TRUSTED BY INDUSTRY LEADERS

>10kHz

Sampling rate

>140dB

Dynamic range

<1ms

End-to-end latency

4x5mm

GenX320 camera module

0.13g

GenX320 camera module

<2mW

Sensing power / 16uW standby mode GenX320

MULTIMODAL RGB-EVS DRONE DETECTION

This study explores drone detection using event cameras, focusing on three fusion strategies: pooling-based, asymmetric modality injection, and symmetric fusion.

Results show that event-based models outperform RGB alone, but combining both enhances performance by overcoming their individual limitations.

GPS-DENIED DRONE NAVIGATION

Current GPS systems are vulnerable to interference from large buildings, dense foliage, extreme weather or signal jamming.

EVS outputs a real-time terrain fingerprint for the particular patch of land the vehicle is passing over. This is then compared against a database of terrain fingerprints generated from satellite imagery, which is stored on the vehicle.

1/ Enable GPS-denied navigation capability for low-cost drones: low data rate + low power

2/ Enable accurate long distance/time travel: Cancels position gradual drift through real-time EVS terrain fingerprints

MULTIMODAL SENSING PLATFORM

Prophesee’s event-based Metavision sensors, integrated into the Cambrian M-Series multimodal sensing platform, revolutionize imaging with low-latency performance and microsecond-precision object tracking.

By capturing only scene changes at the pixel level, they drastically enhance energy efficiency, handle challenging lighting with exceptional dynamic range, and reduce data output for real-time analytics.

DRONE DETECTION PLATFORM

Neurobus revolutionizes onboard surveillance with cutting-edge neuromorphic technology, combining event-based cameras and processors inspired by the human brain.

Thanks to ultra-low latency (<1 ms), minimal energy consumption, and intelligent onboard processing, our solutions ensure instant detection and tracking, even in extreme conditions.

AI-BASED TARGET RECOGNITION

Flysight uses Prophesee event cameras for AI-based target recognition in challenging scenarios such as persons or drones evolving in low light, camouflaged or over complex background.

In this work, they managed to cut time to first detection from 12 to 2 seconds using Prophesee sensors in a challenging scenario involving camouflaged personnel detection

DRONE OBSTACLE AVOIDANCE

Vision-based autonomous flight in unknown environments is difficult in part due to sensor limitations of traditional onboard cameras.

Event cameras, however, promise nearly zero motion blur and high dynamic range. By leveraging depth prediction, the team pre-trained a reactive obstacle avoidance policy and achieve high-speed obstacle avoidance in indoor and outdoor settings.

ASYNCHRONOUS LASER PULSE DETECTION

Detect, localize and decode multiple laser impulsions simultaneously, in real time, following STANAG 3733 compliance.

– Infrared lasers compatibility
– Code identification following STANAG 3733
– Improved laser impulsions localization precision
– Simultaneous multiple designation detection

SPACE SITUATIONAL AWARENESS

Astrosite, a world first neuromorphic-inspired mobile telescope observatory developed by the International Centre for Neuromorphic Systems (ICNS) at Western Sydney University is using Prophesee Event-Based sensing as a more efficient and low-power alternative for Space Situational Awareness.

140dB Dynamic Range enabling day/night operations

High-Speed µs temporal resolution for spacecraft / satellite / debris tracking and identification

Low-bandwidth communication: 10 to 1,000x less data

SPACE-BASED OBSERVATION

Event-based sensors have many attractive characteristics for space flight applications. These include very low size, weight, power as well as bandwidth.

Falcon ODIN is a breakthrough space experiment leveraging Prophesee HD sensor, designed to observe both natural phenomena (lighting and sprites) as well as man-made objects on the ground, sea, air and space.

FIND OUT WHAT PROPHESEE METAVISION® TECHNOLOGIES CAN BRING TO YOUR DEFENSE AEROSPACE PROJECTS

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