Over on YouTube user Laboenligne.ca has uploaded a review of the ColibriNANO. If you didn't already know the ColibriNANO is a low cost but high performance direct sampling receiver designed for the HF bands. Currently it costs $269.95 US from nsiradio. It now competes almost directly with the recently released Airspy HF+ which is a lower cost $199 unit with similar performance specifications.
Laboenligne.ca's review initially goes over the specs of the ColibriNANO and usage of the free ExpertSDR2 software that is used with the ColibriNANO. He also shows how the ColibriNANO can be connected to a Raspberry Pi 3 and used remotely over the internet. This is similar to the Airspy's SpyServer, but the difference is that ColibriNANO's server interface works in a browser via HTML5, so it can be used on any platform including mobile devices. Of course the ExpertSDR2 software can also be used to connect to the server as well. In his review Laboenligne.ca notes that he is very impressed with the remote web interface and has set up a public server demonstration of his ColibriNANO available at vpn.laboenligne.ca. He notes that if there is no reception to try again later, as he may be using the antenna on another radio.
The ColibriNANO SDR receiver review (English version)
Many homes in the US and elsewhere no longer require meter reader personnel to come onto the property to read a physical meter at the back of the house. Instead the meter transmits wireless data in the 900 MHz ISM band about electricity usage, and all the meter reader has to do is turn up outside the house and take a reading from the street.
These electricity usage signals are unencrypted and can easily be decoded and displayed with an RTL-SDR and a ready to use program called rtl_amr. The signals even travel quite far, and there have been reports of receiving neighbours signals up to 600m away. K-roy took his RTL-SDR and rtl_amr and wrote on top of it a program that creates a JSON output of the data for easy processing, a PHP, SQLite3 and JQuery based database system for storing the data, and an HTML5 based page for graphing and displaying the data.
Over on Hackaday.io we've come across a project by "Tom" who has created a small tracking device which is located using an RTL-SDR dongle and directional Yagi antenna. The tracking device itself is a simple fingernail sized low power UHF transmitter that transmits short pulses about every second or so in the 915 MHz ISM band. Tom writes that the range is about 400m (line of sight) and with a small button cell battery the device lasts a couple of days with its 180 uA current draw. Presumably longer operation could be achieved by significantly reducing the pulse rate of the circuit.
To receive the tracking device an RTL-SDR is combined with a high gain directional Yagi antenna, a three level 10 - 30 dB attenuator and an Android phone running the RF Analyzer app. The idea is to simply use the attenuator and directional Yagi antenna to determine the direction in which the signal is strongest. That direction with the strongest signal will indicate where the transmitter is. Tom's video below shows an example of the transmitter and RTL-SDR based tracking setup.
Recently the SDR# team have updated the algorithm on the noise reduction plugins used in SDR#. It appears that both the IF and Audio noise reduction plugins were updated with a better smoothing algorithm. We briefly tested the new algorithm and compared it against an older version. The new algorithm has noticeably less hiss and is slightly clearer when compared at the same noise reduction level. We tested with the same threshold levels and using the speech profile.
At the same time we've also seen news that Simon of SDR-Console is working on another noise reduction algorithm based on deep neural networks in the latest private beta version. A video of it in action was posted by Paul J in the SDRplay users group (note that you will need a Facebook account and will probably need to be a member of the SDRplay group to view that video). The algorithm seems to be based on the RNNoise paper that was posted here. The SDR# algorithm was also tweaked based on information gained from that paper although it doesn't use neural networks directly.
If you are in the USA, you might recognize HD Radio (aka NRSC-5) signals as the rectangular looking bars on the frequency spectrum that surround common broadcast FM radio signals. These signals only exist in the USA and they carry digital audio data which can be received by special HD Radio receivers. Earlier in the year in June a breakthrough in HD Radio decoding for SDRs like the RTL-SDR was achieved by Theori when he was able to piece together a full HD Radio software audio decoder that works in real time.
It turns out that some of these HD Radio signals run by iHeartRadio also contain other data streams such as live weather and traffic data that is consumed by HD Radio based car GPS receivers or audio head units in US vehicles. HDRadio.com also write that they can embed other data such as sports scores and emergency messages into the data stream as well.
KYDronePilot's Python script utilizes Theori's decoder to save all received weather and traffic data maps for a folder. Below is an example of traffic and weather data that he received.
HD Radio Received Traffic DataHD Radio Received Weather Data
Inmarsat STD-C is an L-band geosynchronous satellite signal that transmits at 1.541450 GHz. This means that the signal can be received with a simple patch antenna, LNA and RTL-SDR dongle. The satellite is geosynchronous (stationary in the sky), so no tracking is required. On the STD-C channel you'll see messages mainly for mariners at sea such as weather updates, military operational warnings, pirate sightings/reports, submarine activity, search and rescue messages and more. If you are interested we have a tutorial based on other software packages available here which also shows some STD-C message examples. The tutorial can easily be adapted for use with Scytale-C instead.
We've also seen on Twitter that Scytale-C beta tester @otti has noted that a SDR# plugin based on Scytale-C seems to be in the works.
An Important Note on the Coding Ethics of Scytale-C + Tekmanoid Decoder Updates
We feel that it is responsible to make a note on coding and licencing ethics about this software. Originally the software was illegally decompiled by 'microp11' from the closed source Tekmanoid STD-C decoder written by Alex and re-released in a different programming language with a different GUI as the 'open source' B4000Hz software. After Alex took action and micrcop11 realized what he did was wrong he took B4000Hz down. Since then microp11 notes that he has written Scytale-C fully from scratch without the closed source code knowledge. But to be unquestionably legal a full two man clean-room rewrite would probably need to be done as once knowledge of source code is acquired it can be difficult to think of a separate implementation (a somewhat related post discussing this on StackExchange).
However, Alex has noted microp11's passion, and microp11's remorse at the initial decompilation and release of B4000Hz, and has decided to take the higher road and not pursue any further DMCA complaints. Instead he has kindly decided to allow the software to exist, but with acknowledgement of Tekmanoid included. We're glad that the matter was resolved amicably, but still if you use the Scytale-C software we would urge you to still consider the free or paid version of the Tekmanoid STD-C decoder to support Alex.
Recently Alex has updated his software to include a spectrum analyzer and more appealing method of displaying EGC messages. Alex writes regarding his Tekmanoid STD-C decoder:
This software [Tekmanoid STD-C Decoder] is closed source and has been since it was first released around 2009. At that time I made a choice to keep the source private but share the executable EGC app for free with the public, so that others could have some fun on the L-band!
The "pro" EGC-LES version was developed in parallel the same year but kept private, nobody even knew it existed. Although I recognized its potential financial value I didn't take "advantage" of it. Firstly because it was a personal hobby project (can't put a price on intellectual property) and second, because I didn't want to help to further expose people's private communications to the open public.
In February 2017 a raw clone of my de-compiled code was made public, to be later withdrawn with an apology. That is the moment I decided to release the PRO version as payware to the public. Many new features present in today's PRO version have been proposed by users and my aim is to satisfy everyone's wishes.
Recently another similar project was released from the same author, with lots of documents to support the code and only minute traces of the initial de-compilation. This time one could indeed claim to have built it "from scratch" - codewise at least. The fact still remains that *part* of the knowledge (not 'code' necessarily) required to put it together was obtained from this initial reverse engineering process.
Despite the negativity surrounding this case, I decided to withdraw my takedown request on the project in exchange for an acknowledgement to the original Tekmanoid decoder, as this person himself wished to include from the start anyway.
To end it with another positive note, I can only hope this newcomer will bring something new to the scene, and that we will see some interesting things!
Below is a video of the updated Tekmanoid decoder.
Tekmanoid EGC+LES pro decoder
Update: Microp11 wrote to us after this post went out and wrote the following:
I just want to let you know that scytalec is not a re-write. It is another solution of solving the problem of decoding the Inmarsat-C. Written from scratch. Inadvertently any Inmarsat-C decoder in the 1.5GHz band will have the same the building blocks and they are now documented in detail in the bibliography published with my code. The information is hard to find. All the information is from publicly available sources only. Such that the code will be able to withstand the obstacles or remaining open source. The majority of the documentation is technical manuals, as they each in part reveal a piece of the puzzle, and collectively they contain an almost complete communication protocol. Some are books and they must be the specific revision mention within the bibliography. Moreover if any coder will read the documentation they will actually be able to write a better decoder as I found parts of it too late for a more elegant code writing. And this is the whole idea of scytalec, that anyone can do it if they put their mind to it. There is enough documentation to tackle the C-band as well. And giving enough time, I might be planning on doing that after the sdr# plugin I’m working at. Not alone, as I was and I am being helped by others to which I am grateful and their names were and will be mentioned within the code. Just so you will have an idea of how deep the documentation correctness went for this project, even if a code comment was incorrect, say I was referring to a frame as a “block” or “part” I would get an admonishing email on that. So yes, I have high reasons to stand by this code originality.
Over on his YouTube Channel Mile Kokotov has uploaded a video that compares three mid priced SDRs: the Airspy HF+, the SDRplay RSP1A and the ColibriNANO. Each SDR is compared on several ALPHA and NBD morse code stations which exist in his tests from between 14 kHz to 474 kHz. He writes:
In this video I am comparing three SDR-Receivers. I have made few recordings with every receiver with the same antenna and choose the best one (one with the best SNR = signal-to-noise ratio). My intention was to ensure the same conditions for all three SDR`s in order to make as fair as possible comparison. For example, I was set the frequency span displayed on the window to be as same as possible for all three receivers. The vertical axis for the signal stregth, was set to be equal (in decibels) too.Airspy HF+ and ColibriNANO was set to their minimum sample rate (48 kHz). RSP1A was set to minimum sample rate (2 MHz and 8 decimation).
No DSP enhancing on the SDR`s was used except APF (Audio peak filter) on ColibriNANO (I forgot to swith off).
The differences between each receiver as very difficult to detect as only really challenging signal conditions will really set them apart. Mile also added in a comment:
You should not expect the difference to be very obvious! If you compare one average transceiver (which cost about $ 1000 USD) and top class transceiver which cost ten times more, the difference in the receiving the average signals will be very small too. Almost negligible! But when you have difficult conditions, the very weak signal between many strong signals, than the better receiver will receive the weak signal readable enough, but cheaper receiver will not. Today it is not a problem to design and produce the sensitive receiver, but it is very difficult to design and produce high dynamic receiver for reasonable price! The Airspy HF+ and RSP1A are very very good SDR-receivers. They have different customers target and have strong and weak sides. For example Airspy HF+ has better dynamics in frequency range where it is designed for, but RSP1A, on the other hand, has broadband coverage...
Late last month we posted about the Fairwaves XTRX SDR which is a Mini PCIE TX/RX capable SDR with 10 MHz - 3.7 GHz tuning range and 120 MSPS sample rate that costs $199 US and is currently crowdfunding on CrowdSupply. At the time of this post the XTRX is currently 84% funded.
Recently the XTRX team released an update regarding the HF performance below 30 MHz. The update shows that signal attenuation starts to significantly reduce in the HF bands with the 3dB point being at 11 MHz. At 6 MHz the attenuation is at 13 dB, and at 2 MHz it's up to 29 dB. This attenuation may not be too bad though especially for strong HF signals, or perhaps a preamp like the LNA4HF could be used. They attempted to review their design to reduce the attenuation, but found that there is no easy fix especially with having such restricted space as in a PCIE card.
They also note that HF reception with the LMS7002 chip used on the XTRX can be problematic as the LO is fixed to a minimum of 30 MHz. So to receive below 30 MHz the receiving bandwidth needs to be increased which can cause saturation from any strong out of band signals. However, they tested with some very simple external bandpass filters for the 49m band (5.8 - 6.2 MHz) and had decent results.
The XTRX team also added a new breakout header to the board which provides direct connections to the LMS7002 chip ADCs for direct sampling. This could provide even better HF performance with an appropriate custom frontend.
