DRAIDIS Use Case

Combine acoustic, EO/IR, and RF observations for operator-reviewed UAS alerts

The Challenge

Small unmanned aerial systems (sUAS) create fast-changing detection challenges. Sensor coverage, environmental noise, terrain, weather, target profile, and operator workflow all affect how reliably a system can detect and classify an event.

Single-sensor C-UAS designs can create coverage gaps: RF performance depends on detectable emissions, acoustic performance can degrade in high noise, and EO/IR performance can degrade with weather, occlusion, or lighting.

Large or operator-intensive counter-UAS configurations may be difficult to distribute across forward positions, creating a need for modular deployment options.

Single-sensor nuisance detections can contribute to alarm fatigue; actual false-alarm performance varies by sensor, dataset, threshold, and operating environment.

Alert and response timelines depend on sensor placement, compute, network conditions, integration, rules of engagement, and the human decision path.

How DRAIDIS Solves It

DRAIDIS ALPHA brings selected acoustic, EO/IR, and RF observations into one local workflow and presents candidate UAS alerts in ATAK. Operators confirm identification and decide the response. During the pilot, your team measures detection, false-alert, classification, and latency results with mission-representative targets, terrain, weather, sensors, and test data your team selects. Your team also decides whether operating data may be used to evaluate or improve a model.

Acoustic Observation

Use a selected microphone array to surface possible propeller signatures and estimate an initial bearing for operator review.

RF Observation

Use a selected software-defined radio and mission-defined scan plan to surface possible UAS control or telemetry activity.

Sensor Fusion

Compare acoustic and RF observations, show where they agree or conflict, and build a candidate track with confidence for each source.

Visual Confirmation

Cue a configured EO/IR camera within the safety limits your team sets. Vision models present possible contact and type classifications for operator confirmation.

Threat Assessment

Compare the observations with the threat library your team selects, then present possible categories, confidence, and evidence for review.

ATAK Alert

Send a candidate alert to configured ATAK clients with location, possible classification, confidence, evidence, and a recommended next step.

Track Update

Update the candidate track as new observations arrive and show operators which sensors currently support it.

Operator Handoff

Format reviewed detection data for a downstream system selected by the program. Operators retain positive-identification and response authority.

Deployment Configuration

This use case deploys on a single DRAIDIS tier.

Portable

DRAIDIS ALPHA

Backpack-portable design for dismounted patrols, observation posts, and temporary defensive positions. Select the sensors, compute, power, and enclosure for the mission, then test the complete configuration.

Key Capabilities

Purpose-built AI capabilities for this mission set.

Three-Sensor Correlation

Compare acoustic, RF, and EO/IR observations and show conflicting classifications for operator review.

Alert-Latency Testing

Measure sensor-to-alert latency with the selected sensors, models, compute, interfaces, thresholds, and field conditions.

Local Classification Library

Manage the selected UAS signature library locally and control how updates reach the node.

Multi-Target Tracking

Present possible coordinated movement across multiple candidate tracks for operator review.

Passive Sensor Options

Use acoustic and EO/IR inputs when the mission calls for a passive sensing posture.

Detection Evaluation

Measure false-alert and missed-detection rates on representative mission data before field use.

Performance Metrics

Measure

Sensor-to-alert latency

Test

Mission classification quality