Information theoretic measure for ISAR imagery focusing

A high-resolution spectral analysis algorithm with application to ISAR (inverse synthetic aperture radar) imaging is proposed in this paper. The ISAR imaging is induced by target motion, which in turn causes time varying spectrum of reflected signals from the target. During the imaging time, the scatterers must remain in their range cells. Optimal Integration Angle need to be estimated to prevent defocusing in cross-range. In order to measure the evolution of spectra, we propose a new information divergence measure based on Renyi entropy. A detailed discussion reveals many of the desirable properties of this new Jensen-Renyi divergence measure. When applied in inspecting time-frequency representation of reflected signals, optimal integration angle can be obtained to produce a well focused and high resolution ISAR image.