TABLE 2.1 Summary of Current AFSPC Standardized Astrodynamics Algorithms

                                                AFSPC Algorithm
Astrodynamics Task Special Perturbations General Perturbations
Atmosphere model J70 plus HASDM Simple atmosphere
Force models    
    Drag Piecewise-constant ballistic coefficient Constant ballistic coefficient
    Solar radiation pressure (SRP) Piecewise-constant reflectivity coefficient None
    Earth gravity High-order geopotential (Earth Gravitational Model 1996) truncated to medium degree and order plus Earth and ocean tides (from U.S. Naval Observatory) Low-degree zonals only geopotential
    Third-body gravity Sun and Moon (option for analytic or JPL ephemerides model) Semi-analytic Sun and Moon
Trajectory propagation Gauss-Jackson eighth order SGP4
Orbit determination Weighted batch least-squares, with drag/SRP segmentation Weighted batch least-squares, sequential differential correction
Error estimation Covariance propagation Covariance computed but not distributed
     

should address many of these issues—and opportunities. A modern service-oriented architecture and well-engineered software can provide a platform to encourage innovation throughout the community, ease integration of alternative algorithms that offer improvements for all or a subset of customers/clients, and address the interface requirements of users who need legacy products and those who need more technically advanced products.

In this chapter, the committee surveys state-of-the-art and historical approaches to AFSPC astrodynamics tasks and provides an outlook and general recommendations for future advances and applications. In particular, a number of specific technical areas are discussed in which the space situational awareness enterprise is likely to expand, many of them requiring the development of standardized astrodynamics algorithms beyond the current set. These representative technical areas are perceived by the committee as critical to meeting future needs of AFSPC, the JSpOC, the warfighter, and the broader space situational awareness community. Potential areas for improvement are considered in the context of fundamental tasks currently in practice as well as new methods and applications that respond to the changing mission and computing environments. Included are case studies and discussions of new and future possible advances in algorithms, theory, and modeling. The content of this chapter is not exhaustive, but it is representative of the committee’s vision of how the needs and capabilities of space situational awareness within AFSPC are likely to expand in the future. Any of these areas can serve as motivation for the future expansion of the astrodynamics algorithms toward more diverse capabilities.

The chapter is organized according to a logical flow of astrodynamics information: atmosphere models (needed to compute drag forces), force models (needed to propagate orbits), trajectory propagation (including numerical integration techniques), and orbit determination. A section is then devoted to uncertainty representation and computation, which, as discussed in Chapter 1, is an area that needs improvement in order to meet user needs for conjunction assessments. The chapter concludes with a section examining the important future drivers and directions for space situational awareness research. The section ordering is not indicative of perceived priority or importance. Important subtopics include data association methods, analytic techniques, modern dynamical systems, nonlinear filtering, and characterization of objects in orbit.



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