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Signal Based Motion Compensation (SBMC) is an enabling technology for low cost SAR applications as well as an enhancement for more robust SAR applications. SBMC involves down range and cross range compensation for platform motion with motion compensation (mocomp) signals derived entirely from radar signal based measurements. It is an alternative to Motion Measurement Sensor (MMS) based mocomp and a next step growth from autofocus. A very robust SBMC algorithm has been developed and demonstrated on simulated data and real radar data provided by actual radars. The algorithm is tuned to a particular radar and adapted to any level of aircraft navigation system. This SBMC approach will enable a low cost SAR capability to be provided for budget minded applications. Alternately, it can also be applied to high performance SAR systems for improved capability. It will extend current MMS mocomp and autofocus performance and provide a backup capability to compensate for Nav system performance degradation, such as from component failure or GPS jamming.

This paper is concerned with imaging and moving target detection using a Synthetic Aperture Radar (SAR) platform that is known as Gotcha. The SAR platform can interrogate a scene using an imperfect circular trajectory; we refer to this as nonlinear SAR data collection. This collection can make monostatic and quasi-monostatic measurements in the along-track domain. We present subaperture-based wavefront reconstruction algorithms for motion compensation and imaging from this nonlinear SAR database. We also discuss adaptive filtering algorithms to construct MTI imagery from the two receiver channels of the system. Results will be provided.