Ground Station is a full-featured, open-source software solution for satellite tracking and radio communication. Designed for amateur radio operators, satellite enthusiasts, and researchers, it provides a comprehensive and easy-to-use platform for monitoring spacecraft, controlling radio equipment, and receiving live radio signals from satellites. This project was built with the help of Claude Code and Codex.
Overview page with quick group selection and real-time satellite status indicators
Dedicated tracking interface for the targeted satellite showing orbital parameters, pass predictions, and real-time position data
Waterfall view with live transcription overlay during active satellite communication
Waterfall view with live GMSK packet decoding and decoded output details
Packet viewer showing telemetry payload bytes in hex with ASCII side-by-side
TLE synchronization page showing real-time progress and satellite database updates
Comprehensive SDR device management interface supporting RTL-SDR, SoapySDR, and UHD/USRP radios with remote capability
File browser view showing decoded weather images, packet outputs, and saved transcriptions
Automated observations dashboard with upcoming passes and task status
Chain of threads and processes IQ samples pass through, showing performance and data flow across the DSP pipeline
- Real-time Satellite Tracking: Track hundreds of satellites with high-precision orbital models. TLE data is automatically updated from CelesTrak and SatNOGS.
- Automated Antenna Rotator Control: Interface with popular antenna rotators to automatically track satellites as they pass overhead.
- Rig Control (Hamlib): Control Hamlib-compatible rigs with Doppler correction during satellite passes.
- SDR Integration: Stream and record live radio signals from a wide range of SDR devices, including RTL-SDR, SoapySDR, and UHD/USRP radios.
- IQ Recording & Playback: Record raw IQ data in SigMF format with complete metadata (center frequency, sample rate, satellite info) and play back recordings through a virtual SDR device for analysis and debugging.
- Data Decoding: Decode SSTV, FSK, GFSK, GMSK, and BPSK with AX25 USP Geoscan framing. LoRa and AFSK decoders are currently not working; help is needed.
- AI-Powered Transcription: Real-time speech-to-text for demodulated audio via Gemini Live or Deepgram. Privacy-conscious and user-keyed, with optional translation and file output to
backend/data/transcriptions/. - Scheduled Observations: Define detailed observation tasks that automatically listen, decode, transcribe, and record audio and IQ during satellite passes without manual intervention.
- SatDump Integration: Decode weather satellite images from METEOR-M2 (LRPT and HRPT) via SatDump, coupled with automated observations.
- Performance Monitoring: Real-time visualization of the signal processing pipeline showing data flow between components (SDR → FFT → Demodulator → Decoder → Browser), queue health monitoring, throughput rates, and component statistics to diagnose bottlenecks and optimize performance.
- Responsive Web Interface: A modern, responsive, and intuitive web interface built with Material-UI that adapts seamlessly to desktop, tablet, and mobile devices, allowing you to control all aspects of the ground station from anywhere on your network. Works great on a tablet and cell.
Ground Station includes a comprehensive automated observation system that can schedule and execute satellite passes without user intervention:
- Monitored Satellites: Define satellite monitoring templates with hardware configurations, signal parameters, and task definitions. The system automatically generates scheduled observations for all qualifying passes.
- Automated Pass Scheduling: Automatically calculate and schedule upcoming satellite passes based on configurable criteria (minimum elevation, lookahead window). The scheduler uses APScheduler to trigger observations at AOS (Acquisition of Signal) and stop at LOS (Loss of Signal).
- Flexible Task Composition: Each observation can include multiple concurrent tasks: IQ recording (SigMF format), audio recording (WAV), protocol decoding (AFSK, GMSK, SSTV), and optional AI transcription.
- Hardware Orchestration: Automatically controls SDR devices, antenna rotators (with satellite tracking), and rigs (with Doppler correction) during scheduled observations.
- Live Observation Capability: Users can observe any automated pass in real-time through the web interface - view the spectrum waterfall, listen to demodulated audio, and watch live decoder output. When using the same SDR as an automated observation, users can monitor without interference, but be aware that changing the SDR's center frequency or bandwidth will affect the ongoing observation.
- Multi-SDR Observing: Automated observations can run on one SDR while additional SDRs record, decode, and listen to the same pass in parallel.
- Status Management: Real-time observation status tracking (scheduled, running, completed, failed, cancelled, missed) with automatic cleanup of old completed observations.
- Session Management: Automated observations run in isolated internal VFO sessions (namespace: "internal:<observation_id>"). When using different SDRs, user sessions and automated observations operate completely independently without any interference.
The following features are planned or in development:
- Additional Decoders:
- AFSK packet decoder
- LoRa decoders
- NOAA APT weather satellite images
- Additional telemetry formats
The Ground Station application is composed of a frontend, a backend, and a set of worker processes.
flowchart TB
%% Cache buster: v5-20251115-updated
%% Frontend Layer
A[Frontend: React + Redux + MUI<br/>- Real-time UI updates<br/>- State management<br/>- Interactive satellite maps<br/>- Spectrum & waterfall display<br/>- Audio playback & recording<br/>- IQ recording & playback controls<br/>- Decoder monitoring & output display]
%% Backend Layer
B[Backend: FastAPI + Socket.IO<br/>- WebSocket connections<br/>- Worker process management<br/>- Database operations<br/>- TLE data fetching<br/>- Recording & file management<br/>- Decoder lifecycle management]
%% Worker Layer
subgraph Workers["Worker Processes"]
direction TB
W1[Satellite Tracker + Hardware Control<br/>- Antenna rotator control<br/>- Rig/radio control<br/>- Real-time tracking calculations<br/>- Hardware state management]
W2[SDR IQ Acquisition<br/>- Raw IQ sample streaming<br/>- IQ Broadcaster pub/sub<br/>- Multi-consumer support]
W2A[FFT Processor<br/>- Spectrum computation<br/>- Waterfall generation<br/>- Real-time FFT analysis]
W2B[Demodulators<br/>- FM/SSB/AM modes<br/>- Normal & Internal modes<br/>- Frequency translation<br/>- Audio processing<br/>- Multi-VFO support]
W2C[IQ Recorder<br/>- SigMF format recording<br/>- Metadata capture<br/>- Satellite info tagging<br/>- Waterfall snapshot saving]
W2D[Decoders<br/>- SSTV image decoder ✓<br/>- AFSK packet decoder WIP<br/>- LoRa/GMSK decoders WIP<br/>- Audio Broadcaster for monitoring]
W3[SDR Local Probe<br/>- Device discovery<br/>- Local SoapySDR enumeration<br/>- Hardware capability detection]
W4[SDR Remote Probe<br/>- Remote SoapySDR discovery<br/>- Network device scanning<br/>- Remote capability detection]
end
%% Hardware Layer
subgraph Hardware["Hardware Interfaces"]
direction LR
H1[Antenna Rotators<br/>- Hamlib compatible<br/>- Az/El control]
H2[Radios/Rigs<br/>- CAT control<br/>- Frequency tuning]
H3[Local SDR Devices<br/>- RTL-SDR<br/>- SoapySDR devices<br/>- UHD/USRP]
H4[Remote SDR Devices<br/>- SoapyRemote<br/>- rtl_tcp servers<br/>- Network receivers]
H5[SigMF Playback<br/>- Virtual SDR device<br/>- Recording playback<br/>- SigMF metadata reader]
end
%% Storage Layer
subgraph Storage["Data Storage"]
S1[SigMF Recordings<br/>- .sigmf-data files<br/>- .sigmf-meta files<br/>- Waterfall snapshots]
S2[Decoded Outputs<br/>- SSTV images<br/>- Packet data]
end
%% External Services
subgraph External["External Data Sources"]
E1[TLE Data Sources<br/>- CelesTrak<br/>- SatNOGS DB]
E2[Satellite Databases<br/>- Transmitter info<br/>- Orbital data]
end
%% Connections - Frontend to Backend
A <---|Socket.IO<br/>Bidirectional| B
%% Backend to Workers
B ---|Message Queues<br/>Commands & Status| W1
B ---|Message Queues<br/>Stream Control| W2
B ---|Message Queues<br/>Discovery Requests| W3
B ---|Message Queues<br/>Remote Scanning| W4
%% SDR IQ Distribution via IQ Broadcaster
W2 ---|IQ Broadcaster<br/>Subscribe| W2A
W2 ---|IQ Broadcaster<br/>Subscribe| W2B
W2 ---|IQ Broadcaster<br/>Subscribe| W2C
W2 ---|IQ Broadcaster<br/>Subscribe Raw IQ| W2D
%% Demodulator to Decoder Chain
W2B ---|Internal Mode<br/>Audio Broadcaster| W2D
%% Data back to Backend
W2A ---|FFT Data<br/>Spectrum/Waterfall| B
W2B ---|Audio Data<br/>Demodulated| B
W2D ---|Decoded Data<br/>Images/Text/Packets| B
W2D ---|UI Audio Stream<br/>Live Monitoring| B
%% Recording Storage
W2C ---|Write SigMF<br/>Recording Files| S1
W2D ---|Write Decoded<br/>Output Files| S2
%% Hardware Control
W1 ---|Control Commands| H1
W1 ---|Frequency Control| H2
W2 ---|IQ Data Streaming| H3
W2 ---|Network Streaming| H4
W2 ---|Playback Source| H5
W3 ---|Device Enumeration| H3
W4 ---|Remote Discovery| H4
%% Storage Access
H5 ---|Read Files| S1
B ---|File Management| S1
B ---|File Management| S2
%% External Data
B ---|HTTP/API Requests| E1
B ---|Database Queries| E2
%% Dark Mode Styling
classDef frontend fill:#1a237e,stroke:#3f51b5,stroke-width:2px,color:#ffffff
classDef backend fill:#2e7d32,stroke:#4caf50,stroke-width:2px,color:#ffffff
classDef worker fill:#e65100,stroke:#ff9800,stroke-width:2px,color:#ffffff
classDef hardware fill:#4a148c,stroke:#9c27b0,stroke-width:2px,color:#ffffff
classDef storage fill:#01579b,stroke:#0288d1,stroke-width:2px,color:#ffffff
classDef external fill:#b71c1c,stroke:#f44336,stroke-width:2px,color:#ffffff
class A frontend
class B backend
class W1,W2,W2A,W2B,W2C,W2D,W3,W4 worker
class H1,H2,H3,H4,H5 hardware
class S1,S2 storage
class E1,E2 external
%% Dashed borders for subgraphs
style Workers stroke-dasharray: 5 5
style Hardware stroke-dasharray: 5 5
style Storage stroke-dasharray: 5 5
style External stroke-dasharray: 5 5
This diagram shows how radio signals flow through the system from SDR hardware to decoders and UI:
flowchart TB
%% SDR Source
SDR[SDR Hardware<br/>RTL-SDR, SoapySDR, UHD]
%% IQ Broadcaster
IQB[IQ Broadcaster<br/>Pub/Sub Pattern<br/>Deep copy for each subscriber]
%% Primary Consumers
subgraph Consumers["IQ Consumers"]
FFT[FFT Processor<br/>→ Spectrum Display]
REC[IQ Recorder<br/>→ SigMF Files]
DEMOD[Demodulator<br/>FM/SSB/AM]
IQDEC[IQ Decoders<br/>GMSK/FSK/BPSK]
end
%% Demodulator Branches
subgraph DemodBranch["Demodulator Types"]
direction TB
NORM[Normal Mode<br/>User Playback]
INT[Internal Mode<br/>For Decoders]
end
%% Audio Broadcaster for Internal Demodulators
AUDIOB[Audio Broadcaster<br/>Pub/Sub Pattern<br/>Deep copy for each subscriber]
%% Decoder Chain
subgraph DecoderChain["Audio-based Decoder Processing"]
direction TB
DEC[Decoder<br/>AFSK]
UIAUDIO[UI Audio Stream<br/>Live Monitoring]
end
%% Output Destinations
subgraph Outputs["Outputs"]
SPECUI[Spectrum/Waterfall UI]
SIGFILE[SigMF Recording Files]
PLAYBACK[Audio Playback to User]
DECOUT[Decoded Data<br/>Images/Text/Packets]
AUDIOUI[UI Audio Player<br/>Decoder Monitoring]
end
%% Connections
SDR -->|Raw IQ Samples| IQB
SDR -->|Raw IQ Samples| FFT
IQB -->|Subscribe| REC
IQB -->|Subscribe| DEMOD
IQB -->|Subscribe| IQDEC
DEMOD -->|Branch| NORM
DEMOD -->|Branch| INT
NORM -->|Audio Queue| PLAYBACK
INT -->|Audio Queue| AUDIOB
AUDIOB -->|Subscribe: decoder| DEC
AUDIOB -->|Subscribe: ui| UIAUDIO
FFT -->|FFT Data| SPECUI
REC -->|Write| SIGFILE
DEC -->|Decoded Output| DECOUT
IQDEC -->|Decoded Output| DECOUT
UIAUDIO -->|Audio Chunks| AUDIOUI
%% Styling
classDef hardware fill:#4a148c,stroke:#9c27b0,stroke-width:2px,color:#ffffff
classDef broadcaster fill:#d84315,stroke:#ff5722,stroke-width:3px,color:#ffffff
classDef processor fill:#e65100,stroke:#ff9800,stroke-width:2px,color:#ffffff
classDef output fill:#01579b,stroke:#0288d1,stroke-width:2px,color:#ffffff
classDef decoder fill:#1b5e20,stroke:#4caf50,stroke-width:2px,color:#ffffff
class SDR hardware
class IQB,AUDIOB broadcaster
class FFT,REC,DEMOD,NORM,INT processor
class SPECUI,SIGFILE,PLAYBACK,DECOUT,AUDIOUI output
class DEC,UIAUDIO decoder
IQ Broadcaster (Pub/Sub Pattern):
- SDR produces raw IQ samples at high rate
- IQBroadcaster distributes to multiple consumers simultaneously
- Each subscriber gets independent queue with deep-copied samples
- Slow consumers: messages dropped rather than blocking producer
- Supports: FFT processor, demodulators, IQ recorder, decoders (LoRa/GMSK)
Audio Broadcaster (Decoder Pattern):
- Only used for internal demodulators feeding decoders
- Distributes demodulated audio to:
- Decoder subscriber: SSTV/AFSK decoder processing
- UI subscriber: Live audio monitoring in browser
- Statistics tracking: delivered/dropped message counts per subscriber
- Graceful slow consumer handling
Chain Processing Example (SSTV):
- SDR → IQBroadcaster → Internal FM Demodulator (SSTV)
- FM Demodulator → AudioBroadcaster input queue
- AudioBroadcaster → Decoder subscriber → SSTV Decoder → Image output
- AudioBroadcaster → UI subscriber → Browser audio player
Why Broadcasters?
- Decoupling: Producers don't know about consumers
- Scalability: Add consumers without modifying producers
- Monitoring: Per-subscriber statistics and health monitoring
- Reliability: Slow consumers don't block fast producers
- Frontend: The frontend is a single-page application built with React, Redux Toolkit, and Material-UI. It communicates with the backend using a socket.io connection for real-time updates, including decoded data display and live audio monitoring.
- Backend: The backend is a Python application built with FastAPI. It provides a REST API and a socket.io interface for the frontend. It manages worker processes, decoder lifecycle, and coordinates the pub/sub architecture for signal distribution.
- Workers: The worker processes are responsible for the heavy lifting. They perform tasks such as satellite tracking, SDR streaming, signal demodulation, data decoding (SSTV implemented, AFSK/LoRa in development), and antenna control. Workers use IQ Broadcaster and Audio Broadcaster for efficient multi-consumer signal distribution.
- FastAPI: A modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints.
- SQLAlchemy: The Python SQL Toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL.
- Skyfield: A modern astronomy library for Python that computes positions for the stars, planets, and satellites in orbit around the Earth.
- SGP4: A Python implementation of the SGP4 satellite propagation model.
- Socket.IO: A library for real-time, bidirectional, event-based communication.
- pyrtlsdr: A Python wrapper for the RTL-SDR library.
- SoapySDR: A vendor and platform neutral SDR support library.
- SatDump: Satellite decoder suite used for weather image decoding workflows.
- gr-satellites: GNU Radio out-of-tree modules for satellite communications decoding.
- React: A JavaScript library for building user interfaces.
- Redux Toolkit: The official, opinionated, batteries-included toolset for efficient Redux development.
- Material-UI: A popular React UI framework with a comprehensive suite of UI tools.
- Vite: A build tool that aims to provide a faster and leaner development experience for modern web projects.
- Socket.IO Client: The client-side library for Socket.IO.
- Leaflet: An open-source JavaScript library for mobile-friendly interactive maps.
- satellite.js: A JavaScript library to propagate satellite orbits.
Dedicated worker processes provide IQ acquisition, FFT processing, and demodulation support for multiple receiver families:
- RTL-SDR (USB or
rtl_tcp) workers - SoapySDR devices locally or through SoapyRemote: RTL-SDR, Airspy, HackRF, HydraSDR, LimeSDR, UHD/USRP, and SDRplay (RSP series)
- UHD/USRP radios via a UHD worker
- Need another SoapySDR device? Open a GitHub issue and request support.
The SDR architecture uses a pub/sub pattern (IQ Broadcaster) to separate IQ acquisition from signal processing:
- IQ Acquisition Workers stream raw samples to IQ Broadcaster
- IQ Broadcaster distributes to multiple subscribers independently:
- FFT Processor for spectrum/waterfall display
- Demodulators (FM/SSB/AM) for audio output in normal and internal modes
- IQ Recorder for SigMF format file capture
- Raw IQ Decoders (BPSK, GMSK) that bypass demodulation
- Audio Broadcaster distributes demodulated audio from internal demodulators to:
- Data Decoders (AFSK) for signal decoding
- UI Audio Stream for live monitoring in browser
Note: The signal processing components (demodulators, broadcasters, decoders) were developed with assistance from Claude AI (Anthropic) to handle complex DSP algorithms. These components are clearly marked in the source code and are licensed under GPL-3.0 like the rest of the project.
Ground Station includes comprehensive IQ recording and playback capabilities using the SigMF (Signal Metadata Format) standard:
- SigMF Format: Records IQ data as
.sigmf-datafiles with accompanying.sigmf-metaJSON metadata - Automatic Metadata: Captures center frequency, sample rate, timestamp, and recording duration
- Satellite Tracking: Automatically tags recordings with target satellite name and NORAD ID
- Waterfall Snapshots: Saves PNG snapshots of the waterfall display alongside recordings
- Multi-segment Support: Handles parameter changes (frequency, sample rate) as separate capture segments
- Real-time Monitoring: Live duration counter and visual recording indicator in the UI
- Virtual SDR Device: Recordings appear as "SigMF Playback" SDR in the device list
- Full Processing Pipeline: Playback supports FFT display, demodulation, and all signal processing
- Live-equivalent Decoding: During playback, demodulators and decoders run exactly as they do with live SDR input
- Recording Browser: Sortable list of recordings with metadata preview (sample rate, duration, timestamp)
- Seamless Integration: Switch between live SDR and playback without changing workflows
Ground Station includes an automated observation system for scheduled satellite passes:
- Monitored Satellites: Define satellite monitoring templates with hardware configurations, signal parameters, and task definitions.
- Automated Pass Scheduling: Automatically calculate and schedule upcoming passes based on configurable criteria (minimum elevation, lookahead window).
- Flexible Task Composition: Combine IQ recording (SigMF), audio recording, protocol decoding, and AI transcription in a single observation.
- Hardware Orchestration: Control SDR devices, antenna rotators (with satellite tracking), and rigs (with Doppler correction) during scheduled runs.
- Live Observation Capability: Watch the spectrum waterfall, listen to demodulated audio, and view live decoder output during automated passes.
- Multi-SDR Observing: Run automated observations on one SDR while additional SDRs record, decode, and listen to the same pass in parallel.
- Status Management: Track observation status (scheduled, running, completed, failed, cancelled, missed) with automatic cleanup of old entries.
- Session Management: Automated observations run in isolated internal VFO sessions (namespace: "internal:<observation_id>").
For development setup, build steps, and testing, see DEVELOPMENT.md.
The repository includes a multi-stage Dockerfile that builds the React frontend and a Python environment with SDR libraries.
docker build -t ground-station .
# Option 1: Standard bridge mode (works for local SDRs)
docker run --rm -p 7000:7000 --device /dev/bus/usb ground-station
# Option 2: Host networking (required for SoapySDR remote server discovery via mDNS)
docker run --rm --network host --device /dev/bus/usb ground-stationPre-built multi-architecture Docker images are available for each release. For detailed instructions on using a specific release, see the Releases page.
# Latest release tag (recommended)
docker pull ghcr.io/sgoudelis/ground-station:<version>
# Or pull architecture-specific tags directly
docker pull ghcr.io/sgoudelis/ground-station:<version>-amd64
docker pull ghcr.io/sgoudelis/ground-station:<version>-arm64Option 1: With SoapySDR Remote Server Discovery (Recommended)
Uses host networking to enable automatic mDNS discovery of SoapySDR remote servers:
# AMD64
docker run -d \
--platform linux/amd64 \
--network host \
--name ground-station \
--restart unless-stopped \
--device=/dev/bus/usb \
--privileged \
-v /path/to/data:/app/backend/data \
-e GS_ENVIRONMENT=production \
-e GR_BUFFER_TYPE=vmcirc_mmap_tmpfile \
ghcr.io/sgoudelis/ground-station:<version>
# ARM64 (Raspberry Pi, etc)
docker run -d \
--platform linux/arm64 \
--network host \
--name ground-station \
--restart unless-stopped \
-v /dev:/dev \
--privileged \
-v /path/to/data:/app/backend/data \
-e GS_ENVIRONMENT=production \
-e GR_BUFFER_TYPE=vmcirc_mmap_tmpfile \
ghcr.io/sgoudelis/ground-station:<version>Option 2: Standard Bridge Mode (No SoapySDR Remote Discovery)
Uses standard bridge networking with port mapping:
# AMD64
docker run -d \
--platform linux/amd64 \
-p 7000:7000 \
--name ground-station \
--restart unless-stopped \
--device=/dev/bus/usb \
--privileged \
-v /path/to/data:/app/backend/data \
-e GS_ENVIRONMENT=production \
-e GR_BUFFER_TYPE=vmcirc_mmap_tmpfile \
ghcr.io/sgoudelis/ground-station:<version>
# ARM64 (Raspberry Pi, etc)
docker run -d \
--platform linux/arm64 \
-p 7000:7000 \
--name ground-station \
--restart unless-stopped \
-v /dev:/dev \
--privileged \
-v /path/to/data:/app/backend/data \
-e GS_ENVIRONMENT=production \
-e GR_BUFFER_TYPE=vmcirc_mmap_tmpfile \
ghcr.io/sgoudelis/ground-station:<version>Important Notes:
- Replace
/path/to/datawith your desired data directory path - Option 1 (host networking) is required for automatic discovery of SoapySDR remote servers via mDNS
- Option 2 works for local SDRs and all other features
- For Raspberry Pi hardware, only the Raspberry Pi 5 is recommended
- For ARM64, using
-v /dev:/devensures all USB devices are accessible - Access the web interface at
http://<YOUR_HOST>:7000
We welcome contributions! Please see the CONTRIBUTING.md file for details on how to get started.
This project is licensed under the GNU GPL v3. See the LICENSE file for details.