[Developers]

Effector Matching Engine

An acoustic sensor network triangulates an enemy artillery position. The grid reference is confirmed, the classification is hostile, and the command post needs engagement options in the next two minutes before the batter

Category: ModulesLast Updated: Apr 2, 2026
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Overview#

An acoustic sensor network triangulates an enemy artillery position. The grid reference is confirmed, the classification is hostile, and the command post needs engagement options in the next two minutes before the battery relocates. The Effector Matching Engine does in seconds what a fire support coordinator would spend ten minutes doing manually: it queries all available effectors, scores each one against the target across range, type suitability, readiness state, ammunition availability, terrain line-of-sight, collateral risk, and time-to-effect, then presents a ranked list of options with the scoring rationale visible at each step.

The engine automates the process of pairing detected targets with available engagement assets. When a target is confirmed from any sensor source (GMTI radar, acoustic triangulation, video analytics, or OSINT), it evaluates all available effectors and produces a ranked engagement option list. The system supports the full engagement workflow from proposal through confirmation, execution, and battle damage assessment, maintaining a complete audit trail throughout.

Open Standards#

  • GraphQL (June 2018 specification): The full API surface, asset registration, target ingestion, matching, assignment lifecycle, BDA capture, and real-time subscription streams, is exposed exclusively through a typed GraphQL schema with queries, mutations, and subscriptions.
  • WGS 84 (EPSG:4326): All effector and target positions are stored and processed as WGS 84 decimal-degree coordinates; range feasibility scoring applies the Haversine formula against the WGS 84 Earth radius.
  • STANAG 4607 Ed. 3 (Ground Moving Target Indicator): GMTI radar tracks decoded from STANAG 4607 packets are accepted as a native target source type, allowing counter-battery and GMTI-cued engagements without manual re-entry.
  • STANAG 4774 Ed. 1 (Confidentiality Metadata Label Syntax): Every effector asset, target detection, and assignment record carries a NATO classification label (UNCLASSIFIED, NATO_RESTRICTED, SECRET, etc.) that gates per-subscriber visibility on real-time subscription channels and enforces mandatory confirmation before execution.
  • Link 16 (STANAG 5516 / MIL-STD-6016): Link 16 tactical data-link tracks are a declared source type for target detections, enabling air-picture and surface-track data to flow directly into the matching engine from JTIDS/MIDS terminals.
  • JC3IEDM (NATO MIP / STANAG 5525): Confirmed effectors and active targets are emitted to the shared MDOC operational-picture store as JC3IEDM-aligned operational entities, making them available on the common operating picture workspaces (cop, isr-fusion).
  • ISO 8601: All temporal fields, detection timestamps, engagement start/end times, and audit-log entries, are stored and exchanged as ISO 8601 UTC-offset timestamps (TIMESTAMPTZ).

Last Reviewed: 2026-04-02 Last Updated: 2026-04-14

Key Features#

Multi-Factor Scoring#

Each candidate effector is scored against the target using configurable weighted factors: range feasibility (can the effector reach the target), type match (is the effector appropriate for the target category), readiness state (is the effector available and operational), ammunition availability (does the effector have suitable munitions), line-of-sight feasibility (informed by terrain analysis), risk assessment (collateral damage estimation and friendly force proximity), and time-to-effect (how quickly the effector can engage). The composite score ranks all options for the operator.

Configurable Doctrine Weights#

Scoring weights are configurable per tenant organisation, allowing different forces to encode their doctrine and rules of engagement into the matching algorithm. A force prioritising minimal collateral damage increases the risk weight; a force in a high-intensity scenario may prioritise time-to-effect. Weight profiles can be saved and switched based on operational phase.

Engagement Workflow#

The engagement lifecycle follows a structured workflow: Propose (engine generates ranked options), Confirm (operator selects and authorises an engagement), Execute (engagement is initiated and tracked), Assess (battle damage assessment is recorded). Each state transition is logged with operator identity, timestamp, and justification. The workflow enforces mandatory confirmation before execution, preventing automated engagement without human authorisation.

Battle Damage Assessment#

After engagement execution, the system captures BDA data including observed effect, target status (destroyed, damaged, functional, unknown), assessment source (sensor, visual, report), and confidence level. BDA results feed back into the operational picture, updating target status and informing follow-on engagement decisions.

Multi-Source Target Ingestion#

The engine accepts targets from all platform sensor sources: GMTI radar tracks, acoustic triangulation fixes, video analytics detections (including high-value target classifications), OSINT-derived locations, and manually reported positions. Each target retains its source provenance through the engagement lifecycle.

Use Cases#

  • Fire Support Coordination: Rapidly match detected targets to available fire support assets across artillery, mortar, air support, and direct fire systems, presenting commanders with ranked engagement options.
  • Air Defence: Match detected aerial threats (drones, aircraft) to available air defence systems based on range envelope, engagement altitude, and missile availability.
  • Counter-Battery: Receive acoustic-triangulated enemy artillery positions and immediately generate counter-fire options ranked by response time and available ammunition.
  • Joint Fires: Coordinate engagement across multiple force elements by evaluating effectors from different units against shared target lists, deconflicting engagements to prevent duplication.
  • Post-Action Review: Review complete engagement chains from initial detection through BDA, supporting lessons-learned analysis and doctrine refinement.

Integration#

  • Acoustic Sensor Network: Receives triangulated source locations as engagement targets.
  • GMTI Radar Monitoring: Receives confirmed radar tracks as engagement targets.
  • Military Video Analytics: Receives high-value target detections with geocoded positions.
  • Terrain Analytical Modelling: Queries line-of-sight and elevation data for engagement feasibility assessment.
  • Unified Operational Events: All engagement workflow transitions generate events in the unified timeline.
  • Drone Operations Management: Drone assets are included as candidate effectors when armed UAS are available.

GraphQL: effectorAssets, targetDetections, effectorAssignments, effectorStats (queries); registerEffectorAsset, updateEffectorStatus, updateEffectorPosition, ingestTargetDetection, matchTarget, confirmAssignment, rejectAssignment, startEngagement, completeEngagement (mutations).

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