GMV is developing an experimental payload focused on the assessment of in-orbit satellite servicing for tracking debris in MEO/LEO making use of ad-hoc solutions for high-performance computer-vision algorithms, FPGA implementation and new dedicated equipment development for a stand-alone smart-sensor HW combining optics, imaging sensor and computing electronics in a reduced shaped unique enclosure. The SBSS-GNSS (Space-Based Surveillance System) would be hosted as experimental payload on board Galileo satellites of Galileo constellation for offering debris surveillance with main focus in Galileo orbits (MEO) as secondary service for monitoring and detection the proliferations of debris in the most populated space area. Observation of objects in MEO and LEO can be covered by ground-based radar or optical telescopes, the case for a space-based surveillance system is considered as particularly interesting for observation of objects from a different perspective complementing the observations obtained from ground while presenting certain advantages such as higher performances due to absence of atmosphere and good timeliness. Space-based techniques significantly improves the results achievable with ground-based techniques by reducing the observable debris size and by enabling observations for different orbits.
The proposed experimental payload consists on a miniaturized independent system which is able to detect debris, through dedicated image processing algorithms accelerated on-board by a HW implementation. The computer-vision solution process images performing various filters looking for debris candidates in the FOV of the camera. The algorithms includes the detection and tracking of potential debris objects, being the detected candidate features in the images. The candidates screening and selection includes different considerations such as the detection of light curves, the different relative motion of stars vs potential debris and the geometrical expected motion and detection over consecutive frames. A preliminary assessment has been already performed evaluating four different cases of debris orbits (taken from results of the PROOF SW tool analysis) keeping fixed the size of the debris. The orbital characteristics are quite different leading to different velocity of the debris on the camera sensor. Distinct values of this quantity, here called “Dwell Rate”, are analyzed from 1.4 pxl/s up to 7.5 pxl/s.
The dedicated avionics include two rad-hard FPGA, European NG-MEDIUM and high-performance Virtex5QV. The smart sensor camera is embedded within the miniaturized electronics and directly connected to NG-MEDIUM, in charge of both the image acquisition and also external/internal interfacing. While embedding a camera, the system also allows the connection of eventual second external camera that can supply images from different satellite locations and pointing, covering bigger or complementary areas. Through direct connection with embedded imaging sensor it is managed the configuration, commanding and acquisition of images using FPGA logic and applying pre-processing in streaming pipelinea. Avionics incorporates a second FPGA dedicated to the implementation and HW-acceleration of the computer-vision algorithms, the most computationally demanded part. The FPGA high performance solution allow more consecutive frames being processed thanks to the utilization of FPGA and the pipeline processing in streaming thanks in part to the integration of the logic for the camera images acquisition in the presented embedded HW solution.

State-of-the-art optical space instruments are capable of producing data rates that considerably exceed the available down-link capacities. The potential data rates are increasing as the sensor technologies progress. These trends require a signifi-cant data reduction on-board, most appropriately at the source of the data, the in-strument. Furthermore, the high availability needed to fulfill the science goals re-quire a high degree of autonomy. In this presentation we will discuss these trends using the example of the architecture of the data processing system of the PLATO payload. PLATO (PLAnetary Transits and Oscillations of stars) is the third medium (M3) mission in ESA’s Cosmic Vision programme. The goal of the PLATO mission is to detect terrestrial exoplanets in the habitable zone of so-lar-type stars and characterize their bulk properties. The PLATO instrument is comprised of 24 identical refracting telescopes each equipped with 4 CCDs, plus 2 additional telescopes which aid the space-craft fine-pointing. Altogether the PLATO payload is comprised of over 27 CPU cores, over 30 FPGAs and 6 Space-Wire Routers. In order to master this complex system of interacting soft-ware and hardware we use standardized protocols, pre-qualified operating sys-tems, Model-Based Systems-Engineering tools and techniques, code-generation, and on-board control procedures. We will give an overview of the aforemen-tioned tools and techniques, discuss their benefits and pitfalls and share the les-sons learnt so far in the development of the PLATO instrument. Finally, we will propose architectural considerations that could potentially improve the perfor-mance of similar instrument designs in the future.