Space debris modelling and situational awareness

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The attitude states of space objects have long been neglected in orbital determination and propa-gation. The result of this is uncertainty in the positions of objects. There is an ongoing initiativewithin the space industry to improve our tracking capabilities in order to improve the accuracywith which the positions of space objects are known and can be predicted. Incorporating attitudestate would be one way of achieving this goal. Additionally, the results of debris modelling research has indicated a possibility of a collision driven growth in the low-Earth orbit debris population. Active Debris Removal (ADR), typically though a physical interface and de-orbit manoeuvre, has been suggested as a technique for mitigatingthis growth. Attitude state information is of the utmost importance to an ADR mission both forselecting a suitable object to remove and for carrying out the mission itself.Determining the attitude state of an inactive space object requires external observation data,typically radar or optical. Of all the available data types, none are more common than opticallight curves. It is therefore the objective of this research to develop techniques to derive informationon space object attitude state from optical light curve data.In light of the going research in the field, the selected approach was to split the problem into aforward model, and an inverse model. The forward model is responsible for generating accuratesynthetic light curves. The inverse model will then use parameter optimisation techniques to define possible attitude state solutions.