A two-step approach for the prediction of dynamic aircraft noise impact

Noise impact on surrounding areas of airports has become an important issue with direct consequence on their potential of development. Accurate predictions of the noise levels generated all around an airport area by approaching, landing and departing aircraft are necessary for the effective evaluation of the noise impact of new traffic scenarios as well as new departure/approach procedures. The noise levels associated to traffic scenarios have been computed in general using static models while applying an arbitrary night penalty to compute a daily noise impact index. In this communication a two-step approach to get predictions of the aircraft noise level time series at a given location is described. The proposed approach is based on the dynamic relations between aircraft flight parameters and the corresponding flyable 4D trajectories. First, the differential flatness property of flight guidance dynamics is used to generate from the considered 4D trajectories, the successive values of the main aircraft noise causal factors. These values are then submitted to a neural estimator which generates the prediction of the noise level evolution produced at a given location by an aircraft. Then summing up the effects of each nearby aircraft, the evolution of noise levels at the location can be predicted. The approach can easily be extended to a grid of points, thus providing noise levels estimation at any location in an airport vicinity.