[mrandish]

Well, since you were kind enough to offer...

1. Roughly how long does it take for MagNav to get a "lock". For example, GPS takes 10 or 15 seconds (at least consumer stuff I have access to). Also, with GPS the accuracy improves if you're moving. I assume it may be similar with MagNav but it would be an interesting advantage if MagNav got a lock super fast vs GPS and/or it was basically at 100% resolution without needing to move (and I understand MagNav's "100%" res is much lower than GPS).

2. What's your drive-by guesstimate on probable future evolution of MagNav tech on the 'Four Horsemen' of mobile tech (size, weight, power, cost)? For example, which of the four are more like "No reason it can't improve a lot if given sufficient time, funding and development with no new science required" and are more "Well, physics/materials are currently an unsolved, seemingly fundamental barrier to improving beyond X threshold." In a perfect world... (the one we don't live in), MagNav would be on a five year productization track that'll put it inside an Micro SD card footprint with negligible power budget at 25 cents/ea by the million and be common in small Costco drones as a fallback if GPS fails.

Also, nicely appropriate username :-)

[shannonclaude]

1. MagNav needs to be done continuously over a trajectory. Like GPS, it actually needs to be fused with INS data to work. Also GPS actually takes longer for a good lock on. What your phone is actually doing is sensor fusion (GPS + wifi, onboard accelerometer and gyro, etc.) and caching of the satellite information in order to produce a best estimate immediately. So when you first get a lock it takes a while even up to 15 minutes depending on the environment. Afterwards your phone/receiver tends to remember what satellites there were in the trajectory. It's a background process thats constantly running. We've experienced this first-hand in our experiments.

2. Since I work for a company in this area, I can't say too much, but SWaP is definitely going to decrease. Right now I think you could decrease size to a midsize cereal box. I don't think a super accurate version would exist for phones yet. Power consumption is somewhat low, but you need a serviceable GPU and RAM, like an Apple M3 to run things. Power consumption will improve with improvements in compute.

I think cost is the most prohibitive of them all, because quality magnetometers and INS are not cheap. > $20K per unit at least. i'm not talking MEMS grade stuff you see in phones and student projects, I'm referring to Tactical/Navigation grade—the stuff you see on military platforms. I think you'll see MagNav on military planes much faster, due to their mission-critical needs. For commericial planes to use them at scale, one needs FAA clearance which is a bottleneck for good and bad reasons.

We're not in a perfect world yet. MagNav will take some time to develop. What I think is missing is a larger community to work on this issue. There isn't that much motion in the space. Less than 5 serious players in the game, IMO. There also aren't that many suppliers who make the parts (magnetometers, etc.) you need for MagNav.

Lots of more thoughts here, but if anyone wants to chat more, contact me at [e-mail]

[mrandish]

Thanks for taking the time to answer. That was a perfect level of detail to give me a broad, high-level vibe on MagNav. And the answers are about as I expected. Approaches which serve as an alternative to a ubiquitous, cheap, COTS tech (like GPS), are interesting. They're usually driven by highly specialized use cases where the cheap COTS default isn't always quite adequate and there's a small but meaningful number of customers with challenging requirements and deep pockets.

I imagine larger military drones which need to navigate autonomously for extended periods over denied environments in all conditions are very interested in MagNav as a component in their sensor fusion suites. Even narrowing the current position to less than a square kilometer would make the identification problems faced by other sensors like optical much easier to solve.