Chris Sabol

Satellite Formation Flying Design and Evolution

Several satellite formation e ying designs and their evolution through time are investigated. Satellite formation e ying designs arederived from the linearized equations of relative motion under two-body dynamics better known as Hill’ s equations (Hill, G. W., “ Researches in the Lunar Theory,”American Journal of Mathematics , Vol. 1, No. 1, 1878, pp. 5‐26). The formations are then propagated forward in time in the presence of realistic perturbations to determine the stability of each design. Formations considered include in-plane, in-track, circular, and projected circular designs. The Draper Semianalytic Satellite Theory is used to propagate mean elements of the satellites. When perturbations disrupt the satellite formations, an effort is made to quantify the cost of formation-keeping maneuvers. The goal of this effort is to provide physical insight into satellite formation e ying design and outline the effects of realistic dynamics on those designs.

Covariance-based Uncorrelated Track Association

When the Air Force Space Surveillance Network observes an object that does not correlate to an entry in the Space Object Catalog, it is called an Uncorrelated Track (UCT). Some of these UCTs arise from objects that are not in the Space Catalog. Before a new object can be added to the catalog, three or four UCTs must be associated so that a meaningful state can be estimated. Covariance matrices can be used to associate the UCTs in a more statistically valid and automated manner than the current labor-intensive process. To perform the association, the state and covariance from a UCT at a certain epoch must be propagated to the epoch of another UCT state estimate. The uncertainty in UCT state estimates can be large due to limited data and tracking geometry. When the UCT is propagated more than a few hours, the in-track uncertainty becomes much larger and the uncertainty quickly becomes non-Gaussian if it is expressed in Cartesian coordinates. The state uncertainty expressed in elliptical curvilinear coordinates remains Gaussian for longer propagation times and larger in-track separations than when expressed in Cartesian space. Simulations show that automated covariance-based UCT association using curvilinear coordinates performs very well even with time-varying measurement biases.

Photometric Attitude Estimation for Agile Space Objects with Shape Uncertainty

The problem of estimating attitude for actively maneuvering or passively rotating space objects with unknown mass properties/external torques and uncertain shape models is addressed. To account for agile space object maneuvers, angular rates are simply assumed to be random inputs (e.g., process noise), and model uncertainty is accounted for in a bias state with dynamics derived using first principles. Bayesian estimation approaches are used to estimate the resulting severely non-Gaussian and multimodal state distributions. Simulated results are given, conclusions regarding performance are made, and future work is outlined.

Improved Angular Observations in Geosynchronous Orbit Determination

How improved angular observations can aid in the determination of satelliteposition and velocity in thegeosynchronous orbit regime is studied. Raven, a new, automated, low-cost sensor being tested by the U.S. Air Force Research Laboratory, allows for angularobservationsof satellitesto be madewith a standard deviation ofapproximately 1 arc-s (which maps into approximately 170 m at geosynchronous altitude ); this is an order of magnitude improvement over traditional angular observation techniques. Simulation studies are undertaken to show how these angular observations can be used in the orbit determination process both as the only tracking data source and as a supplement to other tracking data sources, such as radio transponder ranges. Parameters varied in the simulation studiesincludethenumberofobservingstations,thedensity oftheopticalobservations,and thenumber of nights of optical tracking. The studies indicate that including the improved angular observations with traditional high-accuracy range observations produces a considerable improvement in orbit determination accuracy over the range observations alone. The studies also indicate that single site geosynchronous orbit determination is an attractive alternative when combining improved angular and high-accuracy range observations.

Angles-Only Orbit Updates for Low-Earth-Orbit Satellites

This paper provides the development of a simplified covariance model for predicting the along-track error uncertainty and error uncertainty growth rate for the single-pass, angles-only orbit update, the validation of the model using simulation and real data cases, and a summary of efforts made to characterize the uncertainty of general-perturbations-based element sets. The analysis shows that one of the limiting factors in obtaining a high-accuracy orbit update from a single pass of angles-only data is the eccentricity uncertainty. For the observation characteristics considered, a high-accuracy orbit update could not be obtained if the initial eccentricity uncertainty is 10 -5 or greater. Analysis of general perturbation element set uncertainties showed that typically the eccentricity uncertainty is no smaller than 10∼5, so the eccentricity uncertainty is a limiting factor in obtaining an accurate orbit update with a single pass of angles-only data with general perturbations element sets.

Uncorrelated-Track Classification, Characterization, and Prioritization Using Admissible Regions and Bayesian Inference

This paper introduces and discusses a method to rigorously classify and prioritize uncorrelated tracks using Bayesian inference and admissible regions. A detailed derivation and discussion of the methodology are given, followed by a generalized definition of prioritization parameters. Several example prioritization parameters, including time left to detect, zero-effort miss, and effective albedo–area, are motivated and given. A number of illustrative applications with optical uncorrelated tracks are examined to demonstrate information that can be extracted from each observation. Finally, the information extracted from each uncorrelated track is then compared and prioritization of subsequent sensor-asset measurements discussed.

The Joint Space Operations Center Mission System and the Advanced Research, Collaboration, and Application Development Environment Status Update 2016

The Joint Space Operations Center (JSpOC) Mission System (JMS) is a service-oriented architecture (SOA) infrastructure with increased process automation and improved tools to enhance Space Situational Awareness (SSA) performed at the US-led JSpOC. The Advanced Research, Collaboration, and Application Development Environment (ARCADE) is a test-bed maintained and operated by the Air Force to (1) serve as a centralized test-bed for all research and development activities related to JMS applications, including algorithm development, data source exposure, service orchestration, and software services, and provide developers reciprocal access to relevant tools and data to accelerate technology development, (2) allow the JMS program to communicate user capability priorities and requirements to developers, (3) provide the JMS program with access to state-of-the-art research, development, and computing capabilities, and (4) support JMS Program Office-led market research efforts by identifying outstanding performers that are available to shepherd into the formal transition process. In this paper we will share with the international remote sensing community some of the recent JMS and ARCADE developments that may contribute to greater SSA at the JSpOC in the future, and share technical areas still in great need.

Search and Determine Integrated Environment (SADIE) for Automated Processing of Space Surveillance Observations (Invited)

A new high-performance computing software applications package called the Search and Determine Integrated Environment (SADIE) is being developed and refined jointly by the Air Force and Naval Research Laboratories (AFRL and NRL). SADIE is designed to resolve uncorrelated tracks (UCTs) and build a more complete space object catalog for improved Space Situational Awareness (SSA), automatically. The motivation for SADIE is to address very challenging needs identified by Air Force Space Command (AFSPC) and other senior leaders and to develop this technology for the evolving Joint Space Operations Center (JSpOC) and Distributed Space Command and Control Center (DSC2)-Dahlgren. The SADIE suite includes modification and integration of legacy applications and software components that include Satellite Identification (SID) and Parallel Catalog (ParCat) as well as other utilities and scripts to enable end-to-end catalog building and maintenance in a parallel processing environment. SADIE is being developed to handle large catalog-building challenges in all orbit regimes and includes the automatic processing of radar and optical data. Promising real data results are provided for the processing of near-Earth radar and Space Surveillance Telescope optical data.