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CW Skimmer 2.1 employs a high-sensitivity CW decoding algorithm based on Bayesian statistics, enabling simultaneous decoding of up to 700 CW signals within a receiver's passband on a 3-GHz P4 system when paired with a wideband receiver. The software features a fast waterfall display with sufficient resolution for visual Morse Code interpretation, automatically extracting and labeling callsigns on the waterfall traces. Extracted callsigns are exported as DX cluster spots via an integrated Telnet cluster server. The application includes a DSP processor with a noise blanker, AGC, and a variable-bandwidth CW filter, alongside an I/Q Recorder and player. It supports both 3 kHz radio passbands and wideband SDR receivers like SoftRock, RF Space SDR-IQ/SDR-14, SRL QuickSilver (QS1R), HPSDR Mercury, and Microtelecom Perseus. System requirements specify Windows XP/7/8/10 (32-bit or 64-bit), a Pentium-4 2.5 GHz for wideband operation or 1 GHz for 3-kHz radios, a COM port for CAT control, and a stereo sound card supporting 48 kHz sampling. It integrates with Elecraft KX3, Icom IC-7300/IC-7610, and Flex 6000 series radios, with documentation available for various setup configurations.

KGKSDR is my attempt at some SDR decoding software. I'm putting this software together purely as a learning exercise, to better understand the mathematics behind SDR in general.

WSJT-X and MAP65, open-source amateur radio programs, facilitate weak-signal digital communication. WSJT-X covers VHF/UHF to HF, decoding subthreshold signals. MAP65 optimizes for VHF/UHF EME with JT65. Free and GNU GPL licensed, WSJT-X is on Windows, Linux, and OS X, while MAP65 is Windows-only, supporting SDR hardware.

How-to decode and Display APRS Packets from WebSDR Audio using linux computer

SDR++ is a cross-platform, open-source SDR software designed for minimal bloat and ease of use, supporting Windows, Linux, macOS, and BSD operating systems. It incorporates multi-VFO capabilities and offers extensive hardware compatibility through both _SoapySDR_ and dedicated modules. The software features SIMD accelerated DSP for efficient signal processing and provides full waterfall updates when possible, which enhances signal browsing. Its modular design facilitates the development of custom plugins, allowing users to extend its functionality. The application's focus on a bloat-free architecture and user-friendly interface aims to simplify the experience of working with Software Defined Radios. The full waterfall update mechanism is particularly beneficial for visualizing and identifying signals across a wide frequency spectrum, improving operational efficiency for radio amateurs. The modular plugin system enables community contributions and specialized enhancements, making _SDR++_ adaptable for various amateur radio applications, from general listening to specific digital mode decoding.

Analyzing 433 MHz radio signals from common wireless devices, such as temperature sensors and remote controls, involves understanding **On-Off Keying (OOK)** modulation. This resource details the process of capturing these signals using a Software Defined Radio (SDR) like Gqrx and then visually inspecting the captured audio data in a sound editor such as Audacity. It differentiates between **Pulse Width Modulation (PWM)** and Pulse Position Modulation (PPM) encoding schemes, illustrating how to identify and decode binary data by eye based on pulse and gap durations. The article provides a step-by-step walkthrough for decoding a wireless thermometer's data, correlating bit patterns with known temperature, humidity, and channel values. It also demonstrates decoding an RF remote control's button presses, highlighting the constant and varying parts of the transmitted packets. The content further introduces automated decoding using tools like RTL_433, explaining its capabilities in parsing various device protocols and showing how to interpret its output, including modulation type and decoded data. Specific examples include analyzing Prologue sensor protocol specifications from RTL_433's source code and noting common operating frequencies like 433.92 MHz in Europe and 915 MHz in the US.

Decoding 433MHz-transmissions with software-defined radio.

Receiving & Decoding NOAA Weather Satellites using a simple rtl-sdr dongle, a helix antenna and a Windows PC

The Meteor-M N2 is a polar orbiting Russian weather satellite that was launched on July 8, 2014. Its main missions are weather forecasting, climate change monitoring, sea water monitoring/forecasting and space weather analysis/prediction. Meteor-M N2 transmits images using the digital LRPT protocol at around 137.1 MHz with can be received with an RTL-SDR.

Receiving **GOES-16** and **GOES-17** weather satellite imagery requires a specific hardware and software configuration, detailed in this practical guide. The author outlines the necessary components, including a Raspberry Pi, an RTL-SDR dongle, a suitable LNA with SAW filter for 1.69 GHz, and a parabolic grid antenna. This setup enables direct reception of high-resolution weather data, a fascinating aspect of amateur radio satellite operations. The installation process begins with preparing the Raspberry Pi, followed by updating the system and installing essential dependencies like `git`, `build-essential`, and `cmake`. A critical step involves compiling and installing `librtlsdr` from source, ensuring proper driver setup and blacklisting conflicting DVB drivers. The guide then walks through testing the RTL-SDR dongle to confirm device recognition and troubleshoot common issues like USB power or driver installation problems. Finally, the instructions cover cloning and building `goestools`, a software suite essential for processing the satellite signals. This compilation, while time-consuming on a Raspberry Pi, is crucial for decoding the raw data into usable imagery. The guide concludes with the initial steps for creating the `goesrecv.conf` configuration file, preparing the system for active satellite reception.

Ground Station offers real-time satellite tracking and radio communication capabilities, primarily for amateur radio operators engaged in satellite operations. It utilizes **TLE data** from sources like CelesTrak and SatNOGS for precise orbital prediction and integrates with various SDR devices, including RTL-SDR, SoapySDR, and UHD/USRP radios, to receive live signals. The software provides automated antenna rotator control and **Hamlib-compatible** rig control with Doppler correction, crucial for maintaining signal lock on fast-moving LEO satellites. It supports IQ recording in SigMF format and decodes several digital modes such as SSTV, FSK, GFSK, GMSK, and BPSK with AX25 USP Geoscan framing. Dedicated interfaces are available for satellite tracking, SDR waterfall displays with live transcription and packet decoding, and telemetry packet viewing. Users can manage TLE data synchronization and SDR hardware, along with browsing decoded outputs through an integrated file browser. An observations dashboard and DSP topology view further enhance the operational experience, providing comprehensive tools for monitoring and analyzing satellite passes.

This PDF document outlines the process for establishing an **OpenWebRX+** station utilizing Software Defined Radio (SDR) devices on a Linux platform, specifically Debian Bookworm. It details the capabilities of such a setup, including reception across various frequency bands supported by the SDR hardware and the decoding of multiple modes like FM, WideFM, SSB, AM, ADSB, FT8, and CW, with examples provided for FT8 reception and mapping, sensor data, and ADSB. The guide recommends specific hardware configurations, suggesting older x86-64 laptops with 4GB RAM or Raspberry Pi 4 models for the host system. For SDR devices, it endorses **RTL-SDRv3/v4** or HackRF, noting the necessary driver installations for RTL-SDR. The software installation sequence is meticulously laid out, from installing Debian Bookworm to adding OpenWebRX+ repositories, installing the application, and configuring device-specific drivers. Authored by Christian Horn (JL1AYH), the resource also includes a brief personal background of the author. It concludes with instructions for accessing the OpenWebRX+ interface via a web browser, either locally or remotely over a network, and provides contact information for further inquiries.