Jean-Michel Friedt

Hellschreiber is a morse-like graphical transmission of digital data reminiscent of fax over wireless communication media designed in the 1930s and used during the second world war by the German military. Now used by the ham radio community, we consider how hellschreiber is emitted using a Raspberry Pi GPIO pin configured as radiofrequency emitter, an approach made popular by rpitx and generalized to GNU Radio with our gr-rpitx OOT sink block (https://github.com/jmfriedt/gr-rpitx). The transmitted signal is recorded by a RTL-SDR DVB-T receiver and decoded using gr-hellschreiber (https://github.com/tlavarenne/gr-hellschreiber). Preparing this presentation was an opportunity to become familiar with GNU Radio 3.9 and the presentation concludes with some of the challenges (and solutions) met when porting gr-acars (https://sourceforge.net/projects/gr-acars/) to this new version of the signal processing framework.

J.-M Friedt & P. Abbé

Signal processing of Sentinel1 spaceborne RADAR datasets freely available from the European Space Agency web site, followed by the deployment of a corner reflector which will be visible in the latest datasets.

Software Defined Radio users and developers are well aware of the {I, Q} stream and their handling for powerful software processing at baseband. While most developments focus on hardware, acquisition and digital communication signal decoding, a huge dataset of {I, Q} samples is available from the spaceborne Sentinel1 satellites. Indeed, the European Space Agency is providing free access (the anonymous registration with the service will be discussed in the presentation) to the datasets collected by the two Sentinel-1{A, B} satellites. Spaceborne RADAR provide all-weather (RADAR is not affected by cloud), day-night (RADAR is active and does not depend on external illumination sources) monitoring conditions covering the whole surface of the Earth from the low Earth polar orbiting satellites. Most significant over optical measurements, microwave RADAR measurements allow for phase recovery and hence interferometric measurement which is not possible with optical measurements. Furthermore, radiofrequence wave complex interactions with the reflective surfaces (scattering, absorption, polarization rotation) provides a rich context for analysis complementary to optical observations.

Thanks to the Single Look Complex, Interferometric Wide datasets collected over land, discovering Interferometric Synthetic Aperture RADAR processing is no longer a matter of being associated with a dedicated laboratory and applying to selective research projects (e.g. Canadian RADAR-Sat datasets or German TanDEM-X) but only of fetching the huge datasets (4-GB/image) and learning the processing sequence.

In this talk which will appear as a sequel to the development of Ground Based SDR RADAR discussed during GRCon2020 [1], we will introduce a processing flowchart first relying on the SNAP graphical user interface provided by ESA before switching to an automated command line approach relying on Makefile since each processing step depends on the proper completion of the previous one. We will address some basic conditions whose results are expected, namely German open-pit coal mines and earthquake-induced land motion. Indeed the 5 mx20 m pixel and 5.6 cm wavelength is best suited for large scale, sub-cm natural or human-induced geomorphological transformations, while the short term coherence is best achieved by analyzing the successive data collected from one observation to another with a 12-day repetition rate.

After demonstrating a functional flowchart resulting in GeoTIFF phase and coherence maps consistent with optical satellite and aerial imagery, we conclude the presentation by adding a cooperative target corner reflector acting as localized point-like measurement source, assuming the reflector is large enough to be the dominant reflection source over the pixel area.

[1] Software defined radio based Synthetic Aperture noise and OFDM (Wi-Fi) RADAR mapping, GRCon 2020, at https://pubs.gnuradio.org/index.php/grcon/article/view/71

G. Goavec-Merou & J.-M Friedt

Embedded systems are tailored to a specific task aimed at minimizing resource and energy consumption (e.g. ADi PlutoSDR). Cross-compiling benefits from powerful personal computer computational resources and user-friendly interfaces while removing the burden on the embedded board of running the compiler. GNU Radio was ported to Buildroot to provide SDR enthusiasts access to the many boards supported by this cross-compilation framework. We demonstrate its use in a graduate course project aimed at developing an embedded network analyzer.

A network analyzer for characterizing a radiofrequency device requires a radiofrequency receiver for collecting the signal that was generated to probe the response of a Device Under Test, and a matching signal source. We consider the RTL-SDR dongle as the receiver, while the Raspberry Pi processor Phase Locked Loop (PLL) has been shown to generate a radiofrequency signal in the FM band. In this demonstration, PiFM is used as a signal source. As students were not allowed to visit university during lockdown, a cost-effective solution had to be found to provide hardware to all students to complete the course at home: the solution of a Raspberry Pi4 and DVB-T dongle was selected to provide the framework of embedded radiofrequency system development. GNU Radio is cross-compiled using Buildroot to the Raspberry Pi 4, iterative tests allow for checking the functionality of each step, until a complete measurement is achieved.

Software Defined Radio is best known for receiving and processing radiofrequency signals transmitted over the ether. However, many scientific experiments benefit from the flexibility, stability and reconfigurability of digital signal processing even when handling radiofrequency signals. In this presentation, we address two demonstrations of this concept. First, readily available SDR hardware is used to replace general purpose laboratory instruments (spectrum analyzer, lock in amplifier) for characterizing radiofrequency processing acoustic transducers (filters, resonators). The benefit of SDR lies in communication bandwidth: while general purpose instrument communication protocols (GPIB, VXI11 over Ethernet) require hundreds of milliseconds or seconds to transfer data, SDR platforms stream at high bandwidth I/Q coefficients collected on the fly on a ZeroMQ socket by the (GNU/Octave) processing software. We demonstrate a 10000 fold bandwidth gain when converting a general purpose instrument experiment to a SDR approach. Another approach is to address high bandwidth radiofrequency oscilloscopes as radiofrequency source for time of flight measurement. The gr-oscilloscope GNU Radio source demonstrates how to communicate between GNU Radio and laboratory grade equipment, here oscilloscopes, for processing discontinuous data streams using GNU Radio.

Combining the flexibility of FPGA hardware configuration with the high abstraction level of an operating system running on a general purpose central processing unit (CPU) requires mastering a broad range of knowledge, from low level hardware configuration to kernel drivers to libraries and userspace application. While some vendor specific frameworks tackle the challenge, we focus on a vendor independent solution applicable to current FPGA Systen on Chip providers: the OscImp Digital framework provides a comprehensive set of FPGA IP, associated Linux driver, library and userspace examples based on GNU Radio running on the embedded CPU. We demonstrate its use on the Redpitaya platform processing baseband signals as well as the Zynq, most significantly associated with the AD9363 radiofrequency frontend on the PlutoSDR board. In both cases, the FPGA is not only used to stream I/Q coefficients but pre-process the datastream in order to reduce bandwidth and efficiently feed the CPU: we demonstrate embedded FM broadcast radio reception as well as GPS decoding on the PlutoSDR custom bitstream. The framework is available at https://github.com/oscimp/oscimpDigital

A low cost, digital video broadcast-terrestrial (DVB-T) receiver is used to collect radiofrequency signals emitted from the low Earth orbiting Russian satellite Meteor-M2. The QPSK encoded signal is analyzed all the way from extracting bit values, to recovering the JPEG encoded image transmitted from the satellite. This investigation is an opportunity to experimentally assess all the layers of digital communication widely used from Deep Space communication to daily mobile phone communication, including Viterbi encoding, Reed Solomon error correction, and JPEG image display.

Few members of the audience might have any interest in the details of Meteor M2 weather satellite transmissions. However, tackling the reception of this digital weather satellite opens the opportunity to address most if not all the layers of the OSI model, from the physical layer by collecting the radiofrequency signal using a cost-effective DVB-T receiver acting as a general purpose software defined radio signal source, to the data link layer with the various error correction schemes implemented to address the corruption introduced by the noisy radiofrequency communication channel (Viterbi, Reed Solomon) and the network layer with the frame encoding including telemetry and, of course, the payload as a digital picture. The latter is encoded in JPEG format, adding more abstractions with the lossy compression to be reverted to display greyscale images representative of the atmosphere and ground reflectivity in the various wavelengths monitored by Meteor M2. This decoding path matches most recent space-borne signal transmissions, as documented by the Consultative Committee for Space Data Systems (CCSDS [1]), and despite extensive documentation available online, a practical demonstration of the various decoding steps helps understanding the many documents over which the information is spread.

[1] https://public.ccsds.org/Publications/BlueBooks.aspx

Global Navigation Satellite System (GNSS) positioning has become ubiquitous in many daily activities, with the Global Positioning System (GPS) being the most common source of signals. Having analyzed earlier the reception and decoding of such signals, we now address the issue of signal spoofing, and develop some of the requirements on the emitted signal power and stability to efficiently spoof single frequency GPS receivers, whether in mobile phones, cars or UAV.

Initially designed as a military positioning system (NAVSTAR & GLONASS), Global Navigation Satellite Systems (GNSS) and the Global Positioning System (GPS) in particular have become ubiquitous to mostly everyone's life. Before being a localization system through triangulation of the signals received from the satellite constellation, GNSS is based on time transfer. As such, it is used in multiple industrial applications requiring time-synchronization, whether for communication (mobile phone basestations), trading (stock exchange), or distributed sensor timestamping: a British study [1] estimates at 1 billion pounds (aka euros) per day the cost of GNSS disruption (jamming), not to mention the impact of spoofing in which the user might not even be aware that a false signal is being received. While GNSS spoofing, requiring multi-MHz bandwidth around a carrier frequency of 1575.42 MHz, used to be restricted to well funded organizations, the advent of Software Defined Radio (SDR) emitters opens the opportunity for any motivated developer to create a spoofing device. We here demonstrate the use of Analog Device's PlutoSDR for such a purpose, the need for an accurate local oscillator, the impact of the local oscillator frequency on the short term (phase noise) and long term (Allan deviation) frequency stability of the output signal, the capability to move mobile phones, cars and even high grade (UBlox) receivers to any location assuming a few conditions are met (emitting signals mimicking the same satellites as those seen at a given time by the receiver, meaning not too far in space or time with respect to the real signal). Finally, we demonstrate shifting the timing output of high-grade receivers (1 PPS) by introducing erroneous time offsets in the messages transmitted by the spoofing signal. We conclude with mitigation strategies, excluding multi-constellations approaches which are only a matter of better spoofing capability, but focusing on physical signal characteristics hardly spoofed from a single ground based emitter.

[1] https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachmentdata/file/619544/17.3254EconomicimpacttoUKofadisruptiontoGNSS-Full_Report.pdf

We demonstrate the use of affordable DVB-T receivers used as general purpose software defined radio interfaces for collecting signals from a non-cooperative reference emitter on the one hand, and signals reflected from non-cooperative targets on the other hand, to map the range and velocity in a passive radar application. Issues include frequency and time synchronization of the DVB-T receivers, mitigated by appropriate digital signal processing relying heavily on cross-correlations.

Passive radar uses existing non-cooperative emitters as signal sources for mapping non-cooperative target range and possibly velocity. The attractive features of this strategy is the lack of dedicated broadband source for RADAR application, low cost from the use of existing emitters, and stealth since the operator is undetectable. This measurement technique has become accessible to the amateur with the availability of low cost receivers ideally suited for software defined radio processing. In the framework of passive radar applications, two receivers must be synchronized to record simultaneously the reference channel and the signal reflected by the targets: cross correlation will then finely identify the reference signal delay in the measurement signal and allow for target identification. In the case of moving targets, a brute force approach similar to Doppler compensation in GPS acquisition is applied for the cross correlation to coherently accumulate energy: the range-Doppler maps hint at the distance to the target and its velocity. Most interestingly, in the latter context, clutter (signals reflected from static targets) is separated from the moving target which becomes well visible even in a complex environment. In this presentation, we discuss the details of real time acquisition and signal post-processing for passive radar application, while addressing some of the challenges of diverting DVB-T receivers from their original application. While passive radar has been demonstrated with FM broadcast emitters, analog television emitters, or wifi, we shall here consider the broadband signal provided by digital terrestrial television broadcast signal.

With the proliferation of unmanned aerial vehicles (UAV) on the one hand, and the availability of Structure from Motion (SfM) algorithm [1] in the opensource Micmac [2, 3, 4] software suite (French National Geographic Institute, IGN) for generating Digital Elevation Models (DEM) and orthophotos on the other hand, we describe the processing chain to acquire and geoereference DEMs in QGIS. The fast acquisition and very high (sub-meter) resolution are well suited for repeated measurements and assess terrain morphological changes. The processing sequence is

1. fly and acquire georeferenced images. If only a GPS receiver and camera are aboard the UAV, matching time tag with GPS date and time will allow for georeferencing the pictures (exiftool)

2. identify matching points between adjacent images: the GPS position is used to reduce the number of comparisons and limit the lengthy analysis to nearest neighbors

3. identify lens properties, bringing the largest cause of uncertainty in the model generation, from various pictures of the same ground feature exhibiting as much height variation as possible,

4. generate coarse point cloud to assess camera position and matching algorithm consistency

5. generate dense point cloud, orthophoto and DEM

6. include the resulting georeferenced pointcloud in QGis, converting the (arbitrary TIF) pixel value to quantitative height (meters).

We demonstrate sub-meter resolution DEM generation in vegetation-less environments (urban, glacier moraine) while coarse-acquisition (C/A) single-frequency GPS only allows for 5-m accuracy, hence requiring an additional ground control point matching step for repeated DEM comparison.

This presentation is a shortened sequel to the FOSS4G presentation given in 2016 (in French at the moment) focusing on UAV azimutal images.

[1] Nolan, M., Larsen, C. F., and Sturm, M.: Mapping snow-depth from manned-aircraft on landscape scales at centimeter resolution using Structure-from-Motion photogrammetry, The Cryosphere Discuss., 9, 333-381, doi:10.5194/tcd-9-333-2015, 2015

[2] J. Lisein, M. Pierrot-Deseilligny, S. Bonnet, P. Lejeune. A PhotogrammetricWorkflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery. Forests, Volume 4, Issue 4, pp.922-944, dx.doi.org/10.3390/f4040922, December 2013

[3] Daakir M., Pierrot Deseilligny M. , Pichard F., Bosser P (2015). & Thom C., UAV photogrammetry and GPS positioning onboard for earthworks, ISPRS Journal of Photogrammetry and Remote Sensing

[4] Github archive and its excellent documentation

DCF-77 is a German very low frequency (VLF) emitter locked on the Cs clocks of PTB used for synchronizing radiofrequency-disciplined clocks found, for example, in low-cost weather stations. VLF signals propagate through the waveguide whose boundary conditions are defined on the one hand by ground, and on the other hand by the ionosphere (charged) layer altitude. In addition to the amplitude modulation of the Cs-locked DCF-77 frequency standard, a phase modulation is imprinted on the carrier for time of flight measurement, allowing for "precise" time of flight measurements. The topic of the presentation is

1. reception of the DCF-77 VLF signal using a coil antenna, with enough power to feed a lock-in amplifier and extract phase and magnitude information. When the reference signal of the lock-in is referred to a local Cs primary standard, day/night ionosphere altitude variations are readily observed -- here using the carrier phase analysis,

2. extraction of the time of flight through CDMA processing of the phase output from the lock-in amplifier, recorded on a (low frequency) oscilloscope, emphasizing the time resolution improvement of the phase modulation with respect to the amplitude modulation gained from the increased signal bandwidth,

3. replace the lock-in amplifier with software-defined radio processing of signals recorded with a personal computer sound card or the analog to digital converter (RTL2832U) of a DVB-T receiver dongle,

4. refer the second channel of the stereo sound card/DVB-T to a low-cost GPS 1-PPS time reference for local oscillator drift compensation, and hence measure the ionosphere altitutde variation through time of flight variation by comparing the phase-encoded cross-correlation peak position with the 1-PPS position, yielding results consistent with the lab-grade instrumentation.

Although the whole processing chain is trivial, various issues making its practical implementation challenging will be emphasized. Most significantly, the processing chain is very similar to those applied to GPS signals, yet easier to grasp with the strong VLF signal. We aim at analyzing the time stability of the phase modulated signal -- allowing for sub-100 us timing resolution -- and correlated observed phase fluctuations with ionosphere altitude

RADAR systems are instrinsically wideband devices, with a range resolution inversely proportional to the probe signal bandwidth. Recording wideband signals is a challenging task, with high data rates often yielding low resolution samples and hence poor range. Multiple strategies have been investigated to reduce the recording rate, including stroboscopy (assuming a static environment), downconversion or frequency stepped measurements, all of which are well suited to feed Software Defined Radio applications. In addition to monitoring passive reflectors, cooperative targets can be designed to reflect a signal whose delay is not representative of distance or velocity but a physical quantity. One early application of such an insight has been the bug placed by Russians in the American ambassador house, modulating an incoming continuous wave illumination signal to an amplitude modulated backscattered signal. Although the leaked NSA documents hint at such techniques still being used today, we will be interested in more daily applications in which sensors are designed to return a signal representative of an identifier (ID-tag) or a physical property.

While Software Defined Radio (SDR) is mostly concerned with data transmission, especially for communication purposes, one original aspect of RADAR application of SDR is to consider the complete system, from emitter to receiver, and including the design of dedicated cooperative targets acting as sensors. While the backscattered signal from the target includes a signature representative of a physical quantity (amplitude, frequency, time of flight), the SDR approach provides the flexibility needed to adapt the emitted signal to the target signature. As an example, when the signature from a narrowband resonator is the resonance frequency -- shifting for example with temperature -- the flexibility of SDR allows for focusing on the spectral features under interest and prevents wasting time on regions of the spectrum where the signature is known, from prior measurement, not to lie. While the original Theremin [1] spying experiment [2] was using a dielectric cavity resonator whose boundary conditions were varying with a thin membrane position -- vibrating under varying pressure waves from the ambassador voice -- to convert the incoming Continuous Wave (CW) to a backscattered Amplitude Modulated (AM) signal, the signal to noise ratio is plagued by clutter from environmental reflectors. Time gating, as trivially implemented in SDR by a delay between switching between emission and reception for clutter to fade out before the sensor signal is detected, offers the opportunity for improved detection range which is hardly accessible to purely hardware implementation (eg Frequency Modulated Continuous Wave -- FMCW) RADAR strategies. The main challenge of SDR implementation of RADAR techniques is the necessary wideband emitter or receiver: various techniques have been envisioned to overcome the narrowband limitation of high resolution Analog/Digital sampling, including Frequency Stepped Continuous Wave or stroboscopy. These various approaches will be discussed, with hopefully some low cost demonstration of remote sensing using commonly available hardware, including acoustic filters acting as delay lines [3].

[1] A. Glinsky, Theremin: Ether Music And Espionage, University of Illinois Press (2005)

[2] P. Wright, Spycatcher, Heinemann (1987)

[3] J.-M Friedt, A. Hugeat, A low cost approach to acoustic filters acting as GPR cooperative targets for passive sensing, 8th International Workshop on Advanced Ground Penetrating Radar (IWAGPR), 2015

CDMA systems rely on encoding data streams radiated by multiple emitters on the same carrier frequency with (ideally) orthogonal codes. Recovering the signal from each emitter requires identifying the code assiociated with each source, which hence also requires recovering the carrier to account for relative emitter/receiver motion (Doppler shift), thermal drift and oscillator bias. We demonstrate this concept with the reception of GPS signal -- a constellation of satellites orbiting 20000 km over the surface of the earth -- with 20 euro worth of equipment centered on a DVB-T receiver designed for receiving neighbouring television signals. We extend the concept to passive radar, in which a radiofrequency emitter (television, broadcast radio) signal reflected on a mobile target is used for identifying the velocity and position of the target. In this approach, no active source is needed: RADAR measurement is only a matter of correlating the direct and reflected signal, after identifying the Doppler induced frequency shift.

Software defined radio has exhibited tremendous growth in the last years thanks to the wide availability of significant computational power available in embedded and personal computers and ubiquity of radiofrequency interfaces. One Open Source environment suitable for grasping the basics of digital signal processing, in particular applied to radiofrequency signals, is GNURadio. While software is freely available and shared through the internet, hardware remains dependent on the availability of suitable boards from hardware vendors. In order to justify the time investment in learning to use this signal processing environment, we discuss the development of custom processing blocks and adding custom sources.

Radiofrequency communication has become ubiquitous with the proliferation of digital radiofrequency networks and the continuing use of analog communication through wireless links (eg satellite and commercial FM transmission). The trend to shift from analog, hardware based receiver to software-based digital signal processing is dictated by the flexibility of the approach in which hardware is developed once and then used for multiple purposes by updating the firmware and processing algorithms. GNURadio provides a development environment in which a signal source is fed multiple processing blocks before reaching a data sink (oscilloscope output, sound card, file storage). Not only are most basic processing blocks already available, but the opensource aspect of the software allows for new developers to quickly become familiar with the various interfaces by browsing through the source codes. Hence, the time investment of learning the constraints of complying with the framework requirements of GNURadio is compensated for by the availability of most useful processing functions and quick display of basic processing functionalities (eg oscilloscope or FM radio reception). Dedicated applications of this processing environment to unusual applications such as physics lab or experiments is possible by implementing dedicated processing blocks and including these in the processing chain.

Indeed, signal processing functionalities are not limited to radiofrequency signals but can be extended to all sorts of capabilities: in this presentation, we will start by illustrating the development steps for implementing a new digital communication procotol (ACARS communication protocol used between aircrafts and ground) from prototyping using an interpreted language (GNU/Octave) in order to identify the core processing steps, to converting to C and then complying with the GNURadio framework. We will further discuss the development of such signal processing blocks as part of low-cost physics experiments in which various input sources (sound card and DVB-T receivers) are connected to dedicated digital signal blocks to extract the transfer function of a quartz tuning fork. Complying with the GNURadio framework allows for real time processing. Finally, we present the addition of custom hardware as input source, demonstrating the flexibility of the opensource approach and the relevance of the investment of learning this new development framework whose use is hence mostly independent of available hardware peripherals.

The last issue in the