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.
We are considering building a new multi-purpose RTL-SDR product. The idea is to make several difficult to achieve applications and projects much more accessible. We are looking to implement the following ideas:
3x on-board coherent RTL-SDRs built into the PCB
4x SMA inputs: 3x individual inputs, 1x common input (switched between the two).
All RTL-SDRs connected to the same clock source – enables coherent experiments
All RTL-SDR feature sets and performance equivalent to RTL-SDR V3 or better
On-board noise source and directional coupler
Useful for correlation with rtl_coherent
Measure filter characteristics, and get rough SWR antenna readings.
Noise source able to be switched in and out via silicon switches
Useful with rtl_coherent and other coherent experiments for cross correlation timing correction. This allows for accurate direction finding.
Ability to mount onto a Raspberry Pi 3, and provide an ESD protected, buffered and filtered output for RpiTX transmissions. (a PCB plugin filter specific to the transmission frequency would need to be installed onto PCB to use this feature)
With a filter installed the board can be connected to an antenna and used with RpiTX for simple transmissions.
Go portable with an Raspberry Pi 3 compatible HDMI LCD screen and a battery pack. Possible HackRF portapack alternative.
Multi-band RTL-SDR applications
One RTL-SDR receiving NOAA, one receiving ADS-B, one scanning the air band.
Easy trunk tracking with 2x RTL-SDR. Third RTL-SDR used for something else.
One streaming NOAA weather, one scheduled to receive NOAA/Meteor sats and weather balloons, one receiving Outernet weather updates.
RF direction finding
Possible radio astronomy applications?
Noise source applications
VSWR meter with directional coupler
Raspberry Pi mount applications
Replay attacks and security analysis of ISM band devices with RpiTX and an ISM band filter.
Transmitting WSPR with WSPRpi.
Portable if used with a small HDMI screen and battery pack.
Possible control of board via an Android app.
Similar applications to the HackRF Portapack idea.
Multi-band noise locator if a GPS is added to the Pi. e.g. See Tim Havens’ ‘Driveby’ concept.
The idea is still in the concept stages so we’re looking for any feedback from the community to see if this is even something that people would want.
Would a receiver board like this interest anyone? We would also work on providing basic ready to go software on a downloadable image file for the Raspberry Pi 3 so starting an app would be as easy as using a launcher. We would also provide various tutorials as well.
The target price would be $99 USD. If you think this is too much, please let us know what you would expect to pay in the comments.
Are there any additional features that anyone requests? Please let us know in the comments.
Coherent-receiver.com is a company which is a customer of our RTL-SDR V3 dongle and they have been working on creating a multi-channel coherent receiver product based on the RTL-SDR. An RTL-SDR multi-channel coherent receiver is at its most basic, two or more RTL-SDR dongles (multi-channel) that are running from a single clock source (coherent). A multi-channel coherent receiver allows signal samples from two different antennas to be synchronized against time, allowing for all sorts of interesting applications such as passive radar and direction finding.
The team at coherent-receiver.com have used the new expansion headers on our V3 dongles to create their product. In their receivers they attach a control board which has a buffered 0.1 PPM TCXO (buffered so it can power multiple RTL-SDR’s). They also added an 8-bit register and I2C connection capabilities which allows for control of future add-on boards. The I2C capability is useful because it means that several RTL-SDR dongles can be controlled and tuned from the same control signal. More information on the registers and build of the receiver control board can be seen on their technical support page.
One example application of a multi-channel coherent receiver is passive radar. Coincidentally, we’ve just seen the release of new GUI based Passive Radar software by Dr. Daniel Michał Kamiński in yesterdays post. Passive radar works by listening for strong signals bouncing off airborne objects such as planes and meteors, and performing calculations on the signals being received by two antennas connected to the multi-channel coherent receiver.
A second example is direction finding experiments. By setting up several antennas connected to a multichannel coherent receiver calculations can be made to determine the direction a signal is coming from. An interesting example of direction finding with three coherent RTL-SDRs can be seen in this previous post. A third example application is pulsar detection which we have seen in this previous post.
Coherent-receiver.com sent us a prototype unit that they made with four of our V3 dongles. In testing we found that the unit is solidly built and works perfectly. We tested it together with Dr. Kamiński’s passive radar software and it ran well, however we do not have the correct directional antennas required to actually use it as a passive radar yet. In the future we hope to obtain these antennas and test the coherent receiver and the software further.
Currently they do not have pricing for these models as it seems that they are first trying to gauge interest in the product. If you are interested in purchasing or learning more they suggest sending an email to [email protected] It seems that they are also working on additional RTL-SDR ecosystem products such as filters, downconverters, antennas and LNAs.
We hope that the release of this product and Dr. Kamiński’s software will give a boost to the development of coherent multi-channel receivers as we have not seen much development in this area until recently.
David of rowetel.com has recently been working on creating a direction finding system with his HackRF. A direction finder can be used to determine which direction a radio signal is coming from and is good for detecting sources of noise, illegal transmissions, for amateur radio fox hunts or for in David’s case, tracking down a local repeater troll.
In most direction finding implementations so far people have ran two SDRs from the same clock source in order to create a phase coherent receiver. However David is using a different method and he writes:
The trick is to get signals from two antennas into the SDR, in such a way that the phase difference can be measured. One approach is to phase lock two or more SDRs. My approach is to frequency shift the a2 signal, which is then summed with a1 and sent to the SDR. I used a Minicircuits ADE-1 mixer (left) and home made hybrid combiner (centre).
David uses his HackRF to capture the signal and the free Octave numerical computation environment to compute the mathematics. In his post David explains the math behind this implementation, and shows some of his results in which he has been able to find the angle towards the transmitter in a test bench set up.
David also writes that this method could be used for offline direction finding. By logging the baseband signal whenever a transmission occurs, direction finding could be done days later and compared with several logged transmissions across town to get a cross bearing. He also writes that an offline logging system would be useful for evidence in case of prosecution of people illegally transmitting.
Something we missed posting about from last year was this presentation on “RasHAWK”, a direction finding system (pdf) built out of a Raspberry Pi, an RTL-SDR and four antennas on a 4 way switch running software created with REDHAWK. REDHAWK is a visual DSP development platform that can be considered similar to GNU Radio or some parts of MATLAB. The authors write:
The RasHAWK team has used a Raspberry Pi as the basis for a networked RF sensor capable of supporting spectrum monitoring, signal intercept and direction finding (DF) operations.
Several RasHAWK sensors are deployed in a distributed sensor grid, wirelessly tethered to a command and control (C2) laptop. The system has the following key features and capabilities:
A simple operator interface to configure the sensors
Falling raster and PSD displays to monitor the spectrum for signal activity
Demodulate FM signals from target FRS radios and play audio on selected channels
Perform coarse DF on target emitters
Display a map of the surrounding terrain that is annotated with the positions of the sensors, the target emitter and calculated lines of bearing (LOB) to the target. The map provides a RF Common Operating Picture (COP) with can be viewed on WiFi enabled tablets or smartphones.
Each RawHAWK sensor can determine the bearing of transmitted signal. By combining several networked RasHAWK sensors at different locations they are able to pinpoint the actual location of the transmitter on a map.