ISAR image formation and feature extraction using adaptive joint time-frequency processing

We address two ISAR imaging problems by utilizing adaptive joint time-frequency (JTF) processing ideas, In the first application the adaptive JTF processing is applied to extract non-point scattering resonant features from an ISAR image, By applying JTF processing to the down range dimension, we show that it is possible to extract the strongly frequency-dependent components from the data that correspond to resonant features on the target, Our results show that non-point scattering mechanisms can be completely removed from the original ISAR image. leading to a cleaned image containing only physically meaningful point scatterers. The non-point scattering mechanisms, when displayed in the frequency-aspect plane, can be used to identify target resonances and cut-off phenomena, In the second application, we utilize adaptive JTF processing to address the motion compensation issue. By applying JTF processing to the cross range dimension, we track how the Doppler frequency varies as a function of imaging time. We then derive the target motion and remove this effect from the data. In both applications, the adaptive JTF engine preserves the phase information in the original data. Consequently, the two processing blocks can be cascaded to achieve both motion compensation and feature extraction.