CLI Reference

CLI Reference

The spectrum-alert console entry point remains fully supported. It uses the same configuration, detector and data directory as the web dashboard.

spectrum-alert --help
spectrum-alert <command> --help

Command groups

Command	Purpose
version	Show version information
web	Start the web dashboard
monitor	Start, inspect and automate spectrum monitoring
train	Train a model from stored feature data
system	Host metrics and health
geo	Receiver roster, scanning, calibration and triangulation
config	Configuration command group

Monitoring

# Current receiver and system state
spectrum-alert monitor status

# Live scan
spectrum-alert monitor start --freq-start 144 --freq-end 148 --mode full

# Timed scan
spectrum-alert monitor start --freq-start 430 --freq-end 440 \
  --duration 300 --sample-rate 2.048 --gain 20

# Detection tuning
spectrum-alert monitor start --freq-start 144 --freq-end 148 \
  --threshold 0.8 --strict-threshold \
  --dc-exclude-hz 8000 --edge-exclude-hz 20000 \
  --novelty --novelty-cooldown-s 5

Common options:

Option	Meaning
--freq-start, --freq-end	Scan range in MHz
--mode full|lite	Detection feature set
--duration	Stop after this many seconds
--sample-rate	Receiver sample rate in MS/s
--gain	Tuner gain in dB
--threshold	Anomaly threshold, 0 to 1
--strict-threshold	Require stronger SNR for borderline scores
--dc-exclude-hz	Ignore the LO/DC region
--edge-exclude-hz	Ignore Nyquist-edge artefacts
--novelty	Suppress repeat alerts for stable signals

Autonomous operation

# Continuous single band
spectrum-alert monitor autonomous --freq-start 144 --freq-end 148 \
  --continuous-learning

# Rotate between bands
spectrum-alert monitor autonomous-multiband \
  -b 144-148 -b 430-440 \
  --data-minutes 5 --monitor-minutes 15

# Finite number of rotations
spectrum-alert monitor autonomous-multiband \
  -b 144-148 -b 430-440 --rounds 3

Training

# Train a full-feature model using the last seven days
spectrum-alert train models --mode full --days 7

# Train a lite model
spectrum-alert train models --mode lite --days 3

Training reads data/features/*_<mode>.csv, requires at least ten usable rows, and writes model artifacts under models/. The web Training panel exposes the same operation with additional model types and deployment controls.

System

spectrum-alert system status

Reports CPU, memory, disk and receiver availability.

Geolocation

# Receiver roster
spectrum-alert geo receivers

# Add a local receiver
spectrum-alert geo add-receiver Home --lat 35.130 --lon 33.310 \
  --gain 30 --ppm 20

# Add a remote rtl_tcp receiver
spectrum-alert geo add-receiver Hill --lat 35.080 --lon 33.380 \
  --mode rtltcp --host 10.0.0.5 --port 1234

# One scan
spectrum-alert geo scan 446100000 --span 200000 -i 0.5

# Locate an emitter
spectrum-alert geo triangulate 446100000

# Calibration
spectrum-alert geo calibrate
spectrum-alert geo calibrate --apply

# Fit path-loss exponent
spectrum-alert geo fit-ple

Triangulation needs at least two enabled receivers with coordinates. Two receivers produce an underconstrained fix; three or more give a usable estimate.

Web

spectrum-alert web --host 0.0.0.0 --port 8000

The default dashboard port is 8000. The compose file maps host port 8088 to it.

Terminal and GUI together

The two interfaces can share data. A typical workflow:

1. Collect captures from the CLI.
2. Open the dashboard and review them under Config → Data Management.
3. Train or evaluate a model under Training.
4. Use the workspace for locating and identification.

A physical dongle cannot be open in two processes at once. Stop dashboard monitoring before starting a CLI scan on the same device.

Related

• Quick Start
• Web Dashboard
• Docker
• Troubleshooting