A stochastic analysis of state transitions in an air-space management system

This paper explores the application of stochastic process ideas to answer some fundamental questions about a state system which arises in the Mode Select Beacon System (Mode-S), an air-space management system. A series of models is developed, based on semi-Markov processes, population models, and Monte Carlo simulation. Computer programs in the APL programming language to implement the models and to process the resulting data are developed. The output of the models illuminate the behavior of the state system by providing predictions with confidence bounds about the movements of aircraft among the states over time.