3 ms·

The single frequency situation isn't all that bad though since there are a dozen satellites in view and tracked even in urban outdoor environments.

s1mon 4y ago
I live in San Francisco. We don't exactly have the tallest buildings, but I can assure you from years of tracking runs in the downtown area here and nearby forested areas, GPS gets very screwed up unless it has a clear view of the sky. This is with a variety of Garmins, Apple iPhones and Apple Watch. I'm looking forward to the newer devices with L5.
- londons_explore 4y ago
  It's known as the 'urban canyon' effect. It can be significantly reduced if the GPS has access to a 3d model of the nearby buildings - then the GPS can guess which signals are probably reflections and which are direct. Alas, I think this isn't done outside data centers/labs, because the data download to have a large 3d model to get a GPS fix isn't a service anyone wants to run for free.
  - sorenjan 4y ago
    Uber showed this in 2018, I don't know how widely used it is now. I doubt any phone app uses it offline at least. https://www.uber.com/en-SE/blog/rethinking-gps/ https://www.uber.com/en-SE/blog/rethinking-gps/
- netheril96 4y ago
  Given how many Android phones already have this, maybe you could borrow one and compare? I want to know the answer.
jtolmar 4y ago
It's certainly better than it used to be, since there are more satellites, and a lot of work goes into doing well in these environments (I used to do the GPS integration for Google Maps). There are two big tricky parts about urban canyons. First, yeah, you still have quite a few satellites, but they're all in the same directions. Satellites directly above you don't really tell you anything. Satellites in front of and behind you can only tell you how far you are along that axis. You don't have any satellites to the sides, because you're in a canyon. So in an idealized version of a really bad urban canyon, the GPS can tell how far you are on the street, but not which street you're on, which is what the user actually wants to know. (I did a lot of work on knowing this from context, but it's still quite a mystery on a cold start.) The second is that, unlike natural canyons, signals in urban canyons tend to bounce. So instead of seeing the satellite missing, you see it giving a signal that's consistent with if you were in the next street over. Which is the same problem we had in the first place. There's a lot of outlier detection done in the chips, but in a really noisy environment, sometimes that'll inevitably end up throwing out the good data and choosing the outlier.
- dereg 4y ago
  Awesome explanation. Thank you.

s1mon 4y ago

I live in San Francisco. We don't exactly have the tallest buildings, but I can assure you from years of tracking runs in the downtown area here and nearby forested areas, GPS gets very screwed up unless it has a clear view of the sky. This is with a variety of Garmins, Apple iPhones and Apple Watch. I'm looking forward to the newer devices with L5.

londons_explore 4y ago
It's known as the 'urban canyon' effect. It can be significantly reduced if the GPS has access to a 3d model of the nearby buildings - then the GPS can guess which signals are probably reflections and which are direct. Alas, I think this isn't done outside data centers/labs, because the data download to have a large 3d model to get a GPS fix isn't a service anyone wants to run for free.
- sorenjan 4y ago
  Uber showed this in 2018, I don't know how widely used it is now. I doubt any phone app uses it offline at least. https://www.uber.com/en-SE/blog/rethinking-gps/ https://www.uber.com/en-SE/blog/rethinking-gps/
netheril96 4y ago
Given how many Android phones already have this, maybe you could borrow one and compare? I want to know the answer.

jtolmar 4y ago

It's certainly better than it used to be, since there are more satellites, and a lot of work goes into doing well in these environments (I used to do the GPS integration for Google Maps). There are two big tricky parts about urban canyons. First, yeah, you still have quite a few satellites, but they're all in the same directions. Satellites directly above you don't really tell you anything. Satellites in front of and behind you can only tell you how far you are along that axis. You don't have any satellites to the sides, because you're in a canyon. So in an idealized version of a really bad urban canyon, the GPS can tell how far you are on the street, but not which street you're on, which is what the user actually wants to know. (I did a lot of work on knowing this from context, but it's still quite a mystery on a cold start.) The second is that, unlike natural canyons, signals in urban canyons tend to bounce. So instead of seeing the satellite missing, you see it giving a signal that's consistent with if you were in the next street over. Which is the same problem we had in the first place. There's a lot of outlier detection done in the chips, but in a really noisy environment, sometimes that'll inevitably end up throwing out the good data and choosing the outlier.

dereg 4y ago
Awesome explanation. Thank you.