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In this article, a new reduced-dimensional adaptive processing algorithm based on joint pixels sum-difference data for clutter rejection is proposed. The sum-difference data are obtained by orthogonal projection of the joint pixels data of different synthetic aperture radar (SAR) images generated by a multi-satellite radar system. In the sense of statistical expectation, the sum-differ- ence data contain the common and different information of the SAR images. Therefore, the objective of clutter cancellation can be achieved by adaptive processing. Moreover, based on the residual image after clutter rejection, statistical analysis of constant false-alarm rate (CFAR) detection of moving targets is also presented. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm even with heterogeneous clutter and image co-registration error.

This paper presents a preliminary knowledge based approach to space-time adaptive processing (STAP) for ground moving target indication from an airborne platform. The KB-processor accounts for practical aspects of adaptive processing, including detection and processing of non-homogeneous data, appropriate selection of training data, and accounting for array effects such as mutual coupling and channel mismatch. In combining these hitherto separate STAP issues into a unified approach, this paper furthers the move of STAP from theory to practice. The KB-approach is tested using measured data from the multi-channel airborne radar measurements (MCARM) program.

The Shuttle Radar Topography Mission (SRTM) was flown in February 2000 to map the world's land mass with high accuracy, using two Synthetic Aperture Radar (SAR) systems. Spaceborne single-pass across-track SAR interferometry was used for the first time. The mechanical configuration of the interferometer formed both an across-track and a small along-track baseline between the antennas in the cargo bay of the space shuttle and at the tip of the deployable boom. SAR Along-Track Interferometry (ATI) is sensitive to ground motion and was recently proposed for traffic monitoring applications. Due to the along-track baseline, SRTM data currently offer the unique opportunity to study the effects of moving objects on high-resolution spaceborne SAR ATI data. This paper presents an analysis of moving vehicles in SRTM/X-SAR ATI data as well as application examples, and describes specific SAR processing techniques for vehicle detection and velocity measurement.