Time Series Analysis Methods and Detectability Factors for Ground-Based Imaging of the LCROSS Impact Plume

Abstract

On 9 October 2009, multiple telescopes were used in a coordinated international observing campaign to acquire ground-based time series imaging to monitor the evolution of the impact plume from NASA’s Lunar CRater Observation and Sensing Satellite (LCROSS) mission. Although standard image processing techniques applied to these data were unsuccessful at detecting the presence of any impact plume, one detection was reported after processing images with Principal Component Analysis (PCA) filtering. In this work, we develop improvements to PCA filtering that increase the signal-to-noise ratio (SNR) of plume lightcurves. We use this updated methodology to remove atmospheric seeing effects not accounted for in the previous work, such as geometric distortions. We assess the robustness of PCA filtering as we search for plume detections in observations from five additional cameras in comparison with each pixel’s lightcurve during the final 40 s prior to impact to match the approximate duration of post-impact excess brightness. We explore the resulting combination of three detections and three non-detections to determine criteria for detectability in future observations of low SNR transient events. Our results indicate three observational setup constraints for optimizing the success of PCA filtering: (1) full-frame scattered light should not exceed the dynamic range between the illuminated and unilluminated surfaces, (2) the camera’s analog-to-digital conversion (ADC) should use at least 16-bit resolution, and (3) the ADC should not use gamma correction. We find that poor spatial or temporal resolution do not significantly degrade detectability, which suggests that any future LCROSS-like events may be detectable in PCA-filtered amateur observations.