Ender, JoachimJoachimEnder2022-03-142022-03-142019https://publica.fraunhofer.de/handle/publica/41033010.23919/IRS.2019.8768149In this paper we regard an approach to fast sparsity-based GMTI processing for an air-or space-borne along track antenna array. The idea for this algorithm was inspired by a technique called fast compressive sensing based on approximated observation (CSBAO)' [8l, which replaces the multiplication by the sensing matrix or their Hermitean conjugated by fast FFTbased processors. We show that it is possible to formulate a signal model for the short CPI case and to apply fast operations (FFTs and elementwise multiplication) fitting into the concept of the Iterative Shrinkage-Thresholding Algorithm (ISTA) which converge to sparse solutions of the sensing equation. In this way, the sparse moving target sources can be discriminated from the clutter.en621conference paper