Assuming your concept was valid, i.e. signal strength was a function of distance by
some formula (inverse square), the approach to follow is called least squares. Look
around for additional info with that terminology.

- jlw

Scott in Aztlan wrote:

Suppose you were participating in a search for a hidden radio transmitter, only
instead of the usual radio receiver with a directional antenna you have a
receiver with an omnidirectional antenna and a GPS receiver. As you wander
around, you collect positions from the GPS and signal strength values at those
positions from the radio; your goal is to crunch these data points into an
estimate of the transmitter's location.

Clearly you could use trilateration with any 3 of the data points and get an
estimate, but how would you make use of the fact that you have an arbitrary
number of data points? Isn't there some algorithm which, the more data points it
is given, the better its estimate gets (similar to the way you can average a
series of position readings taken from a stationary GPS receiver to compensate
for the effects of SA)?

Can someone point me in the right direction?

Thanks!

--
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