An approach for aeroacoustic footprint-modeling of low altitude platforms by means of time domain system identification

The work done in this study is motivated by an emerging civil market for low flying unmanned platforms, accompanied by more stringent requirements on this novel type of aircraft from a manufacturer's as well as from an operator's point of view. It presents a way to time efficiently derive an empirical noise model for UAV (Unmanned Aerial Vehicle) applications based on system identification techniques in combination with inflight measurements. The resulting acoustic model is tailored to online operations together with tactical onboard algorithms. This interconnection enables future UAV developments to perform noise abatement procedures for highly demanding low-flight missions in real-time. Furthermore, it can be shown that the model-based approach allows for validations of theoretical aircraft noise prediction methods and aeroacoustic design routines as well.