Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/73843
Título: Reconfigurable video processor for space
Autores/as: Armesto Caride, L.
Rodríguez, A
Pérez Garcia, A.
Sáez, S.
Valls, J.
Barrios Alfaro, Yubal 
Sánchez Clemente, Antonio José 
González Arjona, D.
Herrera, J. P.
Veljković, F.
Clasificación UNESCO: 3324 Tecnología del espacio
Palabras clave: Enable S3
Fault Injection
Fault Rate
Fault Tolerance
FPGA, et al.
Fecha de publicación: 2019
Editor/a: Springer 
Resumen: This work presents a Reconfigurable Video Processor demonstrator that takes the benefit of ENABLE-S3 developments for the integration and validation of image processing applications demanded by the emerging space industry. Applications such as On-board hyperspectral image compression for Earth observations and Autonomous Vision-based Navigation for Guidance, Navigation and Control of the spacecraft form part of the demonstrator. Modern space industry requires more flexibility, larger platforms and lower design costs. Hence, an SRAM-based Field-programmable gate array (FPGA) is selected as the platform for the processor. Although compliant with the aforementioned specifications, this technology is highly susceptible to radiation effects. In this work the space environment has been simulated by a virtual radiation sensor thus decreasing the design time, costs and very expensive hours “in the beam” available in a small number of Radiation Facilities. The virtual sensor and reconfiguration techniques help to validate the proposed applications and to exhaustively test the SRAM-based FPGA prior to radiation testing. With this approach the reduction of design and testing costs has been achieved and the confidence in the technology and the algorithms has been gained. In addition, the a2K Tool Suite has been used to assist in the V&V process of the demonstrator decreasing the number of tests, testing time and cost of personnel, all of them being the objectives of ENABLE S3 project.
URI: http://hdl.handle.net/10553/73843
ISBN: 978-3-030-14627-6
DOI: 10.1007/978-3-030-14628-3_18
Fuente: Validation and Verification of Automated Systems: Results of the ENABLE-S3 Project / Leitner A., Watzenig D., Ibanez-Guzman J. (eds), p. 231-249, (Enero 2019)
Colección:Capítulo de libro
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