Improved Estimation Approaches for High-Accuracy Satellite Detection, Tracking, Identification, and Characterization

ABSTRACT: Numerica is proposing to extend its mature multiple hypothesis tracking (MHT) technology by providing additional estimation and data fusion algorithms to support improved space object detection, tracking, identification, and characterization. An extended program would aim to develop a feature-aided MHT (FA-MHT) capability that (i) exploits both kinematic and feature data including light curve (intensity) data with supporting camera models (e.g., CCD, CMOS, and RULLI) and (ii) provides a new supporting algorithm suite for 12-dimensional states (i.e., position, velocity, attitude, rotation rates) and six degree-of-freedom (6-DOF) dynamics. The envisioned output of the FA-MHT would be a high fidelity space catalog which would augment the traditional space catalog (i.e., position-velocity or orbital element track data) with additional information about an object's attitude, spin rates, shape, and other physical properties. As a post-processor to the FA-MHT system, Numerica would develop a space object characterization prototype using physics-based or machine learning-based classification techniques. Thus, the proposed FA-MHT, object classifier, and supporting algorithms will build upon Numerica's existing MHT system for space surveillance by providing an advanced capability for joint data association, attitude estimation, and feature extraction with the potential to improve the robustness of space object characterization. BENEFIT: The first anticipated benefit from the proposed program would be an automated and robust feature-aided multiple hypothesis tracking (FA-MHT) system that would perform joint data association, state and attitude estimation, and feature extraction with the potential to provide improved estimation approaches for high accuracy space object detection, tracking, identification, and characterization. A second anticipated benefit would be the significant advance in astrodynamics algorithms for 12-dimensional states and six degree-of-freedom dynamics that would support the FA-MHT system and other space situational awareness functions such as conjunction analysis and satellite attitude change detection. The resulting FA-MHT system and its supporting algorithms, which would make use of both kinematic and feature data, would provide analysts with a more accurate and reliable decision-making tool. The key commercialization of the proposed program would be a transition of the algorithms and software, either alone or embedded in a modern multiple target tracking system, to Air Force Space Command, Space Missile Command, the Joint Space Operation Center, the National Reconnaissance Operations Center, or to a prime working on the Space Fence radar such as Lockheed Martin. This program also provides the opportunity to work with other contractors and the nation's Air Force labs in support of the nation's space protection and situational assessment programs utilizing Numerica's strengths in all phases of multiple target tracking, modern control systems, sensors, sensor resource management, and situation assessment.