Daniel Báscones;Francisco García-Herrero;Óscar Ruano;Carlos González;Daniel Mozos;Juan Antonio Maestro
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引用次数: 0
Abstract
Hyperspectral imaging is an excellent tool to remotely analyze the Earth from in-orbit devices. Satellites capture these images containing vast information about the ground pixels. To optimize storage and transmission speeds, compression is often performed onboard the satellite. To that end, algorithms such as the CCSDS 123.0-B-2 are implemented on FPGAs, enabling this process in an efficient and fast manner. Single-Event Upsets (SEU) are commonplace in this scenario, e.g. bit flips in the FPGA’s configuration memory which can catastrophically alter the algorithm’s output. In this paper, we propose a fault tolerance technique for this specific case. The compression core is checked periodically by running a golden model designed to excite the full internal datapath based on a synthetic image. A failure in this check will trigger a reconfiguration of the compression core. Results show better detection rates than Dual Modular Redundancy (DMR) at a fraction of the resource cost, proving this technique as a viable alternative. Furthermore, other algorithms with similar processing flows might benefit as well from this technique.
期刊介绍:
The IEEE Transactions on Computers is a monthly publication with a wide distribution to researchers, developers, technical managers, and educators in the computer field. It publishes papers on research in areas of current interest to the readers. These areas include, but are not limited to, the following: a) computer organizations and architectures; b) operating systems, software systems, and communication protocols; c) real-time systems and embedded systems; d) digital devices, computer components, and interconnection networks; e) specification, design, prototyping, and testing methods and tools; f) performance, fault tolerance, reliability, security, and testability; g) case studies and experimental and theoretical evaluations; and h) new and important applications and trends.