Research in the area of Space Object Surveillance Technology (SOST) relates to measurements of objects orbiting the earth by either space-based or ground-based sensors. Understanding the intended function and current state of a “resident space object” (i.e. either a satellite or space junk orbiting the earth) is important – precise knowledge of the orbit will alter satellite operators of impending collisions.
However, observations can be difficult due to observational considerations, including the size of the object, whether or not it is spinning, and the atmospheric and geometric conditions under which the object is observed. In addition to radar and optical observations, infrared measurements allow for the calculation of the object temperature and may provide clues to the composition and operational status of an object.
Object obscuration due to environmental phenomena is a key challenge for robust target detection, tracking and characterization. While the spatial and temporal variability due to stressing environmental phenomena occurring within the atmosphere and ionosphere will have different effects on radio-frequency (RF), electro-optical (EO), and infrared (IR) sensors, maintaining a diverse collection of sensing systems can be costly and does not necessarily mitigate all impacts. Further, impacts are not strictly limited to sensors as environmental phenomena can also adversely impact communication links and GPS signals. Minimizing environmental impacts can be accomplished by using environmental forecast data within the algorithms used for sensor tasking, by weighting the environmental impact on each node’s performance and optimizing the overall capabilities of the network, or by accounting for these phenomena in the data exploitation algorithms.
Stressing environmental conditions occur in different spatial regions and with different temporal scales, but can be modeled individually and forecast minutes, hours or days in advance. We have developed a prototype decision-aid toolkit which is capable of leveraging real-time attributes of the near-Earth terrestrial and space environment to manage tasking of a diverse sensor network. The toolkit utilizes a knowledge-base of satellite measurements and other data sources that quantify the intensity, duration, location, and extent of environmental phenomena. The set of supported phenomena include but not limited to auroral dosing, stratospheric warming, polar mesospheric cloud formations, tropospheric clouds, radar and optical scintillation and high-altitude ozone variability. The toolkit has been designed with generic interfaces that can accommodate the addition of new environmental modules, such as for ionospheric disturbances, and can interface easily with a variety of sensor networks. The toolkit makes use of supportive routines such as surface databases and employs across-the-spectrum radiative transfer capabilities; flexible, realistic climatological models are used for circumstances when real-time inputs are not available.
Satellite Classes and Atmospheric Type
Environmental Conditions That Affect Sensor Performance
Environmental Impacts That Degrade Sensor Performance
To learn more about AER's Space Object Surveillance Technology expertise, please contact us.