In this article, I introduce a novel airborne network mobility model, called the Smooth Turn Mobility Model, that captures the correlation of acceleration for airborne vehicles across time and spatial coordinates. E?ective routing in airborne networks (ANs) relies on suitable mobility models that capture the random movement pattern of airborne vehicles. As airborne vehicles cannot make sharp turns as easily as ground vehicles do, the widely used mobility models for Mobile Ad Hoc Networks such as Random Waypoint and Random Direction models fail. Our model is realistic in capturing the tendency of airborne vehicles toward making straight trajectory and smooth turns with large radius, and whereas is simple enough for tractable connectivity analysis and routing design.

Mobility models serve as the foundation for evaluating and designing airborne networks. Due to the significant impact of mobility models on the network performance, mobility models for airborne networks (ANs) must realistically capture the attributes of ANs. In this paper, I develop a comprehensive modeling framework for ANs. The work I have done is concluded as the following three parts. First, I perform a comprehensive and comparative analysis of AN mobility models and evaluate the models based on several metrics: 1) networking performance, 2) ability to capture the mobility attributes of ANs, 3) randomness levels and 4) associated applications. Second, I develop two 3D mobility models and realistic boundary models. The mobility models follow physical laws behind aircraft maneuvering and therefore capture the characteristics of aircraft trajectories. Third, I suggest an estimation procedure to extract parameters in one of the models that I developed from real flight test data. The good match between the estimated trajectories and real flight trajectories also validate the suitability of the model. The mobility models and the estimation procedure lead to the creation of “realistic” simulation and evaluation environment for airborne networks.