by DefenceTalk  January 26, 2022 in Technology News

DefenceTalk于2022年1月26日在《科技新闻》上发表

 

Swarms 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, Artificial Intelligence is getting increasingly important.

成百上千的小型卫星越来越多地被用于向地球提供数据和互联网服务。用于定位、通信和处理如此大量的卫星，人工智能变得越来越重要。

 

To enable a large-scale use of Artificial Intelligence in orbit, RUAG Space, Europe’s leading supplier to the space industry, and Stream Analyze, recognized as one of Sweden’s leading tech startups, are teaming up.

为了在轨道上大规模使用人工智能，欧洲领先的航天工业供应商RUAG Space公司和被公认为瑞典领先的科技初创公司之一的 Stream Analyze公司正在合作。

 

They have agreed to combine RUAG Space’s latest single board computer for satellites called “Lynx”, with Stream Analyze’ analytics platform “sa.engine”, to provide solutions for space customers’ future Artificial Intelligence applications in space.

他们已同意将RUAG Space公司最新的卫星单板计算机“Lynx”与Stream Analyze公司的分析平台“sa.engine”结合起来，为太空客户的未来太空人工智能应用提供解决方案。

 

A “smart” satellite will be able to automatically send messages to Earth of its own performance and status, such as: “Hello, it seems like I am going to use 20% more energy than usual next week. Is that ok?” instead of just raw data.

“智能”卫星将能够自动向地球发送有关其自身性能和状态的信息，例如：“你好，看来下周我将比平时多消耗20%的能量。可以吗？”而不仅仅是原始数据。

 

Optimize response time

优化响应时间

 

“This cooperation makes satellites ready for intensified use in future of Artificial Intelligence,” says Anders Linder, Senior Vice President Satellites at RUAG Space. Moving the intelligence from servers on ground into edge processing on the satellite in space has several advantages, Anders Linder explains: “It is possible to optimize response times and utilization of the data downlink resource which is often a bottleneck. Especially as sensors are getting more powerful and producing more and more data in the satellites which would currently need to be sent to Earth for processing.”

RUAG Space公司卫星高级副总裁安德斯·林德（Anders Linder）表示：“这种合作使卫星为未来人工智能的强化使用做好了准备。”将智能从地面服务器转移到空间卫星上的边缘处理有几个优势，安德斯·林德（Anders Linder）解释说：“可以优化响应时间和数据下行链路资源的利用率，这通常是一个瓶颈。特别是随着传感器变得越来越强大，并且在卫星中产生越来越多的数据，这些数据目前需要发送到地球进行处理。”

 

Fast and autonomous decision making

快速自主决策

 

“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,” adds Nils Sahlberg, Vice President and Head of Strategy and Business Development at Stream Analyze.

Stream Analyze公司副总裁兼战略和业务发展负责人Nils Sahlberg补充道：“对我们来说，Stream Analyze公司通过边缘分析为其他人增加价值和新功能就是我们的全部。这种新功能的一个例子是，其他人可以分析卫星传感器动态提供的数据，因为这些数据是生成的，没有延迟，允许更快的响应时间和决策。”

 

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.

决策支持可以比使用完整的数据集更快地下传到地面。也可以直接在卫星上自主做出决定。可以在卫星上分析数据，通过组合不同的传感器输入实时做出决策。与卫星本身相关的监测数据也将使卫星运行、性能和寿命更加优化。

 

Better performance of satellite swarms

卫星群的更好性能

 

With large new constellations of satellites (satellite swarms) forming a large mesh of interconnected nodes in a constantly moving dynamic global network, it is a huge challenge to orchestrate the communication traffic in an optimal way.

在不断移动的动态全球网络中，新的大型卫星星座（卫星群）形成一个大的互联节点网格，以最优的方式协调通信流量是一个巨大的挑战。

 

Analyzing the network behavior, 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. Stream Analyze’ sa.engine allows this network optimization to be performed in real-time onboard the satellite.

分析网络行为，例如软件定义的卫星动态通信网络中的流量模式或其他特性，可以优化通过网络的数据路由，从而优化整个通信系统的性能。 Stream Analyze公司的“sa.engine”允许在卫星上实时执行这种网络优化。

 

Direct interaction with the satellite’s sensors

与卫星传感器直接交互

 

Through Stream Analyze’ analytics platform sa.engine 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.

通过Stream Analyze公司的分析平台“sa.engine”，卫星运营商将能够直接与卫星的传感器交互并查询任何类型的问题。 “sa.engine”本身只需要几兆字节，并且独立于硬件和软件，因此它可以集成到RUAG Space公司星载计算机的完整标准产品组合中，也可以集成到几乎任何其他卫星计算机中。由于“sa.engine”是可扩展的，它将能够支持任何卫星群，并与其他卫星进行交互和学习。

 

More adaptable and cheaper satellite operations

更具适应性和成本更低的卫星运营

 

Today, the development of analytics algorithms is both time consuming and has limited capability to be changed after launch. “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,” says Jan Nilsson, CEO at Stream Analyze.

如今，分析算法的开发既费时而且在发布后更改的能力有限。Stream Analyze公司首席执行官简·尼尔森（Jan Nilsson）表示“有了sa.engine在手边，人们不​​需要在发射前完成算法和卫星功能。您可以随心所欲地进行开发和部署——从根本上改变模型开发过程和卫星运营——产生更好、更具适应性和更便宜的运营，”。