Interesting. I did some R&D/Simple prototype coding for a WiFi Indoor Location Positioning System in 2001/2. I experimented with Kalman filters as well as RBFs in order to calm down the random jumping that occurs with indoor non-triangulated positioning. I say non- triangulated because, in truth it wasnt, and I assumed such problems would've disappeared had we been using Angle-of-Arrival or Time-of- Flight methods, similiar to GPS. I'd never heard of GPS jumping or giving inaccurate positions in the scenario of a weak signal however, after having gone through the task of WiFi LPS, I dont doubt it, RF is a strange place that can through some interesting curve balls at you.
It's a hard problem to solve if it's the case that GPS could give rise to the same issues. I'm sure with Cellular-Enhanced GPS, it becomes more likely. However, in order to implement something like this, I believe you would need decibal data from the GPS/Cellular Receievers for each signal incorporated into the measurement in order to weight each reading, I dont believe you would want to throw all readings in any kind of a filter equally weighted. Most of the time, say when the average Californian is driving on a busy roadway or highway, you should be able to receive a clean signal since, in terms of an average over distance traveled, you dont have too many tall buildings. Of course the anecotal response to that is that the large asian cities is where most users of these systems will probably reside however, the truth remains that good signals shouldnt be weighted the same as something that had poor signal quality to begin with. Although it's been.. six years since I've looked at Kalman Filters... time to refresh! I'm not sure if it's a problem but, It will be interesting to see what kind of problems come up with regard to positioning availability and accuracy! I think their will probably be a need for hybrid systems with something like Zigbee or, a kind of ultra- sensitive custom indoor time-of-flight/AoA system as people begin to realize the value of Location and not only demand to be tracked but, down to the foot, especially in heavily populated environments.. in say 5 years? Cheers, Brian A. On Dec 7, 2:12 pm, [EMAIL PROTECTED] wrote: > hi all, > > so i understand that there are lots of smart people at google, so > maybe maybe this is > already in shipping libraries :) > > My guess is that the GPS data coming back from the my android is just > raw, unmassaged > data as it gets it from whatever chipset the T1 is using (just like > what happens in the > emulator :). As people I'm sure realize, GPS data is really really > noisy, especially when > the signal is weak, etc. > > I've been googling around and it seems like Kalman filters for GPS > would be a good > way of doing curve fitting so that outliers and other nasties would > get smoothed out. > Does anybody know of either this filter, or some other GPS filtering > mechanism that > are either available through the API's, or elsewhere? > > TIA, Mike --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Android Developers" group. To post to this group, send email to [email protected] To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/android-developers?hl=en -~----------~----~----~----~------~----~------~--~---
