PCA Filtering of Apache Point Observatory 3.5m Agile Observations of LCROSS
Authors/Creators
- 1. Concordia University Wisconsin, Mequon, Wisconsin, USA
- 2. New Mexico State University, Las Cruces, New Mexico, USA
Description
This archive contains data products from observations of the 2009-10-09 impact of the Lunar CRater Observation and Sensing Satellite (LCROSS) spacecraft on the Moon by the Agile instrument on the Apache Point Observatory 3.5m telescope. We use principal component analysis (PCA) filtering both to improve the coregistration of the raw time series and to effectively remove a static background signal that is spatially and temporally modified by atmospheric and instrumental effects. We iteratively remove principal components from the data through cumulative sequential elimination (CSE) to find a maximum signal-to-noise ratio of the LCROSS ejecta plume signal.
Full details are available in the published journal article:
Strycker, Paul D., Nancy J. Chanover, Ruth L. Temme, Jonathan M. Schotte, Payton L. Mueller, and Emily L. Karls. 2023. "Time Series Analysis Methods and Detectability Factors for Ground-Based Imaging of the LCROSS Impact Plume" Remote Sensing 15, no. 1: 37. https://doi.org/10.3390/rs15010037
This work was supported by NASA’s Lunar Data Analysis Program through grant number NNX15AP92G.
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Additional details
Related works
- Is compiled by
- Software: 10.5281/zenodo.7268912 (DOI)
- Is derived from
- Dataset: 10.17189/1519484 (DOI)
- Is published in
- Journal article: 10.3390/rs15010037 (DOI)
- Is source of
- Journal article: 10.1016/j.icarus.2020.114089 (DOI)