This study evaluates the fundamental shift in the United States space-based missile defense architecture from a reliance on a limited number of high-altitude satellites to the deployment of large constellations in Low Earth Orbit. Driven by the enactment of Public Law 119-21 and the proposed "Golden Dome" system, the study examines how and whether space-based infrared sensors are evolving to detect and track modern threats, such as Hypersonic Glide Vehicles and Fractional Orbital Bombardment Systems. While legacy systems like the Space-Based Infrared System provided early warning, their high altitude and sensors' technology hindered the spatial resolution required for precise fire-control capabilities. The Proliferated Warfighter Space Architecture should improve tracking by orbiting closer to Earth and utilizing sensors on multiple satellites to enable 3D triangulation via stereo-vision. However, the technical efficacy of these systems remains difficult to verify due to classified sensor specifications and inconclusive experimental results.

A document by Simone Fontana. Click on the document to view its contents.

Point cloud registration is a fundamental problem in robotics, critical for tasks like localization and mapping. Most approaches to this problem use feature based techniques. However, these approaches are limited when dealing with un-structured environments where meaningful features are difficult to extract. Recently, an innovative global point cloud registration algorithm, PHASER, which does not rely on geometric features or point correspondences, has been introduced. It leverages Fourier transforms to identify the optimal rigid transform that maximizes cross-correlation between source and target point clouds. PHASER can also incorporate additional data channels, like LiDAR intensity, to enhance registration results. Because it does not rely on local features and because of its ability to exploit additional data, PHASER is particularly useful when dealing with very noisy point clouds or with many outliers. For this reasons, we propose an extension to PHASER that considers multiple plausible rototranslation hypotheses. Our extended approach outperforms the original PHASER algorithm, especially in challenging scenarios where point clouds are widely separated. We validate its effectiveness on the DARPA SubT, and the Newer College datasets, showcasing its potential for improving registration accuracy in complex environments.