Enhanced situation awareness for unmanned aerial vehicle operating in terminal areas with circuit flight rules

This paper considers the situation awareness function associated with an unmanned aerial vehicle arriving at an uncontrolled airfield. Given no air traffic control service available within such a terminal area, the unmanned aerial vehicle needs to establish a good level of situation awareness by using its onboard sensors to detect and track other traffic aircraft. Comparing to the existing works which mainly use sensor observations in the filtering process, this paper exploits the circuit flight rules to provide extra knowledge about the target behaviour. This is achieved by using multiple models to describe the target motions in different flight phases and characterising the phase transition in a stochastic manner. Consequently, an interacting multiple model particle filter with state-dependent transition probabilities is developed to provide the required situation awareness function.