Background
The Army Space M&S Focus Area Collaborative Team (FACT) was formed to address the deficiency of space representation in Army M&S. The Space FACT, led by SMDC, is an Army-wide multi-disciplinary team comprised of community experts to research, identify, and coordinate simulation technology projects in space M&S. The FACT developed a roadmap for space representation in Army M&S. The initial enabling technology identified is to develop a generalized representation of satellites. The Generalized Representation of Space-based Platforms (GRoSP) algorithm was developed to fill this capability gap. The objective of the GRoSP project was to develop a fast running representation of individual space-based systems that could quickly provide satellite locations to real time simulations.
Overview
The algorithm is designed to represent the “Move” behavior of a satellite, and address the shortfall found in traditional approaches to space simulation, namely, the use of continuous propagators with explicit representation of each satellite, each with payload(s) and a unique position in space as depicted in Figure 1. A problem with the traditional approaches is that a typical simulation terrain box may represent less than 0.03% of the earth’s surface, and the
computational resources necessary for the continuous propagation might better be used for simulations of processes that impact training or analysis goals rather than propagation of satellites when they cannot influence military operations in the area of interest. GRoSP is a non-propagation and orbit filter method to determine satellite positions resulting in simulation computational savings of more than 90% when compared to traditional satellite propagating methods like those used by Satellite Tool Kit ® (STK) and Satellite and Mission Analysis Tool (SMAT). The algorithm addresses the various satellite orbit types with different techniques to take advantage of distinct attributes associated with each orbit type. GRoSP incorporates methods for the three near circular orbit types: Low Earth Orbit (LEO), Medium Earth Orbit (MEO) and Geosynchronous (GEO). Approximately 98% of the satellites in orbit are in these three orbit regimes. GRoSP assumes circular orbits and thus doesn’t address the fourth orbit type, Highly Elliptical Orbit (HEO).
The GRoSP algorithm is a non-propagation approach and potential standard for predicting satellite over-flight “events” for simulations. GRoSP accepts inputs like orbit shape, velocity, altitude, & inclination and then returns a space event scheduler. The representation is generalized, because 1) it considers only the platform itself and is payload independent, and 2) it does not rely on simulation specific algorithms to calculate line of sight. This initial enabling technology provides the ability for the modeling and simulation communities to answer these questions about a space-based platform during a simulation:
• At a given time t, where is the satellite? Answer can be given in latitude, longitude, altitude (LLA) or Cartesian coordinates.
• Can the satellite payload “see” the simulation terrain box? For LEO satellites, much of their orbits exist with no line of sight access to the terrain box. The simulation might only want to concern itself with these satellites when they are in a position to “see” the gamebox.
• For a given time t, what is the angle above horizon and distance from a particular simulation entity to the GPS satellite? These factors may be used to determine the Position Dilution of Precision (PDOP) or the geometrical effect on GPS accuracy.
GRoSP addresses these questions, using multiple methods, since the different satellite orbital orientations and shapes are such that different methods are necessary to adequately answer these questions in a reasonable and a computationally efficient manner.
Low Earth Orbit Satellites
LEO satellites tend to be between 300 and 2,000 kilometers in altitude and typically have ISR missions, but there are also ones that are used for communications. More than half of the satellites in orbit are LEOs and each of these satellites orbits the earth between 14 and 16 times in a 24-hour period. The GRoSP’s initial and primary focus was on LEO because satellites in this orbit represent approximately 95% of total revolutions by satellites and offers the best opportunities for saving computational resources. The GRoSP algorithm computes only one point per orbit, the north to south equator crossing point or Longitude of Ascending Node (LAN). When a LAN is inside one of the calculated gateways depicted in Figure 2
for that satellite/game box combination, the influence entry and exit points are solved directly using spherical trigonometry. In other words a position and time stamp is provided to the simulation when each satellite can influence and no longer influence the game box. If a LAN is outside of the gateway, then the satellite’s position is not calculated because it cannot influence the game box.
Medium Earth Orbit Satellites
MEO satellites are at about 20,000 kilometers in altitude and are typically tasked with Position/Navigation. Global Positioning System (GPS) and the Russian GLONASS constellations are in this orbit. Each of these satellites has two revolutions per day, and MEOs represent approximately 2% of the satellites in space. GRoSP’s LEO gateway concept isn’t a practical solution for MEOs because a satellite Field of Regard at about 20,000 kilometers covers at least 90% of the earth during a single revolution. Since there are relatively few satellites in this orbit type and they only have two revolutions per day, it isn’t computationally intensive to return the position of a MEO satellite when requested by a simulation even when the satellite cannot influence the area of interest. The basic calculations for satellite position use the same spherical trigonometry calculations used in the LEO method.
Geosynchronous Satellites
GEO satellites are at about 36,000 kilometers in altitude and are primarily communications satellites. Approximately 40% of the satellites in orbit are GEOs. Their orbits are designed to have one revolution per day in order to stay essentially fixed over the same point of the earth as shown in Figure 3.
These satellites have very low inclinations or small angle differences between the satellite orbit plane and the equatorial plane. Geostationary satellites (a subset of geosynchronous satellites) have an inclination angle near 0 degrees and appear to “hang” over one point on the equator. This hanging over one point creates a non-changing geometric relationship between ground stations and the satellite. The GRoSP algorithm models all geosynchronous satellites or GEOs as geostationary satellites for a reasonable representation, and takes advantage of the non-changing geometric relationship between simulation entities and the satellite. GRoSP models these satellites simply by fixing them in one position over the equator.
Benchmarking
The algorithm was successfully benchmarked with STK, an industry space propagation standard. The results for the three satellite types include less than .05 degrees in longitude and zero error in time for LAN calculation. Test conclusions indicated that the algorithm filtering gateways captured all of the relevant orbits for the area of interest. Finally, the satellite position at the entry/exit points had less than a 0.15% error and time at these points had less than 0.66% error.
Data
Two Line Element (TLE) Sets are satellite location data sets produced by Cheyenne Mountain Operations Center for NASA and are available through internet connections at: http://oig1.gsfc.nasa.gov/. A TLE contains position data for a satellite at a specific date and time or epoch. GRoSP is designed to use a database populated with TLEs and attributes that are calculated from TLEs for satellite event schedule calculations. Cheyenne Mountain Operations Center TLEs are the standard and thus it makes sense to use this format for existing satellites, but what about conceptual or hypothetical satellites? Satellite propagation software, like STK, provides a TLE when requested for conceptual satellites. For example, an analysis team preparing to conduct a Space-Based Radar (SBR) military utility study in 2017 first designs the conceptual constellation in STK and then requests TLEs for all individual satellites. The TLEs are then transferred to the database of a simulation with GRoSP for use in the scenario.
Current Application
The algorithm was recently transferred to TRADOC Analysis Center-White Sand Missile Range (TRAC-WSMR) for incorporation in the COMBATXXI model. This simulation is a brigade and below, force-on-force, combined arms model. GPS payloads were identified as the first potential payloads to represent with the GRoSP satellite move algorithm. GRoSP is reusable technology and is appropriate for use in event driven and time stepped simulation environments.
Future Efforts
Following Space FACT Roadmap research efforts include development of aggregate constellation, sensor, and communications behaviors. The development of a payload database has also been identified to complement the GRoSP algorithm. Additional effort with GRoSP may also be completed to incorporate the fourth and final orbit type, HEO.
For more information about the Space FACT or the GRoSP algorithm, contact Mr. Steve Fox at the Space & Missile Defense Battle Lab, 256-955-3580 or steven.fox@smdc.army.mil.