Innovative LCOLA tool prioritizing accuracy, launch access and efficiency

Innovative LCOLA tool prioritizing accuracy, launch access and efficiency - Paper
Innovative LCOLA tool prioritizing accuracy, launch access and efficiency - Presentation
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Id: 238

Type: Conference paper

Published: 10/20/2021

Event: IAASS Conference 2021


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Abstract:

A new Launch Collision Avoidance (LCOLA) analysis capability is presented. The method represents the combination of the patented algorithm developed by Analytical Graphics Inc. and implemented in its Launch Window Analysis (LWA) tool, together with a new LCOLA collision probability algorithm developed by COMSPOC Corporation to maximize launch window using responsive, comprehensive, and efficient LCOLA closure windows. The new tool works by assessing the underlying topography of the launch closure problem to identify and characterize all launch holds within the user-specified launch window without confining the launch operator to “top-of-the-minute” or other such constructs rapidly and accurately. This new LCOLA capability avoids the pitfalls of the typical “digitized” launch window screening approach, where launch objects are compared against the on-orbit catalogue at a small launch “T-zero” step size. The new capability can detect launch closure holds based upon miss distance, collision probability or both. Prior to the probability calculation, each covariance is tested for positive definiteness and remediated if necessary. The tool’s support for parallel processing, combined with its algorithmic efficiency, allow it to process all deployed objects. The tool aggregates all resulting launch holds into a concise report for the launch director and team.

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Citation:

Oltrogge, D.L. and Alfano, S., “Innovative LCOLA tool prioritizing accuracy, launch access and efficiency,” 11th IAASS Conference – Managing Risk in Space, Virtual, Paper AS-09-03, International Association for the Advancement of Space Safety, 19-21 October 2021, accessible at https://comspoc.com/Resources/Content/Private/C-20220423T085327/Paper/20211020_IAASS_LCOLA_Paper_FINAL.pdf.

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