ISAR motion compensation using the burst derivative measure as a focal quality indicator

Authors


Abstract

Inverse synthetic aperture radar (ISAR) is an imaging technique that shows great promise in classifying airborne targets in real-time under all weather conditions. The success of classifying targets using ISAR is predicated upon forming highly focused radar images of these target. Efforts to develop highly focused radar imaging computer software have been challenging, mainly because the imaging depends on and is affected by the motion of the target. Computationally intensive motion compensation algorithms have been developed to remove the unwanted degrading effects of target motion. Those particular motion compensation algorithms which require the use of a space domain focal quality indicator (e.g., entropy) to determine image sharpness as processing proceeds pay a severe computational penalty due to the large number of two-dimensional fast Fourier transforms (2D-FFTs) which must be computed. This is due to the fact that the actual processing of ISAR data is done primarily in the spatial frequency domain and not in the space domain where the final ISAR image is displayed. If a focal quality indicator could be developed to measure image sharpness in the spatial frequency domain, then the computational burden introduced by the numerous 2D-FFTs could be greatly relaxed. This article describes the use of a new focal quality indicator called the burst derivative measure for determining ISAR image sharpness in the spatial frequency domain. Tests have been performed on simulated as well as actual ISAR data using both the burst derivative measure and the entropy measure. Results indicate that the burst derivative measure, when used in conjunction with the entropy measure, can greatly reduce the number of 2D-FFTS presently required in these motion compensation algorithms.©1993 John Wiley & Sons Inc

Ancillary