What is battlefield data fusion software?
Battlefield data fusion software correlates and synthesises intelligence from multiple heterogeneous sources — ISR sensors, HUMINT reports, SIGINT intercepts, OSINT feeds, GEOINT imagery, and logistics streams — into a single coherent operational picture. It implements the JDL Data Fusion Model (levels 1–5) to transform raw sensor readings into object refinement, situation assessment, threat assessment, and process refinement. The output drives CCIR and PIR tracking for commanders at brigade, division, and HQ level across C4ISR environments.
Which data sources can you fuse together?
We have built pipelines integrating ISR drone feeds, infantry position reports, artillery fire-mission data, EW and SIGINT intercepts, HUMINT CRM-style entries, OSINT scrapers, GEOINT satellite imagery, AIS/ADS-B transponder data, and logistics management system exports. Our connector library supports REST, MQTT, Kafka, Delta Lake, FTP batch drops, and classified file-transfer protocols. Multi-level security requirements are addressed through attribute-based access control and compartmented data flows.
Do you implement JDL data fusion levels?
Yes. We implement all five JDL levels: Level 1 (object refinement — track association and state estimation), Level 2 (situation refinement — spatial and temporal correlation to build a situational picture), Level 3 (threat assessment — adversarial intent and consequence analysis), Level 4 (process refinement — adaptive sensor tasking and collection management), and Level 5 (user refinement — feedback loops that tune fusion parameters based on analyst decisions). Our Corvus.Head dashboard presents the fused picture from levels 1–3 to commanders and analysts in real time.
Can you handle classified multi-level security?
We design all-source intelligence systems with multi-level security (MLS) architectures from the outset. This includes attribute-based access control (ABAC) aligned to classification levels, data-tagging at ingestion, compartmented Kafka topics with per-topic ACLs, and audit logging for all data access events. We work under NDA with your security architects to ensure the solution meets your classification requirements, whether SECRET, NATO CONFIDENTIAL, or mission-specific handling caveats.
What technologies do you use for battlefield data fusion pipelines?
We build data fusion pipelines using Apache Kafka and Flink for real-time event streaming, Python and C++ for fusion algorithm implementations, PostGIS and TimescaleDB for geospatial and time-series storage, and containerised services on Kubernetes. Message formats follow NATO STANAG standards including ADatP-3, MIP, and NFFI where required.
How do you handle conflicting data from multiple sensors?
We implement sensor reliability weighting and conflict resolution logic based on source fidelity, recency, and confidence scores. Dempster-Shafer evidence theory and Bayesian fusion approaches are applied to produce fused assessments with quantified uncertainty, rather than silently discarding conflicting signals.
Can data fusion systems support cross-domain joint operations?
Yes. We design data fusion architectures that aggregate and correlate data across operational domains — land, air, maritime, space, and cyber — enabling a joint common operational picture. Cross-domain fusion requires careful handling of classification levels and information sharing agreements, which we scope during the requirements phase.
What is a cross-domain solution (CDS) and do you support it?
A cross-domain solution enables controlled information transfer between networks at different security classification levels. Corvus Intelligence designs data fusion architectures with CDS integration points in mind, ensuring that data flows between classification domains comply with applicable security policy and accreditation requirements.
Do you offer integration with existing intelligence platforms?
Yes. We integrate data fusion pipelines with existing intelligence platforms including OSINT aggregators, ISR management systems, and national-level C2 architectures. Integration work typically involves developing adapters for non-standard data formats, building normalisation layers, and establishing secure API contracts between systems.
How do we start a data fusion development project with Corvus?
Contact us with a description of your data sources, fusion objectives, and operational requirements. We begin with a data architecture review to assess current state and define the fusion pipeline design. Use the contact form below or reach us at contact@corvusintell.com.