WASHINGTON (NRO PR) — The National Reconnaissance Office (NRO) announced the award of five contracts for commercial radar capabilities under the agency’s new Strategic Commercial Enhancements Broad Agency Announcement (BAA) Framework. Companies receiving contracts are Airbus, U.S.; Capella Space; ICEYE, U.S.; PredaSAR; and Umbra.

“We are very pleased with the response to the first focus area under our new BAA,” said Dr. Chris Scolese, NRO director, who announced the release of the BAA acquisition just three months ago. “We know that users across the National System for Geospatial Intelligence are eager to explore commercial radar, and these contracts will allow us to rapidly validate capabilities and the benefits to the national mission.”

The Strategic Commercial Enhancements BAA Framework is designed to reach across disciplines and the global commercial remote sensing market to drive innovation, explore new phenomenologies, and ultimately, to ensure that the U.S. government has access to the best available commercial remote sensing capabilities.

WESTMINSTER, Colo. (Maxar Technologies PR) — Maxar Technologies (NYSE:MAXR) (TSX:MAXR), a trusted partner and innovator in Earth Intelligence and Space Infrastructure, today announced it has been awarded a five-year contract worth up to $26.4 million by the U.S. National Geospatial-Intelligence Agency (NGA) to sustain and enhance the National System for Geospatial Intelligence Open Mapping Enclave (NOME). Under the agreement, Maxar will continue to provide engineering, software development and geospatial tradecraft in support of NOME.

The web-based NOME platform enables a community of vetted U.S. government users to create and update geospatial features in a crowdsourced “living map.” NOME was initially developed to support NGA’s foundation mapping mission, but the platform emerged as a powerful tool to perform unclassified mission support remotely throughout the COVID-19 pandemic. Increasingly, users also leverage the platform to create features for further dissemination across multiple networks and to train artificial intelligence and machine learning (AI/ML) models.