Artificial Intelligence for Adaptive Beamforming
OBJECTIVE
Improve the performance and responsiveness of multi-antenna systems in increasingly constrained and noisy environments.
ADVANTAGES
Reduction in computation time
Lower resource requirements for onboard implementation
Agile beamforming capabilities
Multi-source tracking
Adaptability to a variety of scenarios
APPLICATIONS
Anti-Jamming
ARKANE solutions address emerging jamming threats by enhancing adaptive spatio-temporal processing with integrated machine-learning software blocks.
These approaches require fewer resources and are more effective, adding significant value for autonomous protective systems during flight missions.
Next-Level Beam/Path Formation
These solutions enable the development of large, efficient antenna networks and push beyond the limits of current algorithms with respect to computational complexity.
Radar Tracking
Estimate signal direction-of-arrival from large radar data cubes for precise detection and tracking of moving targets.
The advanced technology uses signal-processing algorithms to extract critical information about direction, speed, and trajectory of detected objects.
USE CASES
Satellite / Communications
Multi-beam formation
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Suitable for LEO / MEO constellations
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RADAR
Multi-source tracking
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Direction-of-arrival (DoA) estimation
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Source localization
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Adaptive beamforming
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GNSS Anti-Jamming Navigation
Jammer rejection
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Robust position, velocity, and timing (PVT)
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Autonomous safeguard systems
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