Space Force's 18th Space Control Squadron was "re-designated" on April 13 as the "18th Space Defense Squadron," but will remain SPACECOM's key provider of space domain awareness.

太空部队的第18太空控制中队于4月13日被“重新指定”为“第18太空防御中队”，但仍将是太空司令部（SPACECOM）太空领域感知的主要提供者。

 

The Space Fence location in the Marshall Islands. (Lockheed Martin)

“太空篱笆”(Space Fence)位于马绍尔群岛。（洛克希德·马丁）

 

WASHINGTON: Improving integration and use of sensor data already available to create a full picture of what is happening in the heavens is one of the biggest challenges faced today by the Space Force’s newly named 18th Space Defense Squadron, according to its commander, Lt. Col. Matt Lintker.

华盛顿：据太空部队指挥官马特·林特克中校称，改进现有传感器数据的集成和使用，以全面了解太空中正在发生的事情，是太空部队新命名的第18太空防御中队今天面临的最大挑战之一。

 

“Right now, if I had to prioritize, I prioritize to be doing better with the data I have,” he told C4ISRNet’s annual conference today — noting that this includes data from commercial partners monitoring space traffic as well as data from the radar and telescopes part of the military’s Space Surveillance Network (SSN).

他在今天的C4ISRNet年会上说：“现在，如果我必须优先考虑的话，我会优先考虑如何更好地利用我拥有的数据。”他指出，这包括来自商业合作伙伴监测空间交通的数据，以及来自军方空间监视网络（SSN）的雷达和望远镜部分的数据。

 

Lintker’s squadron, previously named the 18th Space Control Squadron and one of the units under Space Force Delta 2, was “re-designated” with the “defense” modification on April 13, but will remain “U.S. Space Command’s premier provider of continuous, comprehensive and combat-relevant space domain awareness,” a terse Space Force press release stated.

他在今天的C4ISRNet年会上说：“现在，如果我必须优先考虑的话，我会优先考虑如何更好地利用我拥有的数据。”他指出，这包括来自商业合作伙伴监测空间交通的数据，以及来自军方空间监视网络（SSN）的雷达和天文望远镜部分的数据。

 

Space domain awareness, or SDA, is defined by the Space Force as the ability to detect, track and, most crucially, understand what is happening in space, especially with regards to potential threats from adversary satellites.

太空领域感知（SDA）被太空部队定义为探测、跟踪和最重要的是了解太空中正在发生的事情的能力，尤其是在来自敌方卫星的潜在威胁方面。

 

The Space Force and SPACECOM currently are hashing out how best to integrate the burgeoning amount of highly sophisticated — and in some cases more accurate than its own — space tracking data and analysis on offer from commercial firms both in the United States and abroad.

太空部队和太空司令部目前正在讨论如何最好地整合美国和国外商业公司提供的高度复杂的——在某些情况下比自己的更准确——空间跟踪数据和分析。

 

This effort has been complicated by the fact that the computer systems and software for integrating, managing and sharing SDA data with relevant users were built in and for a different era, and the Pentagon has been struggling for decades to update those capabilities.

由于用于与相关用户集成、管理和共享SDA数据的计算机系统和软件是为不同的时代而构建的，五角大楼几十年来一直在努力更新这些能力，这项工作变得更加复杂。

 

“We are taking all of our current sensors and integrating them and network them in new and imaginative ways. Some of those sensors were designed back in the ’60s in the ’70s, and were never designed for the [communications] pipes that we have today, and for the processing capability we have today,” Lt. Gen. Michael Guetlein, head of Space Force’s Space Systems Command, told the C4ISRNet conference in a later interview.

“我们正在利用我们目前所有的传感器，并以新的、富有想象力的方式将其集成和联网。其中一些传感器早在60年代和70年代就设计好了，从来没有为我们今天拥有的（通信）管道和我们今天拥有的处理能力而设计过，”航天部队空间系统司令部负责人迈克尔·盖特林中将说，在随后的采访中告诉C4ISRNet会议。

 

From   BREAKING DEFENSE

从打破防御

 

Lintker said that while he’s “never going to turn down new sensors,” data integration continues to be a challenge — despite progress being made on developing data standards for “translating” among disparate data sources. For example, data translation is an issue for the Space Force’s newest sensor, the ground-based Space Fence radar, that came fully online in March 2020.

林特克说，尽管他“永远不会拒绝新的传感器”，但数据集成仍然是一个挑战——尽管在开发用于在不同数据源之间“转换”的数据标准方面取得了进展。例如，数据转换是太空部队最新传感器地面“太空篱笆”雷达的一个问题，该雷达于2020年3月全面上线。

 

“Translating across the board,” he said, is his second biggest concern today.

“全面转化，”他说，是他今天的第二大担忧。

 

“But again, just the integration of the data is really step one,” he added. “Step two is then being able to make sense of what that data is. So as we get more and more data, it does become increasingly challenging to kind of make sense of that from an operator’s perspective.”

“但同样，数据的整合只是第一步，”他补充道。 “第二步是能够理解这些数据是什么。因此，随着我们获得越来越多的数据，从操作者的角度理解这一点确实变得越来越具有挑战性。”

 

This is where machine learning (ML) and artificial intelligence (AI) come in, Lintker said. Bringing on board those capabilities will “help us to then make sense of the larger amounts of data.”

这就是机器学习 (ML) 和人工智能 (AI) 的用武之地，林特克说。引入这些功能将“帮助我们理解大量数据”。

 

AI/ML tools further will help operators change focus away from simply tracking objects in space — what is known in the civil world as space situational awareness — toward figuring out where the real threats are. Doing so is made ever more difficult by the boom in space activities over the past decade, meaning that space has become more congested and, at the same time, more contested as potential adversaries build up their military space capabilities.

AI/ML工具将进一步帮助操作者将重点从简单地跟踪太空中的物体（在民间世界称为太空态势感知）转向找出真正的威胁在哪里。过去十年太空活动的蓬勃发展使这样做变得更加困难，这意味着太空变得更加拥挤，与此同时，随着潜在对手建立其军事太空能力，太空竞争也更加激烈。

 

“One of the biggest challenges I have is making sure the operators look past the numbers themselves. As you look across the board, the operational fleet of space systems from China and Russia has grown by 70% in the last few years,” Lintker said. “So how do I get the operators here to then focus in, again, balancing that congested versus contested nature?

林特克说：“我面临的最大挑战之一是确保运营商自己看不到这些数字。从整体上看，中国和俄罗斯的空间系统操作团队在过去几年中增长了70%。”。“那么，我该如何让这里的操作者再次专注于平衡这种拥挤与有争议的性质呢？

 

‘And that is where AI and ML are gonna help us,” he explained, “to focus on where we need to put our attention.”

“这就是AI和ML将帮助我们的地方，”他解释道，“把注意力集中在我们需要关注的地方。”

 

Lintker added that another long-standing challenge is being able to share data across classification levels, in particular for sharing data with allies — something NATO military space leaders have been trying to enhance.

林特克补充说，另一个长期存在的挑战是能够跨分类级别共享数据，特别是与盟友共享数据——北约军事太空领导人一直在努力加强这一点。

 

“Like many things, especially when you look at the bureaucracy and the policy and how things have gone in the past, it’s the classification. So, working through old paradigms and old norms when it comes to: Is this classified at the right level’?” he said.

“就像很多事情一样，特别是当你审视官僚体制和政策，以及过去的情况时，这就是分类。所以，在涉及到以下问题时，通过旧的范式和旧的规范来工作：这是在正确的级别上分类的吗？”他说。