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MatrixSpace launches Fusion 360 multi-sensor drone detection system

MatrixSpace has expanded its portable drone detection portfolio with the launch of Fusion 360, a multi-sensor counter-drone system designed to combine radar, optical and RF/Remote ID data into a single operational view.

The company said Fusion 360 fuses data from multiple sensor types at the point of detection and tracking, with the aim of reducing false alarms and improving identification of small, low-flying or evasive drones in complex operating environments. These include public events, critical infrastructure sites and operational theaters.

According to MatrixSpace, the system is designed to distinguish between compliant or cooperative aircraft and so-called “dark drones” operating without Remote ID or RF signatures. The company describes Fusion 360 as a fusion-native system, meaning sensor correlation occurs at the edge before information is presented to operators.

“We take a radar and AI-first approach to low airspace awareness, resulting in a much higher quality output for users,” said Matt Kling, VP and General Manager, AI Systems, MatrixSpace. “Fusion 360 replaces a typically siloed approach, which is costly and misses critical drone activities. Our customers require a fail-safe, flexible, affordable solution, without wasting time on false threats.”

MatrixSpace said the system is portable and scalable, allowing users to deploy, relocate or network units as coverage requirements change. It is also designed to integrate into existing counter-UAS and security systems through open interfaces.

The Fusion 360 system is powered by the company’s MatrixSpace AI Platform, which applies contextual analysis, such as behavior, compliance status and airspace rules, to sensor data to determine threat relevance.

In addition to Fusion 360, MatrixSpace is offering Portable 360, a radar-only configuration intended to provide low-altitude airspace awareness across a range of applications.

RELATED CONTENT: MatrixSpace unveils updated AI platform for multi-sensor drone detection

Post Image Credit: Jason Leem via Unsplash

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