Bayesian N-Dimensional Aerial Delivery Estimator (BNDADE)

ABSTRACT:MORSE (Mission Oriented Rapid Solution Engineering) proposes an analysis that will verify the existence, and discover the source of a hypothesized bias in the Computed Air Release Point (CARP) planned by the Consolidated Airdrop Tool (CAT). Historical airdrop data, (some of which MORSE has already processed) will be used to conduct this analysis and produce a bias and error budget. MORSE will then create an adaptive, machine learning tool called the Bayesian N-Dimensional Aerial Delivery Estimator (BNDADE). This tool will correlate historical airdrop data to real-time data in order to estimate bias and provide the aircrew with a real-time adjustment to the planned CARP. BNDADE will consist of three main components: a Bayesian estimator, a bias predictor, and a path planning graphical user interface. BENEFIT:The proposed BNDADE tool will enable the observation of Computed Air Release Point (CARP) bias, and correction of this bias. Ultimately, this will result in improved airdrop accuracy. The tool will initially be developed as a stand-alone application, and will provide a correction to the Consolidated Airdrop Tool (CAT) generated CARP. Future insertion of the BNDADE tool into CAT is readily achievable, and provides the most likely transition path for commercialization within the DoD. MORSE staff included in this proposal have significant experience working with the US Air Force and Jacobs-Tybrin developing and integrating new CAT features.