Netxing's idea was to use an FM transmitter connected to a computer to transmit known magnetic stripe card data via FM to the Portapack. The Portapack then receives and outputs this as FM audio to an electromagnet connected to the audio out jack, allowing it to activate the magnetic card reader.
Using this method it could be possible to make a payment by transmitting card data remotely over an FM signal. We're not sure on why you'd want to do this, but it is an interesting experiment regardless.
Lime Microsystems, creators of the LimeSDR, LimeSDR Mini and LimeNET SDR devices have recently begun crowdfunding for a new product they are calling LimeNET Micro. LimeNET Micro is described as a software defined radio platform with an integrated processor for creating self contained wireless networks. In other words it is a LimeSDR LMS7002M SDR transceiver chip with an included Raspberry Pi Compute Module 3, FPGA, GNSS module, EEPROM and Flash memory attached to it.
The LimeNET Micro is capable of full duplex TX and RX (1 port each) with the typical LimeSDR frequency range of 10 MHz - 3.5 GHz. However a major difference is that the LimeNET Micro is only capable of a 0.27 MHz bandwidth, whereas other LimeSDR products are capable of bandwidths up to 30.72 MHz. One interesting additional feature is that the LimeSDR Micro comes with a GNSS module that can be used to receive GPS/GLONASS etc for high accuracy timing if required.
Some use cases that they envision LimeNET micro being useful for include:
Inexpensive enterprise and personal networks
Rural, autonomous, and resilient networks
Universal IoT communications hubs
Rapid deployment infrastructure for emergency response
Remote radio solutions for amateur radio and radio astronomy
Integration into application-specific RF appliances
Radio spectrum survey
Passive wireless geolocation
PHY and security research
RF-aware robotics
The price is $269 USD and this includes a Raspberry Pi Compute Module 3. Higher end kits can be purchased which include Acrylic ($399) or Aluminum enclosures ($459).
LimeNET Micro with Raspberry Pi Compute 3 Module attached.
For a while now researchers at MIT and several other universities have been investigating methods for using frequencies in the WiFi bands to see through walls using a form of low power radar. The basic concept is to track and process the reflections of these signals from peoples bodies.
Recently researchers at MIT have taken this idea a step further, combining the radar results with machine learning in a project they call RF-Pose. The result is the ability to recreate and track full human post information through walls. The abstract from their paper reads:
This paper demonstrates accurate human pose estimation through walls and occlusions. We leverage the fact that wireless signals in the WiFi frequencies traverse walls and reflect off the human body. We introduce a deep neural network approach that parses such radio signals to estimate 2D poses. Since humans cannot annotate radio signals, we use state-of-the-art vision model to provide cross-modal supervision.
Specifically, during training the system uses synchronized wireless and visual inputs, extracts pose information from the visual stream, and uses it to guide the training process. Once trained, the network uses only the wireless signal for pose estimation. We show that, when tested on visible scenes, the radio-based system is almost as accurate as the vision-based system used to train it. Yet, unlike vision-based pose estimation, the radio-based system can estimate 2D poses through walls despite never trained on such scenarios.
The hope is that this technology could one day be used as a replacement for camera based computer vision. It would be a non-intrusive method for applications like gaming, monitoring the elderly for falls, motion capture during film making without the need for suits and of course for gathering data on peoples movements.
It is not mentioned in the paper, but it is likely that they are using some sort of SDR like a USRP for receiving the signals. It's possible that a lower resolution system could be set up cheaply with a HackRF and some passive radar software.
RF Pose Estimating Human Pose Behind walls using RF signals in the WiFi frequencies.Multiple people tracked with RF-Pose
As promised we announced the release to KerberosSDR mailing list subscribers first, so that they'd be the first to get the initial discounted early bird units. However due to much higher than expected interest, we have released a few "second early bird" units at a still discounted price of $115 + shipping. We're only going to release 300 of these so get in quick before the price jumps up to $125. Our pre-order campaign will last 30 days, and afterwards the retail price will become $150.
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.
KerberosSDR with Calibration Board Attached (Metal Enclosure with SMA connectors Not Shown)KerberosSDR Main Board (Metal Enclosure with SMA connectors Not Shown)
Over on his blog author Daniel Estevez has described how he's been listening to aircraft reflections from a 2.3 GHz 2W beacon. The beacon is 10km away from Daniels location and transmits a tone and CW identification at 2320.865 MHz. As aircraft fly nearby to his location Daniel was able to observe aircraft reflections of the beacon, and was able to match them with ADS-B position and velocity reports.
The hardware that he used was a LimeSDR and a 9dBi 2.4GHz planar WiFi antenna patch. By aiming the antenna away from the transmitter, and using his car as a shield to block the transmitter he was able to receive some reflections. Daniel recorded several reflections including one produced by a nearby car.
By combining his results with ADS-B data he was able to superimpose the results, and color aircraft tracks by either a negative or positive doppler shift which was observed from the reflection. By combining the ADS-B data with the time stamps, he was also able to mark the reflections from each aircraft.
Marking Aircraft Reflections at 2.3 GHz against ADS-B Data
Over on YouTube the Ham Radio 2.0 channel has recently uploaded a talk that Scotty Cowling (WA2DFI) did at the 2018 TAPR digital communications conference. His talk centers around single board computers and his findings on the nine best single board computers (SBC) for ham radio SDR setups.
Scotty's talk begins by discussing why you'd want to use SBCs in your ham radio SDR setup, and explains why you might want to place them with the SDR close to the antenna, and then distribute the data over ethernet cable. He then reviews 9 boards listed below:
Hardkernel Odroid C1
Raspberry Pi 3B
Hardkernel Odroid XU4
ASUS Tinker S
FriendlyElec NanoPC-T4
Pine64 RockPro64
96 Boards Mediatek X20
96 Boards HiKey 960
UDOO X86 Ultra
The boards are compared against CPU clock speeds, architecture, cache, debut year, RAM, boot ROM, bus speeds, OS support, and more. Scotty also discusses the need for low latency operation, but is yet to compare this on the boards. The best value for money boards that Scotty recommends end up being the Odroid XU4, Tinkerboard, NanoPC-T4 and the RockPro64.
Ham Radio 2.0: Episode 151 - Evaluating 9 of the Best Single Board Computers for Modern SDR Systems
VOR stands for VHF Omnidirectional Range and is a way to help aircraft navigate by using fixed ground based beacons. The beacons are specially designed in such a way that the aircraft can use the beacon to determine a bearing towards the VOR transmitter. VOR beacons are found between 108 MHz and 117.95 MHz, and it's possible to view the raw signal in SDR#.
Over on RadioJitter author Arnav Mukhopadhyay has uploaded a post describing how to decode VOR into a bearing in real time using an RTL-SDR dongle. His post first explains how VOR works, and then goes on to show an experimental set up that he's created using a GNU Radio program. With the software he was able to decode an accurate bearing towards the VOR transmitter at a nearby airport.
Arnavs post is a preview of an academic paper that he's worked on, and the full paper and code is available by request on the radiojitter post. We've also seen on YouTube that Arnav has uploaded a video showing the software working in action, and we have embedded it below.
Bearing to nearby airport VOR transmitter determined with an RTL-SDR and GNU Radio.
Amazon Alexa is a smart speaker that can be programmed to control home automation devices via voice commands. For example, Stuart Hinson wanted to be able to control his wirelessly controlled blinds simply by verbally asking Alexa to close or open them. Stuart's blinds could already be controlled via a 433 MHz remote control, so he decided to replicate the control signals on an ESP8266 with 433 MHz transmitter, and interface that with Alexa. The ESP8266 is a cheap and small WiFi capable microchip which many people are using to create IoT devices.
Fortunately replicating the signal was quite easily as all he had to do was record the signal from the remote control with his RTL-SDR, and use the Universal Radio Hacker software to determine the binary bit string and modulation details. Once he had these details, he was able to program the ESP8266 to replicate the signal and transmit it via the 433 MHz transmitter. The remaining steps were all related to setting up an HTTP interface that Alexa could interface with.
If you're interested, we've also previously posted about another Alexa + RTL-SDR mashup which allows Alexa to read out ADS-B information about aircraft flying in your vicinity.
