Satellite imaging has been the focus of intense works in remote sensing for the last years. The ability of satellite optical systems to produce high-resolution images has indeed been of a great interest in applications such as change detection or image classification. The design of a satellite acquisition chain is however quite challenging as it involves expensive processes such as sampling and coding. In this work, we investigate the performances of a low-resource satellite imaging chain based on the Compressed Sensing (CS) acquisition technique. We propose a reconstruction algorithm which takes into account the degradations of the satellite imaging chain and we present results on a real satellite data.