All space objects rotate


If the awning of a satellite is bent, it becomes "dark" - it lacks the energy to send signals to earth. Questions like: Are the satellites intact? Was there a collision? Missing parts? Answering such and similar questions about satellites is one of the tasks of the TIRA space observation radar. Because radar has a decisive advantage over optical systems: You can use the systems day and night and in any weather. While optical systems provide an image immediately, with radar you get raw data that you first have to process. The following applies: the better the signal processing, the more knowledge the image provides. The quality of the radar image can therefore be increased via the processing.

Better image quality

Improving the processing of TIRA radar data and thus gaining more precise information about satellites or other objects orbiting the earth is a core task of Fraunhofer FHR. The ISAR principle, short for Inverse synthetic aperture radar, used: The radar structure is fixed while the object rotates around the radar. The antenna rotates in order to track the object on its orbit. The radar continuously sends pulses and records the received reflected signal for each pulse - a distance profile of the object can be obtained from this. From the change in the distance profiles over time, a 2D image of the object can be calculated by means of spectral analysis. At ISAR, data processing is particularly demanding because the forward and rotational movements of the satellite are generally not exactly known. How fast does a specified point rotate on the satellite? And how does the satellite itself move? If you want to get a clear image, both questions must be answered very precisely. The state of stabilization can be assessed from the satellite's own motion. For example, does he stumble?

A new method was developed at Fraunhofer FHR - based on Compressive sensing (CS) - developed to process the images even more sharply. The method creates a better correction of the translational movement and combines this with a spectral extrapolation in order to increase the quality of the processed radar images.