The US Air Force Research Laboratory (AFRL) has granted a $1.8m development contract to BrainChip Holdings for advancing neuromorphic radar signal processing technologies.
This contract titled ‘Mapping Complex Sensor Signal Processing Algorithms onto Neuromorphic Chips’, comes through the Small Business Innovation Research programme.
Go deeper with GlobalData
It builds upon a prior phase where BrainChip demonstrated radar processing algorithms on its Akida neuromorphic hardware.
BrainChip CEO Sean Hehir said: “Radar signalling processing will be implemented on multiple airborne and mobile platforms, so minimising system SWaP-C is critical.
“The contract to improve radar signalling applications for Air Force Research Laboratory highlights how neuromorphic computing can achieve significant benefits of low-power, high-performance compute in the most mission-critical use cases.
“This award is a very strong endorsement from leading organisations such as AFRL for our groundbreaking Akida hardware and state-space AI models using Temporal Enabled Neural Network (TENNs) model offerings.”
How well do you really know your competitors?
Access the most comprehensive Company Profiles on the market, powered by GlobalData. Save hours of research. Gain competitive edge.
Thank you!
Your download email will arrive shortly
Not ready to buy yet? Download a free sample
We are confident about the unique quality of our Company Profiles. However, we want you to make the most beneficial decision for your business, so we offer a free sample that you can download by submitting the below form
By GlobalDataBrainChip’s Akida processor, the first fully digital, event-based AI processor of its kind, leverages neuromorphic principles to emulate the human brain.
It analyses key sensor inputs at the moment of acquisition, processing data with high efficiency, accuracy, and low energy consumption. This is particularly beneficial for edge computing scenarios.
The company’s neuromorphic processing technology is engineered to enhance cognitive communication capabilities.
It adheres to the size, weight, power, and cost (SWaP-C) requirements of military, space, and robotics applications across both commercial and government sectors.
Neuromorphic hardware offers a power-efficient alternative for edge AI processing, using less energy than conventional computing systems for tasks such as signal processing and AI-driven identification.
This project aims to establish a new capacity for integrating advanced radar processing technologies into SWaP-C limited radar platforms.
These platforms serve a range of applications including threat detection, air defence, and guidance systems.
It is also used for mobile platforms such as drones, robots, aircraft, satellites, and defence systems reliant on projectiles, where SWaP-C limitations are most challenging.
