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Intelligent Data Processing using In-Orbit Advanced Algorithms on Heterogeneous System Architecture
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-8096-3891
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1687-930X
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-7586-0409
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-8785-5380
2018 (English)In: IEEE Aerospace Conference 2018 IEEEAC2018, 2018, p. 1-8Conference paper, Published paper (Refereed)
Abstract [en]

In recent years, commercial exploitation of small satellites and CubeSats has rapidly increased. Time to market of processed customer data products is becoming an important differentiator between solution providers and satellite constellation operators. Timely and accurate data dissemination is the key to success in the commercial usage of small satellite constellations which is ultimately dependent on a high degree of autonomous fleet management and automated decision support. The traditional way for disseminating data is limited by on the communication capability of the satellite and the ground terminal availability. Even though cloud computing solutions on the ground offer high analytical performance, getting the data from the space infrastructure to the ground servers poses a bottleneck of data analysis and distribution. On the other hand, adopting advanced and intelligent algorithms onboard offers the ability of autonomy, tasking of operations, and fast customer generation of low latency conclusions, or even real-time communication with assets on the ground or other sensors in a multi-sensor configuration. In this paper, the advantages of intelligent onboard processing using advanced algorithms for Heterogeneous System Architecture (HSA) compliant onboard data processing systems are explored. The onboard data processing architecture is designed to handle a large amount of high-speed streaming data and provides hardware redundancy to be qualified for the space mission application domain. We conduct an experimental study to evaluate the performance analysis by using image recognition algorithms based on an open source intelligent machine library 'MIOpen' and an open standard 'OpenVX'. OpenVX is a cross-platform computer vision library.

Place, publisher, year, edition, pages
2018. p. 1-8
Series
IEEE Aerospace Conference Proceedings, ISSN 1095-323X
Keywords [en]
Heterogeneous System Architecture (HSA)Intelligent Data ProcessingMIOpenOpenVXCubeSatCPU-GPUEnergy consumption
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-38628DOI: 10.1109/AERO.2018.8396536OAI: oai:DiVA.org:mdh-38628DiVA, id: diva2:1188079
Conference
IEEE Aerospace Conference 2018 IEEEAC2018, 03 Mar 2018, Big Sky, United States
Projects
DPAC - Dependable Platforms for Autonomous systems and ControlAvailable from: 2018-03-06 Created: 2018-03-06 Last updated: 2018-07-26Bibliographically approved

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Tsog, NandinbaatarBehnam, MorisNolin, MikaelBruhn, Fredrik

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