Thanks for all of the suggestions so far. We have been experimenting and researching for the last few days but we have been unable to come up with any sort of solution to our problem. We need to have a network of randomly placed nodes that can localize themselves in relation to each other. We would prefer to not use any static nodes but at this point we are willing to try anything. Even when we used static nodes, the static nodes still could not reliably measure the distance (because there is so much multipathing/interference i guess?)
Is this just impossible to do? Is there any way to relativity reliably localize nodes that are 1-3 meters from each other? Thanks so much, Matthew Jacques On Tue, Jun 14, 2011 at 6:05 PM, Michael Schippling <[email protected]>wrote: > search for "rssi location" and various other combinations. > there has been a lot of work done on this, and none of it > is very accurate. > > MS > > Matthew Jacques wrote: > >> Hello, >> >> I am currently trying to build a WSN using MicaZ motes and I need to know, >> to a fair degree of accuracy, how far apart one node is from another. I was >> reading up on how it is possible in some cases to use RSSI and LQI to >> achieve this. I tried taking measurements of average RSSI when the nodes >> were 1.5, 2 and 2.5 meters apart but the results were very erratic. While I >> did notice that the RSSI tended to be higher when the nodes were further >> away from each other, the results were not accurate enough to place the node >> within even 4 meters of its actual location. >> Is RSSI not an accurate enough way to get the precision I need? If not is >> there any other method I can use to get the distance between nodes? >> >> I was also thinking of maybe using the system time of the nodes to time >> how long a signal took to travel between them but I figured that with the >> time to send and the turnaround time of the message in the other node this >> would be a pretty inaccurate way to do it. Is that even worth trying? >> >> Thanks, >> >> Matthew Jacques >> >> >> ------------------------------------------------------------------------ >> >> >> _______________________________________________ >> Tinyos-help mailing list >> [email protected] >> https://www.millennium.berkeley.edu/cgi-bin/mailman/listinfo/tinyos-help >> >
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