On-board Image Classification based on Space-Based FPGA Processing (2018 - )
A general trend in remote sensing is the simultaneous increase in the number of spectral bands and the geometric resolution. Data rates and data volumes approach the physical limits of onboard memory and downlink data rates to earth. However, the feasibility of much more expensive and complex calculations directly on the satellite has been demonstrated already. Application areas beyond the early detection of fires include, for instance, the situation description after a hurricane or earthquake. For disaster and security research applications, short‐term visual and radar derived information are required to describe the situation for rescue workers and relevant services. Reconfigurable logic on FPGAs is a promising direction for low‐latency, real‐time, high‐volume data processing (also) in space. The goal of the thesis is to bring FPGA‐based in‐satellite data processing solutions to representative real‐time applications.
Peer-reviewed Publications (journal or conference)
- O. Kondrateva, B. Scheuermann, and S. Dietzel (2022). Scalable Flow Optimization for Small Satellite Networks using Benders Decomposition. In Proceedings of the IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), 221-230. https://doi.org/10.1109/WoWMoM54355.2022.00041
Other (presentations at conferences or preprints)