Future of location services on OM
imrehg at gmail.com
Sat Jan 10 16:22:02 CET 2009
>> Oh, yeah, sounds easy... The problem is that the cell does not
>> broadcast any location information, so the best you can do is the go
>> around town, record the signal strength, and try to guess where the
>> signal is coming from. If there's plain sight it is relatively
>> straightforward. We tried it in a city - echos, shielding from
>> buildings... imagine the rest, the signal was all over the place. Not
>> something that one can analyse without further knowledge or guesswork.
>> Can send you some logs if you want to check it out
>> Having a "cell fingerprint" database - storing relative strengths of
>> multiple cells together with the recorded GPS position - would provide
>> better operation, but with a cost (in storage place, for example) that
>> is just not worth the effort. With the current GSM methods one does
>> not aim for supreme accuracy, just speed (you can locate which
>> intersection in a city you are in a second, not within 10+ minutes it
>> usually takes with my GPS).
> by simplifying a little but, this could become easier : assume that you log
> positions/cell relationships: for each cell ID, you compute the geometrical
> barycenter of the positions. You then store this position and its accuracy
> (the number of positions/cell relationships, maybe compute the geographical
> spread of the points) that you used to compute the mean.
> Assuming an dense, logging you would then have one position per cell, with
> a "quality factor" (~ how many measures have produced this point), you
> could then simply have a "nearest neighbour" approach to get to know where
> you are.
> It's true that you would not have the real antenna's positions, but you
> would have positions where many people have "seen" the cell ID, which could
> turn to be more accurate.
This is turning into a little bit specialized discussion, away from
the original "overall direction" question.
But to answer this: if you wish, I can send you real logged data. I
tried to do something what you suggest, but it only works well, if you
have logged data from a cell from all directions and from a number of
different distances. In real life, you can have a lot of log from one
side (e.g. west) from what I suspect to be the cell position (based on
signal strength), while on the other side (e.g. East) there's almost
nothing because other cells take over the. Buildings change the
pattern as well. Some times there's no possibility to go all around a
cell and then it can be really ambiguous where the cell is..... All
sorts of problems.
Also, tried real GSM based positioning with such "mean" positions. The
position one have to base on max. 7 (1 connected + 6 neighbours) cells
that the phone knows about at any given moment. Now the connected cell
is not always the one that is the closest - it's the one with the
strongest signal. In my town it seemed the network deployed a number
of very strong cells, supplemented with a lot of weaker cells in
between. My phone was mostly connected to the strong ones all around
town. Though this would be probably an issue with any other GSM based
positioning algorithm, because of the limited information the phone
can have about the network. Have to check how Android uses the cell
Having said all this: I'm not saying it is all impossible. I the
basics have been done (the CellLocator does it in a very rough
manner). I was just thinking that it seems right now, if we want to
compile a a GSM cell database ourselves, that will be 1) difficult, 2)
inaccurate, 3) user-unfriendly --- but none of these should completely
stop the effort.
On the other hand, how well the wifi-based positioning would work?
Have to take some real life data of that one as well, and try to use
More information about the devel