Category: Applications

WHY2025 Conference: Passive and Active RADAR using Software Defined Radio

Videos from the WHY2025 (What Hackers Yearn) have recently been uploaded to YouTube, and there is one interesting talk by Jean-Michel Friedt titled "Passive and active RADAR using Software Defined Radio". 

RAdio-frequency Detection And Ranging (RADAR) aims at using electromagnetic signals for detecting target location and motion. We demonstrate in this talk various RADAR architectures using dual-channel coherent Software Defined Radio (SDR) receivers and the associated signal processing techniques relying heavily on cross-correlations. Embedded systems are tackled, with a Raspberry Pi providing enough computational power for recording and post-processing.

RAdio-frequency Detection And Ranging (RADAR) aims at using electromagnetic signals for detecting target location and motion. Being constantly illuminated with electromagnetic smog, we can benefit from existing radiofrequency emitters meeting RADAR requirements -- strong power and wide bandwidth -- for passive RADAR measurements where no active emitter is needed, using only coherent passive dual-channel Software Defined Radio (SDR) receivers for passive recording of existing signals. If existing signals are unsuitable, we can use the same principle with non-cooperative emitters such as a Wi-Fi dongle in an active RADAR setup.

All processing flowcharts are implemented using GNU Radio for real time acquisition, and GNU/Octave or Python for post-processing: generic principles will be demonstrated, applicable to all sorts of receiver hardware. We will conclude with Synthetic Aperture RADAR (SAR) where antenna motion is used to simulate wide aperture receiving antennas, adding azimuth resolution to range resolution.

Supporting documents are found a https://github.com/jmfriedt/SDR-GB-SAR or https://github.com/jmfriedt/passive_radar orhttps://github.com/jmfriedt/sentinel1_pbr

WHY 2025 - Passive and active RADAR using Software Defined Radio

PiCar – A DIY Car Radio Head Unit made from a Raspberry Pi and RTL-SDR

Thank you to Vinnie Moscaritolo for writing in and sharing with us PiCar, a project to develop a homebrew car radio head unit out of a Raspberry Pi and RTL-SDR. The advantage of PiCar over a standard vehicle head unit is that PiCar is not just a broadcast AM/FM tuner, but is also capable of tuning to and scanning for other signals, such as public safety. In addition, Vinnie has also added various other features to PiCar, such as a GPS nav system, and CAN bus snooper.

Vinnie writes:

What happens when a radio nerd with a Jeep and a Raspberry Pi decides factory dashboards are too boring? You get PiCar — a DIY car radio replacement with a VFD display, a couple of knobs, and a whole lot of hacker soul.

Built around RTL-SDR and Raspberry Pi, PiCar does AM/FM, GPS nav, CAN bus snooping, 1-wire sensors, and even streams tunes from your iPhone — all without draining your Jeep’s battery. It's not just a head unit, it's a rolling testbed for software-defined radio, CAN hacking, and embedded Linux audio.

Vinnie has posted a full 9-part series on PiCar over on his blog. The series covers the why and the how, with several demonstration pictures and videos.

PiCar - Raspberry Pi Car Radio Project

The PiCar head unit
The PiCar head unit

Decentralizing AIS: Trustless Maritime Tracking with SDR

Recently, Owen Taylor, the CEO of WAKE (Worldwide AIS Network), wrote in to us asking if they could promote their project, which is a decentralized AIS aggregation network based on receivers like RTL-SDR. The twist compared to existing aggregators like marinetraffic.com is that WAKE aims to reward users via a crypto token and simultaneously solve the distributed verification problem to avoid problems like spoofing and poor transparency. 

The post below is their own words, and we note that we are not affiliated with WAKE.


Every second, ships transmit short bursts of data over VHF, broadcasting their position, speed, course, and identity. This is AIS (Automatic Identification System), an open, unencrypted protocol that lets vessels, ports, and coastal authorities maintain a shared picture of maritime traffic. Beyond collision avoidance, AIS feeds into port logistics, environmental monitoring, search and rescue operations, and even the financial analysis that drives global commodities trading.

For years, much of this coverage has been built on a mix of official receivers, satellites and a scattered network of volunteers, many of them SDR hobbyists streaming data from antennas on rooftops and coastal hills.

This model works, until it doesn’t. AIS has a well-known weakness: there’s no built-in authentication. Anyone can transmit a valid-looking AIS message. That opens the door to errors and deliberate spoofing, and right now there’s no universal method for verifying what’s real.

How AIS Works

AIS operates on two dedicated VHF channels, 161.975 MHz and 162.025 MHz, using 9600 bps Gaussian Minimum Shift Keying (GMSK) modulation. Transmissions follow a self-organizing time division multiple access (SOTDMA) scheme, where each station selects its own time slots to avoid collisions.

An AIS message can carry vessel identity (MMSI), position (latitude, longitude), speed over ground (SOG), course over ground (COG), navigational status, and other voyage data. Ships transmit at intervals from every few seconds (for fast-moving craft) to every few minutes (for anchored vessels).

For terrestrial reception, the chain looks familiar to any SDR operator:

Antenna → RTL-SDR (or similar) → AIS decoder software → Data feed.

Noise floor, antenna gain, and local RF environment all influence range, which for a coastal VHF station is typically 20–40 nautical miles. Higher elevations and directional antennas can stretch this significantly.

The Current Aggregation Model

Global AIS coverage today comes from a mix of satellite AIS for open-ocean tracking and terrestrial AIS for coastal areas, ports, and choke points. The terrestrial component is heavily dependent on a patchwork of volunteer-operated receivers, often nothing more than a VHF antenna, an RTL-SDR, and a small computer feeding data into a central platform.

Commercial services like MarineTraffic (now owned by Kpler), VesselFinder, and AISHub aggregate these feeds into global datasets that are then resold to shipping companies, commodity traders, insurers, and governments. The scale is impressive, but it comes at a cost to transparency.

In a recent video circulating on Reddit, the CEO of Kpler openly described their “monopoly” on maritime data, built on the volunteers giving up their data for free. While this may be good for their commercial positioning, it also highlights the underlying issue: a small number of companies effectively control access to AIS data, much of which was gathered for free from hobbyists.

From a technical perspective, the aggregation model has another weakness: it is built on trust. If a feed sends false data, whether through AIS spoofing, misconfigured hardware, or bad GPS input, that information can still enter the global record. Most platforms only filter out data that is obviously invalid, and there is no universal multi-source verification or cryptographic proof of authenticity in the AIS ecosystem.

The Data Integrity Problem

AIS is intentionally open and unencrypted to encourage wide adoption and interoperability. The downside is that nothing stops someone from transmitting a false position for a real ship or inventing an entirely fake vessel.

Spoofing incidents have been documented around the world. “Ghost ships” have appeared hundreds of miles inland. Vessel positions have been falsified to hide illegal fishing or smuggling. In some regions, ships broadcast fake locations to evade sanctions or mislead competitors.

Because AIS is used for everything from traffic management to environmental compliance, bad data has real consequences. It can mislead port authorities, disrupt logistics chains, and undermine safety systems that depend on knowing exactly who is nearby.

Distributed Verification

When we talk about “distributed” in this context, we mean a network of many independent AIS receivers,  owned and operated by different people in different locations, all working together to validate the same signals. No single entity has control over the data pipeline, and no single point of failure can compromise the entire dataset.

This approach aligns with what’s known as DePIN (Decentralized Physical Infrastructure Networks). In a DePIN, real-world hardware, in this case, AIS receiving stations powered by RTL-SDR dongles, is deployed by a distributed community, and the data it produces is aggregated, validated, and made available on a blockchain. Contributors are often incentivized for their role in maintaining the physical infrastructure and supplying high-quality data.

Applied to AIS, DePIN solves the monopoly and trust problem by creating:

  • Redundancy — multiple stations cover the same area, making spoofing and errors easier to detect.

  • Transparency — all verification events can be independently audited.

  • Resilience — coverage doesn’t vanish if one provider shuts down or changes terms.

From a technical perspective, defeating AIS spoofing requires proving that a received message is both authentic and physically plausible. A distributed verification system can achieve this by:

  1. Time of Arrival (TOA) Checks
    Comparing reception timestamps across geographically separated receivers. A false signal transmitted from shore will produce a different TOA pattern than one from a vessel at sea.

  2. Motion Consistency
    Checking positions against realistic limits for speed, acceleration, and turn rate. If a ship appears to jump 50 nautical miles in a minute, it fails.

  3. Cross-Coverage Triangulation
    Using relative signal strength and geometry between receivers to estimate origin and compare it to the reported position.

  4. Peer Agreement
    Looking for identical messages confirmed by several uncorrelated receivers. Messages verified by multiple independent nodes have a much higher trust score.

Once these checks are complete, the verification results, not necessarily the raw AIS payload, can be recorded on a tamper-proof, public ledger (such as a blockchain). This creates a permanent, auditable history of which AIS messages passed validation and when, allowing anyone to verify the integrity of past data without relying on a single company’s database.

Incentivizing a Trustless AIS Network

WAKE (Worldwide AIS Network) applies distributed verification principles to AIS in a way that directly involves and rewards the SDR community. At its core, WAKE is a decentralized network of independently operated AIS receivers, often built around RTL-SDRs or similar hardware,  working together to validate and record maritime data in a public, tamper-proof ledger.

In the WAKE model, contributors run AIS stations that submit decoded messages to the network. These messages are cross-checked against others received in the same geographic area. A message is only accepted if it passes both multi-receiver consensus and physics-based checks such as motion consistency and TOA analysis. This ensures that false or spoofed data is rejected before it ever reaches the historical record.

For the SDR community, this represents an evolution of an existing role. Many hobbyists already contribute AIS feeds without recognition or compensation. In WAKE, you’re not just relaying what you receive, you’re part of a validation mesh that makes AIS data more secure and tamper-resistant.

Because WAKE is built on a trustless model, no single operator, including WAKE itself can alter or suppress verified data. The integrity of the maritime picture is maintained collectively, with every contributor helping to keep it honest.

For SDR operators, the incentive is clear: you can keep doing what you already do best, running reliable receivers with clean reception and precise timing, but now with direct rewards for your contribution and the satisfaction of helping build a more open, diverse, and verifiable AIS data ecosystem.

You can learn more about WAKE Here.

Closing Thoughts

AIS has transformed maritime safety and logistics, but it was designed for trust, not for security. That’s fine when all players are honest, but as spoofing incidents have shown, trust alone isn’t enough.

A verification layer built on distributed SDR receivers is one of the most promising paths toward a tamper-proof global AIS dataset. It’s not about replacing the existing AIS ecosystem, but strengthening it.

The SDR community is uniquely positioned to lead that shift. By participating in networks that focus on data integrity, you can help ensure the maritime picture is as accurate tomorrow as it was yesterday, and maybe even fill in the parts of the map no one else can see.

SignalsEverywhere Android Project Updates: Satellite Tracker, HackTV NTSC Transmitter, OBS To HackTV, PacketShare and More

Recently, Sarah Rose Giddings (aka SignalsEverywhere) has been actively developing several radio and SDR based projects for Android, and she would like to provide an update on them.

First, as mentioned in a previous post, Sarah has been developing APRS.chat, an online mailbox system for APRS messages sent over RF. She has also been making progress on various other projects, including various useful Android apps, which she has updated interested people on in her latest livestream.

Hangout Chat | Linux | HackRF NTSC Transmission | Android APPS and More!

Some of the links to the Android software she's working on have been provided below:

Works with Benshi Protocol Radios (VR-N76 UV-PRO etc)

Stuff Created After The Livestream

Help beta test Play Store Releases (Benshi Dash, Benshi Commander, APRS Chat): https://docs.google.com/forms/d/e/1FAIpQLSfNTrCBofQYam6f6CrZ8XxTxZw2vlOiaD6ehGs5NBOAbKkHWw/viewform?usp=header

Screenshots from Sarah's HackTV NTSC Transmitter
Screenshots from Sarah's HackTV NTSC Transmitter

RF Analyzer V2.0 Released: RTL-SDR Compatible Android App

Thank you to Dennis Mantz @dennismantz for writing in and sharing with us the news that RF Analyzer V2.0 has been released for Android devices. RF Analyzer is a popular multimode Android app compatible with a vast number of SDRs, including the RTL-SDR. It also now supports the RTL-SDR Blog V4!

To use the app, you'll need a compatible RTL-SDR such as the RTL-SDR Blog V3/V4, an Android Phone or Tablet with USB OTG support, and a USB-OTG adapter. 

The new V2.0 is a complete rewrite from scratch. Dennis notes the improvements to the app below.

The app has been completely rewritten from scratch. It now features a modern Material Design UI, a more powerful and intuitive interface, and improved performance across the board.

- Support for demodulation while app is in the background
- Improved stability, demodulation and recording features
- Integrated user manual and contextual help
- Added support for RTL-SDR Blog v4

The app is not free, but it is priced at only a few dollars, and there is a 7-day free trial with 60-minute time limit per session. The full feature list is shown below:

- Works with HackRF, RTL-SDR, or pre-recorded IQ files
- View live spectrum (FFT) and waterfall plots
- Demodulate AM, FM, SSB, and CW signals
- Record raw IQ samples for offline analysis
- A responsive and modern Material Design interface
- Scroll, zoom, and tune through the bands
- Built-in context-aware help and a full offline in-app manual

RF Analyzer V2.0 Running on an Android Mobile
RF Analyzer V2.0 Running on an Android Mobile
RF Analyzer V2.0 On a Tablet
RF Analyzer V2.0 On a Tablet

Dennis has also uploaded a video tutorial explaining how to use RF Analzyer V2.0, and there is a full online user manual available here.

RF Analyzer 2.0 - Quick Start Tutorial - Android SDR App

Moving SatDump Towards V2.0.0

Over on the SatDump blog developers Aang23 and Lego11 have recently uploaded a post discussing their plans to move SatDump towards Version 2.0.0. SatDump is currently the most comprehensive and popular software for SDR users wanting to decode images and data from satellites. 

The developers note that their update frequency has slowed down recently due to their focus on V2.0.0. The new version introduces significant under-the-hood changes that will make SatDump easier to manage and develop in the future, and also focuses on improved documentation.  

Users of SatDump will also see an improved GUI, new functionality such as crop, an SSTV decoder, support and improvements for a wide range of satellites, any many other improvements discussed in the post. 

We note that V2.0.0 has not yet been released. The post notes that at some point in the near future they will begin merging the new V2.0.0 branch into master, followed by frequency alpha releases, before finally releasing an official V2.0.0. 

SatDump V2.0.0 ALPHA with new GUI
SatDump V2.0.0 ALPHA with new GUI

RadioSport SDR: Portable Receiver Software for RTL-SDR

Thank you to Richard (9G5AR) for writing in and sharing with us a program he's developed called "RadioSport SDR". RadioSport SDR is a portable, no-install-required SDR program compatible with RTL-SDR devices. Richard writes that it is small and fast enough to be run off a USB stick.

The software supports demodulation of wideband FM, narrowband FM, AM, USB, and LSB modes. It also has a noise reduction feature.

The software can be downloaded from its GitHub release page here.

RadioSport SDR. Portable SDR Software for RTL-SDRs.

Saveitforparts: Receiving NOAA-15 One Last Time

Over on YouTube Gabe from the saveitforparts channel has uploaded a new video discussing the decommissioning of NOAA-15 and NOAA-19. We also previously posted about this topic a few days ago, if you are interested.

NOAA-15 was scheduled to shut down on August 12, 2025, but due to anomalies with NOAA-19, the decommissioning date of NOAA-15 has been extended by a few days until the week of August 18th. NOAA-19 has recently been experiencing transmitter failures, and it may be impossible to receive signals from it at the moment, despite its expected decommissioning date of August 19, 2025.

In the video, Gabe also rushes to try and receive signals from all transmitters on NOAA-15 one last time, setting up VHF, L-Band, and S-Band receivers. He experiences some issues with weak signals, interference, and recording failures, but ultimately succeeds in capturing all three signals during one of the final passes of NOAA-15.

US Government Shutting Down More Weather Satellites