Academic literature on the topic 'SpaceCloud'

Abstract The last decade has seen a dramatic increase in small satellite missions for commercial, public, and government intelligence applications. Given the rapid commercialization of constellation-driven services in Earth Observation, situational domain awareness, communications including machine-to-machine interface, exploration etc., small satellites represent an enabling technology for a large growth market generating truly Big Data. Examples of modern sensors that can generate very large amounts of data are optical sensing, hyperspectral, Synthetic Aperture Radar (SAR), and Infrared imaging. Traditional handling and downloading of Big Data from space requires a large onboard mass storage and high bandwidth downlink with a trend towards optical links. Many missions and applications can benefit significantly from onboard cloud computing similarly to Earth-based cloud services. Hence, enabling space systems to provide near real-time data and enable low latency distribution of critical and time sensitive information to users. In addition, the downlink capability can be more effectively utilized by applying more onboard processing to reduce the data and create high value information products. This paper discusses current implementations and roadmap for leveraging high performance computing tools and methods on small satellites with radiation tolerant hardware. This includes runtime analysis with benchmarks of convolutional neural networks and matrix multiplications using industry standard tools (e.g., TensorFlow and PlaidML). In addition, a ½ CubeSat volume unit (0.5U) (10 × 10 × 5 cm3) cloud computing solution, called SpaceCloud™ iX5100 based on AMD 28 nm APU technology is presented as an example of heterogeneous computer solution. An evaluation of the AMD 14 nm Ryzen APU is presented as a candidate for future advanced onboard processing for space vehicles.

Denna studie är en empirisk fallstudie av det svenska rymd- och automationsföretaget Unibap AB om hur man bygger förtroende för rymdindustrin. Rymdindustrin är särpräglad på det sättet att rymduppdrag har höga insatser på grund av höga kostnader och det faktum att tekniken inte kan modifieras efter lanseringen. Tillförlitlighet och förtroende är därför avgörande faktorer för att göra affärer inom rymdindustrin. Dessutom kan AI-baserade satellitlösningar ge stora fördelar, men 60% av motståndet från företag att köra AI är kopplat till bristande förtroende. Begreppet förtroende har diskuterats tidigare i den industriella marknadsföringslitteraturen och skiljer mellan sociala källor och erbjudanderelaterade förtroendekällor. Det verkar dock finnas ett empiriskt såväl som ett teoretiskt gap när det gäller att bygga upp förtroende för rymdindustrin. Eftersom ämnet är outforskat används en undersökande metodik när man intervjuar 12 aktörer inom rymd- och högteknologisk industri världen över. En viktig aspekt av erbjudande-relaterat förtroende verkar vara användbarhet, därför innehåller denna studie också en användbarhetsbedömning av Unibaps rymddatalösning, SpaceCloud®, som möjliggör inbyggda AI-applikationer. De viktigaste föregångarna till förtroende för rymdindustrin visade sig vara transparens, kompetens, teknikens tillförlitlighet och exakta leveranstider. Det verkar som om socialt och erbjudanderelaterat förtroende väsentligt påverkar partnerskap mellan företag och att erbjudanderelaterat förtroende är den viktigaste typen av förtroende för att vinna kontrakt med skattefinansierade myndigheter. Styrkor och förbättringar av användbarheten hos SpaceCloud® identifieras också,

This study is an empirical case study of the Swedish space- and automation company Unibap AB about how to build trust in the space industry. The space industry is distinctive in the way that space missions are at high stakes because of the high costs and the fact that the technology can not be modified after launch. Reliability and trust are therefore crucial factors of doing business in the space industry. Also, AI-based satellite solutions can bring huge benefits but 60% of the resistance from companies to running AI is linked to lack of trust. The concept of trust has been discussed before in the industrial marketing literature and differentiates between social sources and offer-related sources of trust. However, there appears to be an empirical as well as a theoretical gap when it comes to building trust in the space industry. Because the topic is unexplored, an exploratory methodology is used when interviewing 12 actors in the space- and high-tech industry worldwide. Since one important aspect of offer-related trust seems to be usability, this study also includes a usability evaluation of Unibap's space computer solution SpaceCloud which enables on-board AI applications. Key antecedents of trust in the space industry were found to be transparency, competence, reliability of technology, and exact delivery times. It appears that social- and offer-related trust significantly influence partnerships between companies and that offer-related trust is the most important type of trust to win contracts of tax-funded agencies. Strengths and improvements of the usability of SpaceCloud are also identified, and it is concluded that SpaceCloud has the potential to offer a new way of building satellite applications in the future.

Spacecloth design and development is vital and crucial in Radar Absorbing Materials (RAM) for achieving Low Observability in an Aircraft or an Unmanned Air Vehicle(UAV). The RAM design translates into the spacecloth design. The spacecloths form the constituent layers in a broadband Jaumann absorber in which case they have to be designed for various values of surface resistivity. The design specifications of spacecloth(s) in RAMS is well understood and documented in literature. But the design of spacecloth hitherto, has been the domain of materials' scientists wherein the specified properties of the spacecloth are achieved by an iterative, trial and error process, by mixing various constituents in different proportions to get the design specified surface resistivity in the final end-product. In an effort to bridge this gap, a novel spacecloth for RAM applications is proposed in the thesis. It is proposed that a repetitive geometrical grid network of chip resistors simulates spacecloth. The sheet resistivity of the spacecloth is derived by analyzing various geometries like square, rectangle, triangle and hexagonal grids. The transmission and reflection loss for the chip resistor spacecloth is derived. The design of chip resistor spacecloths for operation at S and C bands is given followed by experimental verification using waveguide simulator experiments. Numerical study of multilayer RAM has been carried out with exponential taper variation of surface resistivities for constituent spacecloth layers and design curves are given for multilayer RAM both for normal and oblique incidence for TE and TM polarizations.