https://albedo.com/post/clarity-1-what-worked-and-where-we-g...
The main performance goal for us was NIIRS 7, and we decomposed GSD/MTF/SNR contributors optimized for affordability when we architected the system
A little more detail that we didn't get into in the post. The 3-CMG control mode we first uploaded was v1. We had plans to improve the agility with later versions. In v1, we didn't have quite enough rate to match earth's, even with max TDI. We called it Banana Scanning. Kind of like slipping over the earth.
Net - the CMG imagery we captured had a few pixels of along-track smear in it. Which would have been removed in post-processing if we had made it through focus cal.
I assume you were setup with a linescan then instead of butcher block FPA?
We got here after stacking quite a few capabilities we'd developed on top of one another and realizing we were beginning to see behavior we should be able to wrap up into a viable control strategy.
Traditional approaches to torque rod control rely on convergence over long time horizons spanning many orbits, but this artificially restricts the control objectives that can be accomplished. Our momentum control method reduced convergence time by incorporating both current and future magnetic field estimates into a special built Lyapunov-based control law we'd be perfecting for VLEO. By the time the issue popped up, we already had a lot of the ingredients needed and were able to get our algorithms to control within an orbit or two of initialization and then were able to stay coarsely stable for most inertial ECI attitudes albeit with wide pointing error bars as stated in the article. For what we needed though, it was perfect.
What kind of current are you driving those coils with (amps or dozens of amps?). What order of magnitude is the resulting force (a few newtons?)
I’ll gladly read the paper but knowing myself I won’t remember why exactly when a few weeks passed.
Is the drag much better than a regular cubesat? It doesn't look tremendously aerodynamic. From the description I was kind of expecting a design that minimized frontal area.
>Additional surface treatments will improve drag coefficient further.
Is surface drag that much of a contributor at orbital velocity?
Yes it's a big contributor. The atmosphere in VLEO behaves as free molecular flow instead of a continuous fluid.
> It is undesirable to have a definition that will change with improving technology, so one might argue that the correct way to define space is to pick the lowest altitude at which any satellite can remain in orbit, and thus the lowest ballistic coefficent possible should be adopted - a ten-meter-diameter solid sphere of pure osmium, perhaps, which would have B of 8×10^−6 m^2/kg and an effective Karman line of z(-4) at the tropopause
Stacks? Testing? Firmware Updates? Programming languages?
Thank you!
On orbit, we fixed it by pushing an FPGA update and adding software-level switching between the channels to prove the update applied and isolate the hardware path — which worked. Broader lesson, it is possible to design a sw stack capable of making updates to traditionally burned-in components.
Hah, this has bitten me often enough I check for it in test suites now - ok, you’ve proven the system works and the backup works, have you proven the primary works? Another in the long list of ways you don’t expect a system to bite you until it does…
This is interesting - is the software stack essentially acting as "light" translation layer or abstraction layer on components?
How does that work? Do you actually VPN into an orbiting satellite? If so, how do you get a public IP for a satellite? Do you just ask an average ISP?
I have no idea what they use but there are various commonly used radio communication methods for talking to satellites.
Of course, this is not necessary if they simply use UHF radio signals encoding bits with pulse modulation, or whatever.
Indeed, that's indeed what I was curious about (Internet vs other channels), since at least part of their tech stack in orbit is relatively straightforward (e.g. linux with preempt_rt).
Although it occurs to me that "does your network stack employ either ethernet or IP (and what were the considerations)" might be an interesting question.
All kidding aside, there are some protocols, like FTP or RTSP, which don't play well with NAT because they include IP addresses in the payload itself. Some solutions exist (so called ALG) but they are often fragile. If the satellite was using some of these protocols to talk to something on a public cloud platform (say, send images via FTP to an EC2 VM), satellites could have a public address to avoid NAT issues, and that point you could also use it as a management address (although maybe only as a backup path).
It's a bit far fetched, but when it comes to satellites, you could say "sky is the limit" :)
EDIT
I admit public IP addresses are a bit unlikely (but... who knows!). However, this picture on their website (https://cdn.prod.website-files.com/64529e978a785fb5da715f99/...) clearly shows a Grafana dashboard.
Ignoring for a moment the fact that Grafana could be self-hosted or in SaaS, Grafana is heavily used to collect logs and metrics from standard servers.
Of course, maybe they built their own integrations to convert raw logs and metrics sent via plain pulse modulation to plain syslog and Prometheus metrics, but maybe it's just that they're using (probably private) IP addresses on board and they are simply streaming logs and metrics to the ground using standard TCP/UDP protocols.
We wrote everything from low level drivers to the top level application and the corresponding ground software for commanding and planning as well. Going forward, we're writing everything top to bottom, just to simplify and have total ownership since we're basically there already.
For testing we hit it at multiple levels: unit test, hardware in the loop, a custom "flight software in test" we called "FIT" which executed a few different simulated mission scenarios, and we tried to hit as many fault cases as we could too. It was pretty stressful for the team tbh but they were super stoked to see how well it worked on orbit.
A big one for us in a super high resolution mission like this is the timing determinism (low latency/low jitter) of the guidance, navigation, and control (GNC) thread. Basically it needs execute on time, every cycle, for us to achieve the mission. Getting enough timing instrumentation was tough with the framework we had selected and we eventually got there, but making sure the "hot loop" didn't miss deadlines was more a function of working with that framework than any limitation of linux operating well enough in a RTOS fashion for us.
How did you test attitude control + the software stack on the ground? Did you use a simulator?
LeoLabs seems to have been really helpful here. What other startups formed your 'space stack' so to speak?
AIchat "compare and contrast the subtle implications of phrase/X with phrase/Y" suggests using "ad spend" for a number (like "budget"), and "ad spending" for activity and trend ("act of spending").
"Learns" has implications of discovery, smaller size, iterative, informality, individual/team scale, messy, and more. For illustration, to my ear, "Don't be stupid" fits as a "lesson", but not as a "learn" or a "takeaway". Nor as a "lesson learned", with its implication of formality and reflection. "Software X is flaky" fits better "learn" than "lesson". And "unmonitored vendor excursions are biting us" more a "takeaway" (actionable; practical vs process).
But it is great to point it out and to show how essential this kind of thinking is, and how it can help to focus on what is really important and what can be fixed.
What is interesting is to theorize about the relative impact of losing any of those three and how you managed to fix the second because you still had power and were able to communicate with the device. I think within those the order of relative importance would be communications, power and then attitude but I could well be mistaken.