Evaluation of Flight Parameters During Approach and Landing Phases by Applying Principal Component Analysis

This paper adopts an unsupervised learning technique, Principal Component Analysis (PCA) to analyze flight data. While the flight parameters for a stable approach have been established for a while, the paper reevaluates these flight parameters using PCA for a set of airports across the United States of America. Some flight parameters were found to be more sensitive to some airports. The parameters have been cross-checked with experts in the industry to better interpret their significance.