms, and alpha, a parameter which measures the average strength of the odd-bounce mechanism over the others. This decomposition into its scattering mechanisms does not use the absolute magnitude of the scattering from the target. Therefore, it is expected to provide information about the target which is completely independent from all ATR algorithms which are based on a single polarization RCS alone. The alpha-entropy decomposition is applied to measurements of hard targets in clutter, and to the clutter alone. These measurements are made