APPLIED DEFENSE SOLUTIONS, INC.

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As space becomes increasingly congested and contested space operators must rapidly assess threats with confidence to know what actions can be taken. Machine learning (ML) offers promise in efficiently ...

This is a prototype system that will take raw observation data, detect and characterize maneuvers, and use reinforcement learning to understand and react to evasive RSO behaviors in near real time. Th ...

In response to the challenges described in AF173-CT05, Applied Defense Solutions (ADS) and the University of New Mexico (UNM) (equivalently, the ADS Team) propose to research and develop innovative va ...

The Air Force Research Laboratory (AFRL) Space Vehicle Directorate (RV) seeks to advance the state-of-the-art in autonomous guidance, navigation, and control (GN&C) technology in support of spacecraft ...

To further enhance our ability to assess orbital events in the context of highly complex and ever evolving situations, provide a fuller understanding of the space operational picture, support indicati ...

An increasing rate of launches into deep-space is compromising the Air Forces ability to effectively monitor orbital activity and perform its space protection mission. Through the SBIR Solicitation AF ...

The United States has enjoyed many asynchronous advantages from its dominance of the space domain. The ability to maintain a deep space catalog is a critical component of the Space Situational Awarene ...

ABSTRACT: In this work we propose an integrated Finite Set Statistical (FISST) and hierarchical reasoning filtering solution to enable rapid catalog processing and object characterization for threat i ...

To further enhance our ability to assess orbital events in the context of highly complex and ever evolving situations, provide a fuller understanding of the space operational picture, support indicati ...