Date of Award
12-2023
Document Type
Project
Degree Name
Master of Science in Computer Science
Department
School of Computer Science and Engineering
First Reader/Committee Chair
Khan, Bilal. Ph.D.
Abstract
This project is an exploration and implementation of an application using Machine Learning (ML) and Artificial Intelligence (AI) techniques which would be capable of automatically tuning Kalman-Filter parameters used in post-flight trajectory estimation software at Edwards Air Force Base (EAFB), CA. The scope of the work in this paper is to design and develop a skeleton application with modular design, where various AI/ML modules could be developed to plug-in to the application for tuning-switch prediction.
Recommended Citation
Wright, Peter, "Machine Learning for Kalman Filter Tuning Prediction in GPS/INS Trajectory Estimation" (2023). Electronic Theses, Projects, and Dissertations. 1830.
https://scholarworks.lib.csusb.edu/etd/1830