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Margaret Hamilton, who coined the term "software engineer". Image from Wikipedia.

How to navigate in deep space

This week is all about the Apollo 11 50th anniversary (at least to those of us who are interested in space). There is one thing about going to the moon that never ceases to amaze me: How did they even find their way to the Moon? In other words, how does deep space navigation work?

For Apollo, Draper Laboratory was instrumental in this effort. And Margaret Hamilton, whom you can see in the photo above, led Draper’s Software Engineering Division, which developed Apollo’s on-board flight software. She also coined the term “software engineering”, by the way.

Now, that was 50 years ago. What’s new since then?

As an “interested layperson”, I simply searched Mergeflow for “navigation” or “trajectory control” in combination with “deep space” or “space probes”. Not exactly sophisticated, I know, and anybody with any serious background in this area could have done much more. But I still got some results I found interesting.

Market information

For example, I did not really expect Mergeflow to dig up market information for deep space navigation. But I did get the CubeSat market.

Currently, the CubeSat market is probably one of the most important market-pull forces for deep space navigation.

CubeSats are very small satellites, only ca. 10 cm sized cubes. And in this CubeSat market, I saw some companies I had heard of before, such as the Sierra Nevada Corporation. But then also companies that were new to me, e.g. GomSpace in Denmark, or NanoAvionics from Lithuania. Or LeoLabs from San Francisco, which does space debris mapping. Not sure, but I think that space debris mapping is a new use case since Apollo.

The Interplanetary Internet

The what? Yes.

When I looked at R&D, I used Mergeflow’s patent class algorithm to help me (I’m trying not to say “navigate” here) the publications. This algorithm assigns patent classes to non-patents, such as R&D publications. Besides deep space navigation, we have explored R&D on LiDAR tech with this algorithm, for example.

For “deep space navigation”, I got this tag cloud from Mergeflow:

Mergeflow discovered R&D aimed at building an interplanetary internet. The idea is that this interplanetary internet will facilitate navigation in deep space.
Mergeflow patent class tag cloud for RD publications on deep space navigation

Wireless networks. Sounded interesting, I zoomed in on this, and there it was, a paper, Future Architecture of the Interplanetary Internet. The idea is to build and deploy a network to interconnect Earth with other planets in our solar system, facilitating future space missions to such places.

Chinese patents

Many of the deep space navigation patents I found were Chinese. So far, so good, not very surprising, given the current patent landscape for many other technologies as well. What I found more interesting is what some of these patents are about.

Quite a number of the Chinese deep space navigation patents listed Shengying Zhu from the Bejing Institute of Technology as inventor. Shengying Zhu’s patents are not about the Moon, though. A lot of them are about navigating toward Mars, and mostly about the final approach or atmosphere entry part of the trip (here or here, for example).

And then, Shengying Zhu has a number of other patents that I found particularly interesting. They are about landing or navigating on “small celestial bodies” (e.g. here or here). Patents for how to navigate to or land on asteroids!

So, what’s new since Apollo?

To me, two things stood out:

(1) Space is not just for big (government) organizations anymore, or even just for SpaceX et al. See the examples of companies in Denmark or Lithuania above.

(2) The scope seems to be the solar system now. Interplanetary Internet. It would be great if this meant that I’d be able to book time on a Jupiter probe and snap some photos!

This article was written by:

Florian Wolf

Florian Wolf

Florian is founder and CEO at Mergeflow, where he is responsible for company strategy and analytics development at Mergeflow. Previously, Florian developed analytics software for risk management at institutional investors. He also worked as a Research Associate in Computer Science and Genetics at the University of Cambridge. Florian has a PhD in Cognitive Sciences from MIT.

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