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Stora September 13th 03 09:00 AM

Transmitter Hunt Using GPS
 

"Scott in Aztlan" wrote in message
...
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

---snip---

Can someone point me in the right direction?


Just follow the strongest radio signal. ;-)




Stora September 13th 03 09:00 AM


"Scott in Aztlan" wrote in message
...
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

---snip---

Can someone point me in the right direction?


Just follow the strongest radio signal. ;-)




Sam Wormley September 13th 03 09:24 AM

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?


If I understand clearly you are interested in locating an RF source which
has nothing to do with GPS by using RF receivers and nondirectional antennae.
Trilateration is only of value if one can establish accurate timing distances,
synchronized between all receivers.

If you used directional RF antennae, then, in conjunction with receiver positions
determined by GPS receivers, you could simply triangulate to estimate the RF
source position.

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)?


Of course SA was permanently discontinued more than three year ago.

Interagency GPS Executive Board (IGEB) - Special Statement
http://www.ostp.gov/NSTC/html/pdd6.html
http://www.igeb.gov/sa.shtml

Presidential Policy & PRESIDENTIAL DECISION DIRECTIVE NSTC-6
http://gps.faa.gov/gpsbasics/PresPolicy-text.htm
http://www.peterson.af.mil/GPS_Suppo...ts/gps_pdd.htm

Selective Availability
http://gps.faa.gov/gpsbasics/SA-text.htm

Joint Program Office
http://gps.faa.gov/gpsbasics/JPO-text.htm

Sam Wormley September 13th 03 09:24 AM

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?


If I understand clearly you are interested in locating an RF source which
has nothing to do with GPS by using RF receivers and nondirectional antennae.
Trilateration is only of value if one can establish accurate timing distances,
synchronized between all receivers.

If you used directional RF antennae, then, in conjunction with receiver positions
determined by GPS receivers, you could simply triangulate to estimate the RF
source position.

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)?


Of course SA was permanently discontinued more than three year ago.

Interagency GPS Executive Board (IGEB) - Special Statement
http://www.ostp.gov/NSTC/html/pdd6.html
http://www.igeb.gov/sa.shtml

Presidential Policy & PRESIDENTIAL DECISION DIRECTIVE NSTC-6
http://gps.faa.gov/gpsbasics/PresPolicy-text.htm
http://www.peterson.af.mil/GPS_Suppo...ts/gps_pdd.htm

Selective Availability
http://gps.faa.gov/gpsbasics/SA-text.htm

Joint Program Office
http://gps.faa.gov/gpsbasics/JPO-text.htm

Jerry L. Wahl September 13th 03 12:26 PM

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!

--
Friends don't let friends shop at Best Buy.



Jerry L. Wahl September 13th 03 12:26 PM

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!

--
Friends don't let friends shop at Best Buy.



Nitespark September 13th 03 12:37 PM



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?


A system for integrating GPS with direction finding has been out for a
few years now. Utilizing Doppler Direction finding equipment, the
heading of the Doppler array, along with the Lat Long of the monitoring
station is sent in a packet burst and superimposed on a map. When you
have 2-3 of these stations submitting this data in real time, you get a
practically instantaneous triangulation on the location of the transmitter.

The Agrelo Doppler units that were available several years ago, had this
capability.

Andy
WD4KDN



--
An armed man is a citizen, an unarmed man is a subject.
An armed society is a polite society.


Nitespark September 13th 03 12:37 PM



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?


A system for integrating GPS with direction finding has been out for a
few years now. Utilizing Doppler Direction finding equipment, the
heading of the Doppler array, along with the Lat Long of the monitoring
station is sent in a packet burst and superimposed on a map. When you
have 2-3 of these stations submitting this data in real time, you get a
practically instantaneous triangulation on the location of the transmitter.

The Agrelo Doppler units that were available several years ago, had this
capability.

Andy
WD4KDN



--
An armed man is a citizen, an unarmed man is a subject.
An armed society is a polite society.


Arcturus Apples September 13th 03 03:19 PM

What your describing sounds alot like GeoCaching.

An already-established sport which I have participated in.
Finally, most if not all of the participants in this sport
also seem to be a younger and/or a college educated
clientele.

More about it at the link(s) below:

http://www.geocaching.com/

http://www.mdgps.net/

http://gpsinformation.net/

"Scott in Aztlan" wrote in message
...
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!

--
Friends don't let friends shop at Best Buy.



Arcturus Apples September 13th 03 03:19 PM

What your describing sounds alot like GeoCaching.

An already-established sport which I have participated in.
Finally, most if not all of the participants in this sport
also seem to be a younger and/or a college educated
clientele.

More about it at the link(s) below:

http://www.geocaching.com/

http://www.mdgps.net/

http://gpsinformation.net/

"Scott in Aztlan" wrote in message
...
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!

--
Friends don't let friends shop at Best Buy.




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