Space Object Characterization Using Time-Frequency Analysis of Multi- spectral Measurements from the Magdalena Ridge Observatory

摘要

The interactions between the surface materials and the body dynamics complicate the characterization of space objects from their optical signatures. One method for decoupling these two effects on the observed signature is to obtain simultaneous measurements using multiple spectral filter bands. The advantage of this approach is that it provides spectral resolution between the filter bands to identify the different materials based on their optical properties as a function of wavelength and temporal resolution between samples to identify the periodic, quasi-periodic, and transient fluctuations characteristic of the object motions, including attitude control, maneuvers, and station-keeping. We have developed algorithms to extract and to analyze light curve data from unresolved resident space objects (RSO) collected at the Magdalena Ridge Observatory (MRO) using the Multi Lens Array (MLA) camera coupled to the 2.4-m telescope. The MLA camera produces 16 spectrally-filtered and temporally synchronous sub-images ranging from 414 nm to 845 nm. We have developed a filter band calibration using a set of stellar observations to remove the atmospheric refraction and absorption effects and differences in the optical paths across the different filter bands using catalogued spectrophotometric data. We apply wavelet analysis to the RSO optical signature light curves to obtain the time-frequency characteristics of the signal for each band. This information allows us to obtain information about the body motions as a function of time. We next attempt to correlate these characteristics across the different MLA filter bands to derive constraints on the types of surface materials.