ruag团队在太空中的ai
Ruag Space has teamed up with Swedish developer Stream Analyze to port AI analytics software to a space-qualified processor board for large scale deployment on constellations of small satellites.
西南arms of hundreds or thousands of small satellites are increasingly used for bringing data and internet services to Earth. To position, communicate and dispose such large amounts of satellites, AI is increasingly important. Adding AI decision making on the satellite allows results of requests to be sent over the radio links, rather than raw data.
Stream Analyze Sa.eNeNing将被移植到Ruag Lynx董事会，在瑞典哥德堡的Ruag Space的网站上设计和建造。6U SpaceVPX板使用3000MIPS四芯臂处理器，具有FPGA协处理器，比ruag目前为ESA程序提供的电脑电脑更强大250倍。
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“We have been very early with this development. We are seeing that Artificial Intelligence and Machine Learning is starting to arrive in space development programs and now we have a computer ready that perfectly matches the requirements of these customers”, said Senior Vice President Satellites at RUAG Space.
Analyzing the network behaviour, such as traffic patterns or other characteristics in a software defined satellite dynamic communication network, allows for optimizing data routes through the network and hence the performance of the complete communication system.
The sa.engine allows the network optimization to be performed in real-time onboard the satellite and enables the operator of the satellite will be able to interact directly with the satellite’s sensors and query any kind of questions. The sa.engine itself requires only a few megabytes and is hardware and software independent, so it can be integrated into the complete standard portfolio of RUAG Space’s on-board computers and into almost any other satellite computer. As sa.engine is scalable, it will be able to support any fleet of satellites and to interact with and learn from other satellites.
“这种合作使卫星在未来的人工智能下准备用于加强使用，”Linder说。将智能从地面上的智能移动到太空中卫星的边缘处理有几个优点。
“可以优化响应时间和利用数据下行链路资源，该资源通常是瓶颈。特别是随着传感器在卫星中获得更强大并产生越来越多的数据，当前需要被送到地球进行处理，“他说。
“For us at Stream Analyze to add value and new capabilities to others through edge analytics is what we are all about. An example of such a new capability will be for others to analyze the data provided by the satellite sensors on the fly, as it is produced and without latency, allowing for faster response times and decisions,” said Nils Sahlberg, Vice President and Head of Strategy and Business Development at Stream Analyze. Decision support can be downlinked to ground much quicker than with a complete data set. It is also possible to make the decisions autonomously directly on the satellite. Data can be analyzed on board the satellite to make decisions in real-time by combining different sensor inputs. Monitoring data related to the satellite itself will also enable a more optimized satellite operation, performance and lifetime.
The current development of analytics algorithms is both time consuming and has limited capability to be changed after launch. Having a programmable engine in space allows models ot be updated. “With the sa.engine at hand, one doesn’t need to finalize the algorithms and the satellite capabilities before launch. You can literally develop and deploy as you go – changing the model development process and the satellite operations fundamentally – generating a better, more adaptable, and cheaper operation,” said Jan Nilsson, CEO at Stream Analyze.
StreamAnalyze.com.;www.ruag.com/space
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