Patrick Miga, Advanced Space; Matthew Givens, Advanced Space
A classic challenge in space domain awareness (SDA) is that of associating new measurements of space objects to a previously generated catalog. Often, ballistic propagation and statistical distance metrics can be used to make these track-to-orbit associations, but these methods alone can fail to associate all available measurement tracks to the catalog and result in a backlog of uncorrelated tracks (UCTs). The reasons for these association failures can be many, including uncertainties in the dynamic models, the existence of new, previously untracked objects, and the fact that these objects could be executing unknown maneuvers of unknown purpose and scale. Further, it is sometimes assumed that the track itself contains enough information to instantiate an initial orbit determination (IOD) solution, which may not be the case if the measurement arc is “too short” for a classical IOD solution to converge.
Motivated by the observation that successful correlation of a track to a maneuvering object constitutes a successful detection of one or more unknown maneuvers, Advanced Space has developed tools for associating uncorrelated tracks considering large uncertainties in the initial orbit solution as well as the possibility that a space object has executed maneuvers since it was previously detected. First, we leverage insights from the existing literature on the “too short arc” problem to create a restricted IOD tool that uses rejection sampling to generate a probabilistic representation of the admissible region for both electro-optical and radar measurement types. This approach is more robust than the more common deterministic admissible region because it can easily incorporate any constraint available and also take factors like measurement noise and timing uncertainty into account. The admissible region samples can be mapped to any state space, such as inertial Cartesian or orbit elements, and either propagated directly or fit with a Gaussian mixture model (GMM) and passed to a GMM propagation routine.
Upon creation of an IOD solution generated by some measurement track, whether from the admissible region approach or by some other method, we map the estimate into modified equinoctial elements and backpropagate its reachability to determine the objects that could possibly explain the measurement track then prune each object in the catalog that is outside this reachable bound. At this point we are left with a much smaller subset of objects in the catalog.
Finally, the measurements, the IOD solution, and the remaining subset of objects in the catalog are fed into an object association scheme which essentially finds the deviation from the future propagated states of the remaining objects. Utilizing techniques from optimal control, a metric like fuel consumption or change in velocity (ΔV) can be mapped to the magnitude of this deviation; it is somewhat reasonable to assume that the object that would lead to the minimal deviation or minimal fuel consumption would be the most likely to explain the measurements and thus would flag a possible maneuver. However, this is not a guarantee; therefore, all objects are assigned a likelihood that is proportional to the size of the metric which offers a likely association back to the object that is responsible for the measurements. This offers a very quick, first glance at possible maneuver detection, and in many cases presents operators with ample time to assess further decisions. As more time passes and upon further successful correlation activities which confirms that other objects are not associated with these measurements, the certainty of which object belongs to the measurements grows.
This flow is combined into a pipeline that seamlessly functions from a given measurement track input and access to the space object catalog. Performance of this method is characterized as well as scenarios with high applicability to the field of SDA, and future development is posed, such as integration into the SDA TAP Lab and improvements to the methodology. Comparisons are also made to existing maneuver detection methods.
Date of Conference: September 16-19, 2025
Track: Astrodynamics