Artificial Intelligence / Machine Learning (AI/ML)-Based Radar Data Compression
AI Overview
This RFP seeks AI/ML-based compression technology for high-rate radar data streams, addressing the challenge of massive synthetic aperture radar data volumes. The solution will develop neural network architectures to compress raw radar returns with minimal distortion, reducing bandwidth requirements for transmission and storage across defense and civilian sensor applications.
This summary is AI-generated from the official solicitation.
Key Details
Official Description
Next-generation radars (especially synthetic aperture radar (SAR)) collect data with massive data rates. Traditional image compression is not optimized for raw radar returns. Recent work extends neural compression to the complex SAR domain. Phase I is to explore autoencoder architectures for radar data using, for example, a complex-valued neural network encoder/decoder that learns to compress raw pulses or range-Doppler maps into a latent code with minimal distortion. The system could be trained...
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Artificial Intelligence / Machine Learning (AI/ML)-Based Radar Data Compression
New opportunity: Artificial Intelligence / Machine Learning (AI/ML)-Based Radar Data Compression
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