Signals Intelligence Network Mapping and Analysis Training by Tonex
| FORMAT Instructor-led / customized |
LEVEL Intermediate to Advanced |
DELIVERY On-site or live virtual |
This course teaches analysts how to transform SIGINT observations into structured representations of communications and emitter networks. Participants learn methods for identifying nodes and relationships, developing link and temporal views, measuring network importance, tracking network change, and integrating technical, geospatial, and behavioral evidence. The course is designed to support intelligence assessments of network structure, activity, resilience, and operational significance while maintaining disciplined treatment of uncertainty and incomplete data.
Learning Objectives
- Construct network models from SIGINT-derived observations and metadata.
- Identify nodes, links, hubs, relays, communities, and recurring relationships.
- Apply graph and link-analysis concepts to prioritize analytically significant entities.
- Integrate temporal, geospatial, communications, and emitter data into network views.
- Detect network changes, anomalies, fragmentation, convergence, and reorganization.
- Communicate network findings using clear visualizations, confidence statements, and intelligence narratives.
Target Audience
SIGINT, COMINT, and ELINT analysts; all-source and network intelligence analysts; collection managers; ISR personnel; targeting and threat analysts; intelligence data scientists; and technical personnel responsible for link, relationship, or network analysis.
Course Modules
| 1. SIGINT network analysis concepts and analytic use cases | 8. Geospatial network analysis and movement context |
| 2. Entities, nodes, links, attributes, events, and relationship types | 9. Communications metadata and emitter characteristics as network evidence |
| 3. Data preparation, normalization, deduplication, and identity resolution | 10. Pattern-of-life, recurring relationships, and anomaly detection |
| 4. Building link charts and communications network models | 11. Network evolution, reorganization, degradation, and resilience |
| 5. Degree, centrality, density, path, and connectivity concepts | 12. Multi-INT enrichment and cross-source correlation |
| 6. Hubs, relays, brokers, bridges, clusters, and communities | 13. Analytic confidence, uncertainty, alternative interpretations, and reporting |
| 7. Temporal network analysis and activity timelines | 14. Capstone: build and brief a SIGINT-derived network map and assessment |