This work describes the testing involved in generating an acoustic signature profile of a small multi-rotor unmanned aircraft system. A typical multi-rotor unmanned aircraft system, with a weight of approximately 2.1 kg, was used for sound pressure level measurements. This study established a relationship between distance, altitude and sound pressure level, finding that the sound decays approximately in line with 6 dB(A) reduction for a doubling of distance. The effect of the orientation of the multi-rotor unmanned aircraft system was also investigated. It was determined that the sound profile does not vary significantly around the periphery of the multi-rotor unmanned aircraft system in the propellerplane. However, when measured with the observer underneath the multi-rotor unmanned aircraft system, the sound pressure level was found to vary by as much as 10 dB(A), with the greatest sound pressure level at approximately 45 from horizontal. Finally, an acoustic array was used to measure key frequencies for the main sound sources: motors and propellers. It was found that extraneous noise from the multi-rotor unmanned aircraft system frame vibration and mounting methods was also common. Despite relatively low levels of sound being measured (especially when compared with conventional aircraft and rotorcraft), the increasing numbers of unmanned aircraft systems in urban environments, close to humans and dwellings, suggests that increasing complaints are likely. Thus, further research was suggested, including expanding the range of multi-rotor unmanned aircraft system to be tested, introducing DGPS, improving the mounting for indoor testing, and psychoacoustic analysis of the sound.
This paper addresses one of the recognized barriers to the unrestricted adoption of Unmanned Aircraft (UA) in mainstream urban use—noise—and reviews existing approaches for estimating and mitigating this problem. The aircraft noise problem is discussed upfront in general terms by introducing the sound emission, propagation, and psychoacoustic effects. The propagation of sound in the atmosphere, which is the focus of this paper, is then analysed in detail to isolate the environmental and operational factors that predominantly influence the perceived noise on the ground, especially looking at large-scale low-altitude UA operations, such as in the envisioned Urban Air Mobility (UAM) concepts. The physics of sound propagation are presented, considering all attenuation effects and the anomalies due to Doppler and atmospheric effects, such as wind, thermal inversion, and turbulence. The analysis allows to highlight the limitations of current mainstream aircraft noise modelling and certification approaches and, in particular, their inadequacy in addressing the noise of UA and, more generally, UAM vehicles. This finding is important considering that, although reducing noise at the source has remained a priority for manufacturers to enable the scaling up of UAM and drone delivery operations in the near future, the impact of poorly considered propagation and psychoacoustic effects on the actual perceived noise on the ground is equally important for the same objective. For instance, optimizing the flight paths as a function of local weather conditions can significantly contribute to minimizing the impact of noise on communities, thus paving the way for the introduction of full-scale UAM operations. A more reliable and accurate modelling of noise ground signatures for both manned and unmanned low-flying aircraft will aid in identifying the real-time data stream requirements from distributed sensors on the ground. New developments in surrogate sound propagation models, more pervasive real-time sensor data, and suitable computing resources are expected to both yield more reliable and effective estimates of noise reaching the ground listeners and support a dynamic planning of flight paths.
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