Back in August we posted a number of videos from the Software Defined Radio Academy talks held this year in Friedrichshafen, Germany. One of those talks was by Stefan Scholl, DC9ST and titled Introduction and Experiments on Transmitter Localization with TDOA. This was a very interesting talk that showed how Stefan has been using three RTL-SDR + Raspberry Pi setups to locate the almost exact position of various transmitters with time difference of arrival (TDOA) techniques. TDOA works by setting up at least three receivers spread apart by some distance. Due to the speed of radio propagation, the transmitted signal will arrive at each receiver at a different time allowing the physical origin point of the signal to be calculated.
He tested the system on various transmitters including a DMR signal at 439 MHz, a mobile phone signal at 922 MHz, an FM signal at 96.9 MHz and an unknown signal at 391 MHz. The results were all extremely accurate, locating transmitters with an accuracy of up to a few meters.
At the North-West University in South Africa Masters student SW Krüger submitted his dissertation titled “An inexpensive hyperbolic positioning system for tracking wildlife using off-the-shelf hardware” back in May of this year. Recently it was found online and can be viewed here (large pdf warning).
In his thesis Krüger explains his experiments with using RTL-SDR dongles to set up a very low cost wildlife monitoring system using TDOA (Time Difference of Arrival) techniques, and very low power beacons on the animal tags. TDOA is a difrection finding technique which involves using multiple receivers spread out over a region and calculating the difference in time from when the signal arrives at each receiver. With this information the position of the transmitter can be determined. Typically to do this the system clock in the computing hardware and OS needs to be synchronized as perfectly as possible between receivers, otherwise timing difference will cause huge errors in the position. Krüger uses synchronization bursts from a beacon, but notes that a real-time clock or GPS module could also be used for accurate time keeping.
In his experiment he set up two RTL-SDR receivers spaced 9 km apart and was able to obtain an accuracy of about 3.5m, which he writes is similar to other wildlife positioning systems that use tags with much higher power consumption. The computing hardware used at the RX station is a Raspberry Pi 3 powered by a 20W solar panel and batteries. There is also a wireless 3G modem for communications. The DSP software produced for the project is all open source and available on GitHub.