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Distributed Dual-Mode Mesh Radar for Base Defense

AFWERX · AFWERX TACFI · AFWERX

AI-Readiness Score
18/25
Pathway Speed
4/5
Timeline Realism
3/5
Problem Framing
4/5
AI / ML Fit
4/5
Award + Transition
3/5

Award

$1,899,796
Award ceiling
MATRIXSPACE, INC
Awardee
Posted July 1, 2024

Description

The current Ukraine-Russia conflict reveals, along with  recent attacks in Jordan, that drones have fundamentally changed today’s battlespace and the future of warfare. Now, thousands of low-cost UAS systems are being deployed with incredible effects and have quickly become indispensable to both sides of the conflict. Air bases, critical infrastructure and personnel, both abroad and domestic, are facing increased threat from UAS surveillance and/or attack. There have been a large number of UAS detection and tracking systems and counter-small UAS (C-sUAS) systems developed in recent years. Yet most of these systems are very large, very expensive, not scalable, and are not designed to be rapidly or easily transported, setup or operated . Many of these systems are also ill suited to support the Agile Combat Employment (ACE) scheme of maneuver. To enable ACE doctrine to increase survivability while generating combat power, sensors and systems must allow scalable coverage, be easily transported, setup and operated by Expeditionary Defenders and other Multi-Capable Airmen. The systems must also be capable of operating in all categories of Enduring and Contingency Locations and in all phases of operations.  To support these types of operations, MatrixSpace proposes in this TACFI Sequential Phase II effort, a prototype UAS Tracking System that is small, lightweight, scalable, easy to transport, quick to setup, easy to operate and able to operate 24x7 using battery and solar power. Combining these scalable and expeditionary capabilities along with tracking both ground and air targets, enhanced UAS Tracking capabilities is in alignment with the Secretary of the Air Force’s (SECAF) operational imperative of achieving tactical air dominance, moving target engagement and operationally focused Advanced Battle Management System (ABMS). The scope of work for this TACFI effort involves scaling MatrixSpace’s DopplerSpace radar for use in tactical, expeditionary, installed base force protection scenarios by creating a scalable “Low-Cost Distributed Radar Sensor Mesh” for low-airspace surveillance. The sensor mesh will detect, track, and identify low flying objects such as UAVs, loitering munitions, and one-way attack vehicles that are RF silent. The effort will focus on three lines of effort: Developing and enhancing the c-UAS radar sensor mesh and integrating proprietary MatrixSpace algorithms for target classification, deploying a full system to Joint Base McGuire-Dix-Lakehurst, and demonstrating the system’s performance against selected relevant UAS. These efforts may occur sequentially or in parallel as the contract successfully executes.

Score Rationale

TACFI is a strong modern fast-track instrument (not quite a 5 because it's a Sequential Phase II continuation rather than a fresh open competition), and the problem is well-bounded with a named test site (JB MDL), clear threat class (RF-silent UAS/loitering munitions), and explicit operational doctrine alignment — losing one point because response deadline is unknown and transition pathway beyond this prototype award is only implied. AI/ML fit is genuine — Doppler radar target classification, multi-target tracking, and identity discrimination against low-observable UAS are real ML-shaped problems with sensor data pipelines — but the award ceiling (~$1.9M) sits just above the $1M floor without an explicit named production follow-on, anchoring award_transition at a 3.

Source

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