Inverse Synthetic Aperture Radar (ISAR) For Terrestrial Targets

ABSTRACT: Inverse synthetic aperture radar (ISAR) moving-target imaging algorithm development is a long-standing challenge that, to date, has proven most effective when applied to imaging of ships, aircraft and satellites where the kinematic motion of the target is well constrained over the required coherent processing interval. In the case of ground targets, the separation amongst features can be considerably less requiring proportionally higher resolution and fidelity. In particular, uncertain angular velocity modulus estimates lead to variations in the scale assigned to the cross range ISAR image axis. Often the target-class separation in this dimension can be less than the uncertainty leading to poor classification performance. STR"s approach to improving moving ground-vehicle ISAR imaging is to embed our ISAR processor in a closed-loop measurement, feature-aided tracking and sensor-resource management system. This architecture allows for relevant and accurate auxiliary data to be made available to the ISAR image formation process and allows for optimal planning of ISAR feature collections. Measurements obtained over the range of target states, e.g. SAR when stationary, HRR when moving linearly, track states, etc. can be used by the ISAR image formation and feature extraction/discrimination processes to refine uncertainties resulting from isolated ISAR data analysis. BENEFIT: If the proposed development approach is successful we will have developed a suite of algorithms that accepts as inputs radar range-pulse sequences and produces as outputs ISAR images of targets and extracted ISAR data-based features. These algorithms can be utilized by radar systems such as JSTARS and Gotcha to enable new moving target feature-aided tracking and classification capabilities.