Developing a Synthetic Light Curve Forward Model Laurence Blacketer Astronautics Research Group University of Southampton

Introduction PhD at the University of Southampton, with Dr. Hugh Lewis, under the preliminary title “Attitude Detection from Light Curves” NASA requests of the IADC member states light curve data of large objects, in support of ADR research. Following a brief analysis, the results data were found to be inconclusive.

The Data ESA: - University of Bern - Zimmerwald telescope JAXA: - Nyukasayama Optical Observatory CNSA: - Multiple Sensors NASA: - TOP SECRET

MMT The Mini-MegaTORTORA system 9 channels installed in pairs 5630 objects 157,869 light curves Oldest: 2014/06/04 Latest: 2018/03/06

The Model Synthetic forward model, used to replicate true light curve data. Positional data acquired from the NASA Horizons system and TLE database. Brightness measurements are generated through application of Bidirectional Reflectance Function, to a faceted geometry.

Model Inputs Inputs: Light curve start and stop times. Object Geometry BDRF parameters Attitude State

Model Output

Demonstration: An Active System Object: Globalstar M067 [32264] Launched: 2007 - 10 - 20 Current Status : ACTIVE Attitude: [0, 0, 0] Attitude Motion: [0, 0, 0] BDRF: - Primarily diffuse reflection from body - Primarily specular reflection from panels

Active: Average Magnitudes

Active: Standard Deviations

Overlaid: Avg. Magnitudes

Overlaid: Standard Deviations

An Inactive System Object: Globalstar M054 [25885] Launched: 1999 - 08 - 07 Current Status : INACTIVE MMT Period: 7.15s Attitude: [0.4449, 5.1212, 4.8249] rad Attitude Motion: [0.7406, 0.4420, 0.1683] rad

Inactive: Average Magnitudes

Inactive: Standard Deviations

Comparison:

Object of Interest Object: Globalstar M067 [32263] Launched: 2007 - 10 - 20 Current Status : INACTIVE Attitude: [0, 0, 0] Attitude Motion: [0, 0, 0]

Object of Interest: Avg. Magnitudes

Object of Interest: Standard Deviations

Overlaid Standard Deviations

Results Summary Modelling an active system with zero attitude motion produces light curves with similar properties to real data. The inactive system was modelled with a random attitude motion, the period of which matches the MMT data. Although Std. Devs. are higher in the synthetic data, both are larger than in the active case. The Std. Devs. of the object of interest transition from values typical of an active system, to values typical of an inactive system.

Future Work Expanded and more rigorous variability analysis. Writing a paper on the sensitivity of the synthetic light curve model to varying inputs. Inverse model development. Use the light curve data to produce attitude state estimates.

Thank you for listening. Laurence Blacketer – University of Southampton E-mail: ldjb1g15@soton.ac.uk