Accession Number : ADA621766


Title :   Orbit Estimation of Non-Cooperative Maneuvering Spacecraft


Descriptive Note : Doctoral thesis


Corporate Author : AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH GRADUATE SCHOOL OF ENGINEERING AND MANAGEMENT


Personal Author(s) : Goff, Gary M


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a621766.pdf


Report Date : Jun 2015


Pagination or Media Count : 239


Abstract : Due to the ever increasing congestion of the space environment, there is an increased demand for real-time situation awareness of all objects in space. An unknown spacecraft maneuver changes the predicted orbit, complicates tracking, and degrades estimate accuracies. Traditional orbit estimation routines are implemented, tested, and compared to a multiple model format that adaptively handles unknown maneuvers. Multiple Model Adaptive Estimation is implemented in an original way to track a non-cooperative satellite by covariance inflation and filtering-through a maneuver. Parameters for successful instantaneous maneuver reconstruction are analyzed. Variable State Dimension estimation of a continuously maneuvering spacecraft is investigated. A requirements based analysis is performed on short arc orbital solutions. Large covariance propagation of potential maneuvers is explored. Using ground-based radars, several thousand simulations are run to develop new techniques to estimate orbits during and after both instantaneous and continuous maneuvers. The new methods discovered are more accurate by a factor of 700 after only a single pass when compared to non-adaptive methods. The algorithms, tactics, and analysis complement on-going efforts to improve Space Situational Awareness and dynamic modeling.


Descriptors :   *LOW ORBIT TRAJECTORIES , *MANEUVERING SATELLITES , *SPACE OBJECTS , *SPACECRAFT TRAJECTORIES , ARTIFICIAL SATELLITES , COLLISION AVOIDANCE , COMPUTERIZED SIMULATION , COVARIANCE , EARTH ORBITS , GAUSSIAN NOISE , GLOBAL POSITIONING SYSTEM , GROUND BASED , KALMAN FILTERING , OPTIMIZATION , PROBABILITY DENSITY FUNCTIONS , SEARCH RADAR , SITUATIONAL AWARENESS , SMOOTHING(MATHEMATICS) , SPACE ENVIRONMENTS , STOCHASTIC PROCESSES , TARGET DETECTION , THESES , TRANSFORMATIONS(MATHEMATICS)


Subject Categories : Statistics and Probability
      Space Navigation and Guidance
      Active & Passive Radar Detection & Equipment
      Spacecraft Trajectories and Reentry


Distribution Statement : APPROVED FOR PUBLIC RELEASE