STAP-ISAR

The aim of this chapter is to develop a processing chain that exploits multichannel information provided by a multichannel synthetic aperture radar (SAR) system to obtain high-resolution images of noncooperative moving target within SAR images. There are two steps of the proposed processing chain. Clutter suppression and platform motion compensation are first performed through the space-time adaptive processing (STAP) processing by exploiting the multichannel information in order to improve target detection capability within SAR image. At this point, inverse synthetic aperture radar (ISAR) autofocusing is required in order to compensate the residual target own motion and to reduce the defocusing effect due to that unknown motion component. The study of moving target detector (MTD)/Moving Target Indicator (MTI) techniques and the development of clutter mitigation algorithms are the aims of this chapter together with the study of the applicability of ISAR processing to refocus moving target detected within SAR images. The integration of the proposed algorithms with ISAR techniques leads to the final processing chain. All the developed techniques are tested on simulated and real dataset. Chapter Contents: • 3.1 Mathematical background • 3.1.1 Multichannel ISAR signal model • 3.1.2 High-resolution imaging of noncooperative moving targets • 3.1.2.1 ISAR processing • 3.1.3 Clutter model • 3.2 Space-time adaptive processing for clutter suppression • 3.2.1 Joint SDAP ISAR • 3.2.1.1 Optimum processing • 3.2.1.2 Suboptimum processing • 3.2.2 Joint E-SDAP ISAR • 3.2.2.1 Optimum processing • 3.2.2.2 Suboptimum processing • 3.3 Results • 3.3.1 SDAP-ISAR results • 3.3.1.1 Dataset description • 3.3.1.2 Multichannel range-Doppler image formation • 3.3.1.3 Clutter suppression and imaging • 3.3.2 E-SDAP ISAR results • 3.3.2.1 Dataset description • 3.3.2.2 Multichannel range-Doppler image formation • 3.3.2.3 Clutter suppression and imaging • 3.4 Conclusion • References.