The work described in the paper uses 7 RTL-SDR dongles with their clocks connected together. Combined with noise source calibration, this results in a coherent SDR. They then train a Deep Neural Network to perform near field localization using an antenna array. If you are interested, we have out own 5-channel coherent SDR called "KrakenSDR" which will soon be released for crowd funding. The abstract reads:
Estimation methods for passive near-field localization have been studied to an appreciable extent in signal processing research. Such localization methods find use in various applications, for instance in medical imaging. However, methods based on the standard near-field signal model can be inaccurate in real-world applications, due to deficiencies of the model itself and hardware imperfections. It is expected that deep neural network (DNN) based estimation methods trained on the nonideal sensor array signals could outperform the model-driven alternatives. In this work, a DNN based estimator is trained and validated on a set of real world measured data. The series of measurements was conducted with an inexpensive custom built multichannel software-defined radio (SDR) receiver, which makes the nonidealities more prominent. The results show that a DNN based localization estimator clearly outperforms the compared model-driven method.
Thank you to Laakso Mikko a PhD student at Aalto University School of Electrical Engineering for submitting news about his research group's latest paper involving a 21-channel phase coherent RTL-SDR system. Laakso writes that he an his colleagues have built a (massive) multichannel receiver array from RTL-SDRs to use in low-budget research. The paper presented at EUSIPCO2020 can be found at IEEE, and for free on their research portal (direct pdf link). The code is also entirely open source and available on GitHub.
Phase coherent SDRs enable interesting applications such as radio direction finding (RDF), passive radar and beam forming.
We introduce a modular and affordable coherent multichannel software-defined radio (SDR) receiver and demonstrate its performance by direction-of-arrival (DOA) estimation on signals collected from a 7 X 3 element uniform rectangular array antenna, comparing the results between the full and sparse arrays. Sparse sensor arrays can reach the resolution of a fully populated array with reduced number of elements, which relaxes the required structural complexity of e.g. antenna arrays. Moreover, sparse arrays facilitate significant cost reduction since fewer expensive RF-IF front ends are needed. Results from the collected data set are analyzed with Multiple Signal Classification (MUSIC) DOA estimator. Generally, the sparse array estimates agree with the full array.
Mikko notes that his next paper on applying deep neural nets to the problem of near-field localization will be presented at this years VTC2021 conference, so we are looking forward to that paper too.
The SDRplay RSPDuo is a 14-bit dual tuner software defined radio capable of tuning between 1 kHz - 2 GHz. It's defining feature is that it has two receivers in one radio, which should allow for interesting phase coherent applications such as diversity.
From V1.32 onwards, MRC (Maximal Ratio Combining) Diversity is supported using the RSPduo. MRC Diversity can be used to combine the 2 tuner input streams together to potentially improved the SNR (signal to noise ratio). The same frequency is used for both tuners in the RSPduo and the gain can be adjusted either on each tuner independently or locked together (the default method).
Diversity mode is enabled by clicking on the RSPduo MODE dropdown and select DIVERSITY. Make sure both the 50 ohm ports are connected to the correct input source and note that the HiZ port is not available for Diversity mode. Trying to use the HiZ port will result in an error message being displayed.
Just a reminder that one week remains in the KerberosSDR Indiegogo campaign. This is your last chance to grab a KerberosSDR at a discounted preorder price. And at the time of posting there are still 50 "second early bird" units remaining at a discounted price of only $115 USD.
If you weren't already aware, over the past few months we've been working with the engineering team at Othernet.is to create a 4x Coherent RTL-SDR that we're calling KerberosSDR. A coherent RTL-SDR allows you to perform interesting experiments such as RF direction finding, passive radar and beam forming. In conjunction with developer Tamas Peto, we have also had developed open source demo software for the board, which allows you to test direction finding and passive radar. The open source software also provides a good DSP base for extension.
Due to the higher than anticipated number of preorders, we have been able to immediately fund further work on improving the demo software, and will be able to continue to work on improving it throughout this and next year. First on the agenda is improving the code buffering structure and DSP processing speed. Shortly after we'll be looking at adding additional features to aide with calibration and direction finding.
We have also now begun ordering parts, begun prototyping the metal enclosure, and have finalized the PCB. Manufacturing is on track to begin shortly after the campaign ends.
Over on their website the team behind the QIRX SDR software have written up an investigation into the feasibility of using RTL-SDR for phase coherent experiments. Phase coherent receivers can allow for experimenters such as interferometry, passive radar, direction finding, etc. In their experiment they connected the clocks of two RTL-SDR dongles together so that each dongle is running from a common clock. They then used their software to check if there was coherence on a DAB signal that they were receiving. To do this they used the null symbol present in DAB signal data to trigger the IQ display for each dongle. One display shows the difference in IQ data between the two dongles. If there is phase coherence then the graph should display zero. Their results found the following:
It has been possible to achieve phase-coherent operation of two I/Q data streams.
It has NOT been possible to achieve phase-coherent operation on every run of the system.
The system showed sub-sample time delay between the two receivers (if the interpretation of the observed behaviour is correct), varying randomly between different runs. A time delay of the two receivers sufficiently small for DAB demodulation of interleaved signals could only be achieved by pure chance. No attempts have been made to solve this problem during the experiments.
The system showed varying phase differences between the two receivers, changing at a constant rate. Three different changing rates have been observed during the experiments. A working solution has been found for this phenomenon, consisting in an continuous permanent correction of the phase angles of every sample. This imposes a considerable enhanced processing load. The occurrence of three different relative phase angle rotation speeds seemed strange. With the lack of documentation any attempt to interpret this behavior seems pure speculation.
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.