Decoding ADS-C with a Cheap Aliexpress LNB and SDRplay RSP1B

Thank you to Nagy István for sharing with us his setup for decoding ADS-C with a 180cm prime focus dish, a cheap Aliexpress LNB, an Aliexpress bias tee, and an SDRplay RSP1B.

István receives the ADS-C signal from the Inmarsat 4A-F4 satellite, which he can see from his home in Hungary. 

István also notes the following information about the Chinese LNB:

This LNB original for DVB reception, but it works on Inmarsat reception, 3.6Ghz where ADS-C signals are, without any modification... But sometimes you need correcting frequency because of LNB oscillator drifting. I don't use dielectric plate, I don't have any material for this, at the moment.

Compared to ADS-B, which continuously broadcasts an aircraft’s GPS position and velocity to any ground station or nearby aircraft, ADS-C instead sends position reports via satellite, and is especially used over oceans and remote areas without ADS-B ground receivers.

However, ADS-C is relatively complex for hobbyists to receive due to the need for a large satellite dish and LNB to convert the 3.6 GHz frequency down to a frequency receivable by most SDRs. However, fortunately, as István shows, the LNB can be obtained cheaply these days.

Inmarsat ADS-C decoding with Jaero and Virtual Radar

ADS-C Being Received with an 1.8m dish, cheap Aliexpress LNB and SDRplay RSP1B.
ADS-C Being Received with an 1.8m dish, cheap Aliexpress LNB and SDRplay RSP1B.

rtl_tcp_echo: Record and Replay IQ Streams with a Transparent rtl_tcp Proxy

Thank you to Sarah Rose Giddings for submitting news about the release of one of her latest software programs called "rtl_tcp_echo". This “man-in-the-middle” application enables you to simultaneously monitor and record signals of interest, then replay the captured IQ data at a later time using software compatible with rtl_tcp.

The software is compatible with Linux, and Sarah notes that a Windows build will be available soon.

RTL_TCP_ECHO is a Go application that acts as a proxy between an rtl_tcp server and its client. It transparently passes control commands (such as frequency, gain, and sample rate), forwards IQ data, and records the IQ stream to a file. Later, you can run the application in playback mode, serving the recorded IQ data as a fake rtl_tcp server—allowing SDR software to connect and replay the IQ stream.

Features

  • Proxy Mode:
    Forwards all rtl_tcp commands (including frequency and gain) and IQ data between client and server. Simultaneously records IQ data to a file.

  • Playback Mode:
    Serves a previously recorded IQ file as an rtl_tcp-compatible server for SDR software to connect and decode.

  • Transparent Command Handling:
    All client commands (frequency, gain, sample rate, etc.) are passed through with optional logging.

  • Simple Configuration:
    Easily specify listen/forward addresses and recording/playback file paths via command-line flags.
rtl_tcp_echo usage
rtl_tcp_echo usage

An Introduction to SDR’s and GNU Radio using an RTL-SDR

Thank you to Paul Maine for submitting his latest YouTube video titled "Introduction to SDRs and GNU Radio Using an RTL-SDR". The video introduces the RTL-SDR and GNU Radio, and then proceeds to demonstrate how to build a simple FM receiver using GNU Radio. Paul goes on to explain some further concepts, such as sampling, aliasing, interpolation, decimation, upsampling, and finally shows a few more example receivers built in GNU Radio.

E18 Introuction to SDR's and GNU Radio Using an RTL-SDR

EU Ham Radio Shops Suspend Shipments to the United States

With the recent changes to US import policy, many shops in the EU, including ham radio shops, have begun suspending shipments to the United States. This is the result of both a widespread suspension of shipments to the US by most EU mail carriers and the ongoing unpredictability of the situation.

One French reseller of our products has written in to our blog, and wanted to explain the reason for their decision to suspend shipments to the US. We believe that other ham radio shops in the EU may also be in a similar position.

To our US Amateur Radio Clients and Community

Because of the recent 15% tariff increase on products imported from the European Union, the suspension of several carrier services to the US, and the growing complexity of the US import system, our online shop Passion-Radio.com must suspend all shipments to the United States until further notice.

In particular, La Poste, the French national postal operator, suspended parcel shipments to the United States as of August 25, 2025 (1), removing one of the main EU–US postal channels. At the same time, UPS announced that starting September 8, 2025, an additional international processing fee will apply to all import shipments, regardless of origin.

There has also been some misunderstanding regarding customs procedures. When parcels arrive in the United States, the buyer must settle not only the 15% customs duty, but also the service fee charged by the carrier for filing customs declarations and advancing duties to US Customs. These charges are billed locally at delivery and remain outside the seller’s control. Import duties and tariffs are always the responsibility of the buyer, not the seller.

"Unfortunately, with constant changes in tariffs, rates, and carrier processes, we cannot guarantee fair, efficient, and transparent shipping conditions," said David, F1JXQ, Director of Passion Radio. "Our goal is to resume shipments to the US as soon as a reliable and cost-effective solution is available for everyone."

Meanwhile, our collaboration with five US-based suppliers continues without disruption, as the European Union has not imposed any retaliatory tariffs or reciprocal 15% import duties on products arriving from the United States.

Updates will be communicated through our shop: https://www.passion-radio.com/store/hamradio-us-tariff-43 and our social channels.

To all our US friends on the bands: we thank you for your understanding and support, and we look forward to resuming deliveries as soon as possible.

They go on to explain an example:

Practical tariffs impact on an item €50

Before tariffs (without 15%, rate €1 = $1.12 April 2025 rate)

Conversion: €50 × 1.12= $56.00*

Total payable ≈ $56.00

After tariffs (with 15%, rate €1 = $1.16 August 2025 rate)

Conversion: €50 × 1.16 = $58.00*

Customs duty 15%: $58.00 × 0.15 = $8.70

Carrier fees (on average, import processing): $15.00

Total payable ≈ 58.00 + 8.70 + 15.00 = $81.70

Total surcharge ≈ +$25.70 (~+45.89% increase compared to $56.00, before tariff tax)

* Not calculated, fees that may apply when converting Euro € <> US $.

FAQ

• Q1: Who pays import duties and tariffs when ordering from Europe?

By law, the US buyer must pay all customs duties, tariffs, and fees when importing goods from Europe. These charges are not paid by the seller.

• Q2: Why do carriers charge extra fees?

Carriers like UPS, FedEx, or DHL must submit customs declarations and advance duties to US Customs. For this, they bill a brokerage or processing fee directly to the buyer.

Sources :

(1) https://www.lemonde.fr/economie/article/2025/08/22/la-poste-suspend-l-envoi-de-colis-vers-les-etats-unis_6633516_3234.html

WOW@Home: A Global Network of RTL-SDR Based Radio Telescopes Looking for Alien Technosignatures

The Wow! signal is a famous, strong, and unexplained radio signal detected in 1977 by the Big Ear radio telescope in Ohio, lasting 72 seconds and appearing to originate from the constellation Sagittarius. Its origin remains unknown, with some speculating that it could be an extraterrestrial technosignature. Upon reviewing the signal data, Astronomer Jerry R. Ehman discovered the powerful signal burst in the readout and wrote a large "Wow!" next to it, unintentionally coining the name.

Wow@Home is a new project that aims to coordinate a network of small radio telescopes globally, in the hopes of increasing our chances of detecting interesting astrophysical and technosignature events, such as the Wow! event.

A network of small radio telescopes offers several distinct advantages compared to large professional observatories. These systems are low-cost and can operate autonomously around the clock, making them ideal for continuous monitoring of transient events or long-duration signals that professional telescopes cannot commit to observing full-time.

Their geographic distribution enables global sky coverage and coordinated observations across different time zones, which is especially valuable for validating repeating or time-variable signals. Coincidence detection across multiple stations helps reject local radio frequency interference (RFI), increasing confidence in true astrophysical or technosignature transient events.

These networks are also highly scalable, resilient to single-point failures, and capable of rapid response to external alerts. Furthermore, they are cost-effective, engaging, and accessible, ideal for education, citizen science, and expanding participation in radio astronomy.

However, these systems also come with notable limitations when compared to professional telescopes. They have significantly lower sensitivity, limiting their ability to detect faint or distant sources. Their angular resolution is poor due to smaller dish sizes and wide beamwidths, making precise source localization difficult.

Calibration can be inconsistent across stations, and frequency stability or dynamic range may not match the performance of professional-grade equipment. Additionally, without standardized equipment and protocols, data quality and interoperability can vary across the network.

Despite these constraints, when thoughtfully coordinated, such networks can provide valuable complementary observations to professional facilities.

The team note that the Wow! signal was strong enough that it could have been detected by a small home radio telescope. They go on to make the case that we could be missing out on detecting many compelling signals simply because radio telescopes aren't watching every part of the sky simultaneously. 

The project will monitor the Hydrogen Line frequency for interesting signals. Currently, the team is using a WiFi grid dish and an external LNA as the radio telescope hardware, but they also aim to evaluate our Discovery Dish with H-Line feed.

Wow@Home Typical Radio Telescope Hardware
Wow@Home Typical Radio Telescope Hardware

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.