📡 RF Lord — RF Spectrum Monitor

Real-time RF spectrum monitoring with drone detection, voice alerts, and signal analysis. Built for HackRF One and RTL-SDR.

Author: Ihor Kolodyuk

Features

• Live spectrum table — split-screen: suspicious left, known signals right, grouped by type
• Signal grouping — same-type signals merged with count, strongest power, nearest distance
• Drone detection — 45 RF signatures (DJI OcuSync/O3/O4, HDZero, Walksnail, ELRS, Crossfire, analog FPV)
• Voice alerts — TTS HAL 9000 voice with signal type + distance announcements
• Signal classification — Artemis 3 database (432 signatures) + spy database (47) + drone database (45)
• Suppress mode — HackRF TX jammer for Cellular, Bluetooth, GPS (hotkey: s)
• Distance estimation — FSPL-based distance calculation per signal type
• Instant hotkeys — background key listener thread for q/r/m/v/s/+/- (no scan delay)
• RTL-SDR support — auto-detects HackRF or RTL-SDR, adapts scan method
• Voice decoding — DSD (DMR, D-STAR, NXDN), multimon-ng (POCSAG, DTMF, Morse)
• Duty scan mode — continuous monitoring with configurable interval

Quick Start

# Install dependencies
sudo apt-get install -y hackrf rtl-sdr dsdcc multimon-ng sox
pip3 install edge-tts numpy

# Clone
git clone https://github.com/ihorman/rflord.git
cd rflord

# Run the monitor
python3 rflord.py

# Or with custom interval
python3 rflord.py --interval 60

Usage

Clean Table Monitor (rflord)

# Default — full scan, 120s interval, voice alerts
python3 rflord.py

# Faster updates
python3 rflord.py --interval 60

# Install as system command
sudo cp rflord.py /usr/local/bin/rflord
sudo chmod +x /usr/local/bin/rflord
rflord --interval 60

Full Scanner (scanner.py)

# Single scan with full report
python3 scanner.py --focus full

# Camera-focused scan (900 MHz, 1.2 GHz, 2.4 GHz, 5.8 GHz)
python3 scanner.py --focus cameras

# Continuous duty monitoring
python3 scanner.py --duty --interval 120

# Specific frequency range
python3 scanner.py --band 2400:2500

# Force device
python3 scanner.py --device hackrf
python3 scanner.py --device rtlsdr

Voice Decoder

# Decode voice at frequency
python3 voice_decode.py scan 155.0         # Auto-detect mode
python3 voice_decode.py scan 130.0 --mode am   # AM (air band)
python3 voice_decode.py scan 446.0 --mode dmr  # DMR digital
python3 voice_decode.py scan 446.0 --mode pocsag  # POCSAG pagers

FPV Video Decode

# Capture and decode FPV video
python3 fpv_decode.py capture --freq 5800 --standard NTSC --output frame.png
python3 fpv_decode.py capture --freq 1280 --standard PAL --spectrogram --output frame.png

Color Coding

Color	Meaning
🔴 RED	Top 3 strongest suspicious signals
🟡 YELLOW	Other suspicious signals
🟢 GREEN	Known/identified signals
🟣 MAGENTA	Drone activity detected
⚡ CW	Continuous carrier (possible beacon)

Signal Types

Code	Description
DP/USB	DisplayPort/USB interference harmonic
USB-noise	USB 2.0 clock noise (480 MHz harmonics)
DAB	Digital Audio Broadcasting
CW	Continuous wave carrier
TETRA	Public safety radio
WiFi/BT	WiFi or Bluetooth
Digital	Digital modulation (bursty)
Analog	Analog signal

Architecture

rflord.py          — Clean table monitor (main UI)
scanner.py         — Full scanner with detailed reports
drone_rf_db.py     — Drone RF signature database (45 signatures)
drone_dsp.py       — Drone signal DSP analysis (OFDM detection)
voice_decode.py    — Voice decoder (DSD + multimon-ng)
rf_analysis.py     — Distance estimation + territory classification
fpv_decode.py      — FPV video frame decoder
tv_capture.py      — TV frame capture (analog + digital)

Dependencies

• Hardware: HackRF One or RTL-SDR
• System: hackrf_transfer, rtl_sdr, rtl_power, dsdccx, multimon-ng, sox, aplay/paplay
• Python: numpy, edge-tts
• Audio: PipeWire or PulseAudio

How It Works

1. Scans all RF bands using hackrf_sweep (1 MHz - 6 GHz)
2. Classifies each signal against known databases
3. Identifies drone activity using 45 RF signatures
4. Estimates distance using Free-Space Path Loss
5. Classifies territory (city/suburban/countryside)
6. Captures IQ samples for deeper analysis
7. Tries voice decode (DSD, multimon-ng) on narrowband signals
8. Announces findings via TTS voice alerts

Detection Capabilities

• Drones: DJI OcuSync/O3/O4, HDZero, Walksnail, ELRS, Crossfire, TBS Tracer, FrSky, Spektrum
• Analog video: NTSC/PAL FPV transmitters (900 MHz, 1.2 GHz, 2.4 GHz, 5.8 GHz)
• Digital voice: DMR, D-STAR, dPMR, YSF, NXDN, P25
• Data: POCSAG, FLEX, EAS, DTMF, Morse, AFSK
• Cellular: GSM 900/1800, 3G, 4G LTE
• Broadcast: FM, DAB, DVB-T

Limitations

• WiFi IP cameras are indistinguishable from normal WiFi traffic
• Cameras recording locally have no RF emission
• DJI drones use encrypted video — cannot decode content
• Narrowband signals (<50 kHz) are not video transmitters
• 900 MHz band is GSM cellular in most locations

License

MIT

Author

Ihor Kolodyuk