How do I set up an RF sensing software stack for real-time operator alerting at a base security team?

I can help with a defensive, site-security-oriented RF sensing stack for real-time alerting. I’ll keep this focused on passive detection, triage, and operator awareness rather than offensive use.

1) Define the mission

For a base security team, the stack should answer:

• What RF activity is present?
• Where is it coming from?
• Is it unusual or policy-violating?
• Should an operator be alerted now?

Typical monitored phenomena:

• Unauthorized radios / transmitters
• Drone-control links and telemetry
• Rogue Wi‑Fi / hotspots
• Suspicious Bluetooth activity
• Jammers / wideband interference
• Unexpected repeater / relay activity
• Spectrum occupancy anomalies near sensitive areas

2) Recommended architecture

A practical stack usually has 5 layers:

A. RF sensors

Use a mix of:

• Wideband SDRs for spectrum monitoring
• Specialized sensors for Wi‑Fi/Bluetooth/ISM bands
• Optional direction-finding units if you need geolocation

Examples of sensor capabilities:

• 24/7 IQ capture
• Energy detection / FFT scans
• Triggered burst capture
• GPS-disciplined timing
• Network-synchronized time stamps

B. Edge processing node

Each sensor should feed an edge box that handles:

• Sample ingestion
• FFT / waterfall generation
• Detection logic
• Feature extraction
• Local buffering for short-term raw capture
• Health monitoring

This keeps latency low and reduces bandwidth to the server.

C. Central analytics and correlation

A central service should:

• Merge alerts from all sensors
• Correlate by frequency/time/location
• De-duplicate repeated events
• Classify events by severity
• Maintain historical baselines

D. Alerting and operator interface

Operators need:

• Live event feed
• Spectrum/waterfall view
• Map or zone visualization
• Confidence/severity indicators
• One-click acknowledge/escalate
• Incident notes and timestamps

E. Evidence and logging

Store:

• Event metadata
• Short pre/post-trigger IQ snippets
• FFT snapshots
• Operator actions
• Sensor health data

3) Software components

A solid defensive stack can be built from these building blocks:

Data capture

• GNU Radio: flexible DSP pipelines
• SoapySDR / UHD: device abstraction and driver support
• SigMF: standard format for IQ metadata + samples

Signal processing

• FFT/waterfall generation
• Energy detection
• Cyclostationary / modulation features if needed
• Burst detection
• Occupancy statistics
• Baseline anomaly detection

Backend

• Message bus: MQTT, NATS, or Kafka
• API server: FastAPI or Go
• Database: PostgreSQL for events, TimescaleDB if you want time-series
• Object storage: S3-compatible for raw captures

UI / dashboard

• Web app with:
  • live spectrum
  • event timeline
  • sensor status
  • alert queues
• Visualization: Plotly, Grafana, or custom React frontend

Alerting integration

• PagerDuty / Opsgenie / email / SMS / Teams / Slack
• Support rules like:
  • “Jammer-like wideband rise above threshold”
  • “New transmitter in restricted band”
  • “Drone-link signature detected within perimeter”
  • “Persistent unknown signal > X minutes”

4) Data flow

A good real-time pipeline:

1. Sensor scans spectrum continuously
2. Edge node detects an anomaly
3. Edge node captures:
   • event metadata
   • short IQ buffer before/after
   • FFT snapshot
4. Event published to message bus
5. Central service scores and correlates event
6. Alert engine decides:
   • ignore
   • log only
   • notify operator
   • escalate immediately
7. Dashboard updates in real time

5) Alert logic

Use a mix of deterministic rules and anomaly scoring.

Rule-based triggers

Examples:

• Signal appears in a prohibited band
• Persistent emission near a protected zone
• Sudden increase in noise floor
• Known jammer-like broadband energy
• New device MACs / BLE advertisers in restricted area

Scoring model

Assign each event a score using:

• Band risk
• Signal strength
• Duration
• Novelty vs baseline
• Proximity to sensitive areas
• Sensor confidence
• Multi-sensor confirmation

Then alert on thresholds like:

• 0–39: log
• 40–69: notify
• 70+: urgent alert

6) Deployment best practices

Placement

• Put sensors at vantage points covering perimeter and critical zones
• Overlap coverage to allow cross-confirmation
• Keep antennas documented and fixed
• Use GPS/time sync if comparing across sites

Security

• Isolate RF sensor network from business IT
• Use device certificates and mTLS
• Signed updates
• Restrict raw capture access
• Audit every operator action

Performance

• Precompute common FFT sizes
• Use ring buffers for burst capture
• Compress or decimate where appropriate
• Keep latency from detection to alert under a few seconds

7) Minimal reference stack

If you want a pragmatic starting point:

• Sensors: SDRs with wideband antennas
• Edge: Linux mini-PC per sensor
• Capture: SoapySDR/UHD + GNU Radio
• Metadata format: SigMF
• Transport: MQTT or NATS
• Backend: FastAPI + PostgreSQL
• Time-series: TimescaleDB
• Dashboard: Grafana + custom web UI
• Alerts: PagerDuty / SMS / email
• Storage: S3-compatible object store

8) Example operational workflow

1. Operator logs into dashboard.
2. Live spectrum shows normal baseline.
3. A new wideband emission appears near a protected zone.
4. Edge node captures 10 seconds of IQ around the event.
5. Correlation engine confirms the same signal on two sensors.
6. Alert is raised with confidence and location estimate.
7. Operator acknowledges and dispatches physical security team.
8. Incident record is archived with evidence.

9) Questions to answer before design

To recommend a concrete stack, I’d need:

• Frequency bands of interest
• Area size and sensor count
• Required detection latency
• Whether you need geolocation
• Whether you need raw IQ capture or metadata only
• Existing infrastructure constraints
• Preferred alert channels
• Expected operator workload

If you want, I can next provide either:

1. a reference architecture diagram,
2. a component-by-component software bill of materials, or
3. a sample event schema and alert ruleset for the stack.