This study covers three aspects of acoustic localisation of drones using a microphone array. First, it assesses a grid-free approach, using differential evolution, to estimate the three-dimensional position of a drone. It is found that this is indeed possible for the drone in the near-field. For larger distances, it still provides the angular position of the drone. Second, the study emphasizes the essence of localisation over small frequency bands with the bands jointly spanning a large frequency range to reveal the presence of multiple sound sources and maximise the drone localisation range. Third, it addresses the localisation ranges for six different drones.

Correction Notice The authors would like to provide the following corrections and clarifications to the article titled “Aeroacoustic Benchmarking of Trailing-edge Noise from a NACA 633–018 Airfoil with Trailing-edge Serrations” which has been published in the AIAA Journal Vol. 61, No. 1, and can be accessed online via https://doi.org/10.2514/1.J061630. The first correction provides clarity in the abstract. Although the main text and Appendices A and B of the original paper provide a thorough analysis of the varying signal-to-noise levels and clearly state that some data points with inherently high noise levels should be excluded in further analysis, the statement in the abstract could lead to misunderstanding that all data points will directly be included in the benchmark activities. It indeed is up to a broader benchmarking team, after considering results among different institutions, to decide which parts of the present dataset will eventually be included. Therefore, for clarity, the text “ ::: The present data are to be included in the framework of the Benchmark Problems for Airframe Noise Computation ::: ” should be replaced by “ ::: The present data are to be considered among participating institutions and may partially be included in the framework of the Benchmark Problems for Airframe Noise Computation ::: ”. The second correction pertains to the manufacturer of the so-called High-Reynolds Model (HRM) airfoil and a reference mentioned in the second paragraph of Sec. II.A. The text “ ::: manufactured by Deharde ::: [23]” should be “ ::: manufactured by RIVAL ::: [23]”. The part of the model considered in this paper was manufactured by RIVAL and Deharde later produced the spanwise extensions for this model to fit in other larger wind tunnels. The authors apologize for this miscommunication. Besides, Ref. [23] in the original paper should be replaced by Ref. [1] of this correction. During the publication process of our paper, this new reference was published and the original Ref. [23] was updated. Therefore, Ref. [1] of this correction provides up-to-date information about the model and is therefore worth referring to. (Figures Presented) The final correction pertains to the plots in Figs. 13 and 15 in the original article. The legends went missing during the production process. Figures 13 and 15 in the original article should appear as Figs. 1 and 2 in this correction, respectively, with the legends on the right side. The authors apologize for this error.

Threats posed by drones urge defence sectors worldwide to develop drone detection systems. Visible-light and infrared cameras complement other sensors in detecting and identifying drones. Application of Convolutional Neural Networks (CNNs), such as the You Only Look Once (YOLO) algorithm, are known to help detect drones in video footage captured by the cameras quickly, and to robustly differentiate drones from other flying objects such as birds, thus avoiding false positives. However, using still video frames for training the CNN may lead to low drone-background contrast when it is flying in front of clutter, and omission of useful temporal data such as the flight trajectory. This deteriorates the drone detection performance, especially when the distance to the target increases. This work proposes to pre-process the video frames using a Bio-Inspired Vision (BIV) model of insects, and to concatenate the pre-processed video frame with the still frame as input for the CNN. The BIV model uses information from preceding frames to enhance the moving target-to-background contrast and embody the target’s recent trajectory in the input frames. An open benchmark dataset containing infrared videos of small drones (< 25 kg) and other flying objects is used to train and test the proposed methodology. Results show that, at a high sensor-to-target distance, the YOLO algorithms trained on BIV-processed frames and concatenation of the BIV-processed frames with still frames increase the Average Precision (AP) to 0.92 and 0.88, respectively, compared to 0.83 when it is trained on still frames alone.

Experimental results on trailing-edge (TE) noise from a NACA 63₃ –018 airfoil are presented for a chord-based Reynolds number Re_c range between 2 × 10⁵ and 3 × 10⁶. Far-field TE noise from the baseline airfoil with a straight TE and TE serrations is measured with varying Re_c, angle of attack, and serration shape and flap angle. Additionally, aerodynamic coefficients and boundary-layer parameters at the TE are also reported. To cover such a broad Re_c range, two NACA 63₃ –018 airfoil models were tested in two different wind tunnels. The measurements include the emitted noise with natural and forced transition locations. For the straight TE, the forced transition location results in up to 5 dB increase of the far-field TE noise level, compared to the natural one. Scaling of the far-field noise spectra from the baseline TE shows that the Strouhal numbers St at which the peak noise level is measured reduce as Re_c increases. TE noise spectra for the cases with the TE serrations are found to be dependent on the airfoil lift and Re_c. The present data are to be included in the framework of the Benchmark Problems for Airframe Noise Computations category I and are publicly available in a repository with the following digital object identifier (DOI): https://doi.org/10.4121/20940646.

An experimental aero-acoustic characterisation of the NACA 63 ₃-018 airfoil is presented in this study, featuring trailing-edge noise emissions with and without serrations. Measurements have been carried out for a chord-based Reynolds number range between 0.18 × 10 ⁶ and 4.8 × 10 ⁶ . Two airfoil models with different chord lengths have been tested in five different wind tunnels. The goal is to compare the measurements in different facilities, quantify the uncertainties, and establish a validation database that can serve as a benchmark for computational studies. The tests have been performed with clean and forced-transition boundary layers for a variety of angles of attack. The effect on the spectral slope and peak levels is evaluated. Scaling laws have been applied to compare different test conditions. The quality and nature of the collapse, as well as the applicability limits of the scaling, are examined. Different serration geometries have been tested at different flap angles. The noise reduction dependence on the aerodynamic loading is discussed. This work is based on an initiative of Task 39 "Quiet Wind Turbine Technology" of the Technology Collaboration Programme (TCP) of the International Energy Agency (IEA).

This study focuses upon a new permeable topology design concept as an alternative to porous metal foams, for turbulent boundary layer trailing-edge (TBL-TE) noise attenuation. The present permeable topology has unconventional characteristics with respect to the metal foams: a combination of low flow resistivity r and high form drag coefficient C. The unconventional characteristics are realized by a Kevlar-covered 3D-printed perforated structure. An experimental study featuring a NACA 0018 airfoil model with a Kevlar-covered 3D-printed TE insert at chord-based Reynolds numbers up to (Formula presented.) is carried out. The airfoil with this TE insert gives a broadband TBL-TE noise reduction up to approximately 5 dB, compared to a solid TE. This reduction varies only slightly with airfoil loading (lower than 1 dB variation), in contrast to the porous metal foams (up to 3 dB variation). When comparing the variation of noise attenuation given by all the permeable materials considered, the variation is found to decrease with the increasing C. This is because C specifies the permeable material's ability to withstand the increasing pressure difference, which causes cross flow that might interfere with the noise attenuation mechanism. Additionally, the drag coefficients as well as the roughness noise of the airfoil equipped with the present TE insert are also significantly lower than those of the metal-foam TE, and are mostly negligible compared to the fully solid airfoil. Based on the findings, design guidelines for permeable TE are proposed: the permeable material shall have a combination of a low flow resistivity and a high form drag coefficient as well as a negligible surface roughness.

In this paper, the performance of four acoustic imaging methods: conventional frequency domain beamforming (CFDBF), functional beamforming (FUNBF), enhanced high resolution CLEAN–SC (EHR–CLEAN–SC) and generalized inverse beamforming (GIBF), is investigated in terms of accuracy and variability. Three experimental test cases are considered: 1) a single speaker emitting synthetic broadband noise, 2) two speakers emitting incoherent synthetic broadband noise, and 3) trailing–edge noise generated by a tripped NACA 0018 airfoil. All the measurements were performed in the anechoic wind tunnel of Delft University of Technology. Overall, GIBF and EHR–CLEAN–SC offer the most accurate results when point sources (speakers) are present. They even achieve super–resolution by separating sound sources beyond the Rayleigh resolution limit. Repeating the measurements indicates a standard deviation in the results of less than 1 dB. When analyzing distributed sound sources, such as trailing–edge noise, CFDBF and FUNBF provide the best performance. This indicates that the acoustic imaging method needs to be selected based on the expected sound source configuration.

The recently introduced high-resolution (HR)-CLEAN-SC algorithm for acoustic imaging provides ‘super-resolution’, i.e. the ability to discern sound sources located closer than the Rayleigh resolution limit. This is achieved by allowing the source markers to be relocated from the actual source locations within a certain constraint to avoid the combined influence of the other sound sources. The freedom to relocate the source markers to increase the performance of the algorithm depends on the maximum sidelobe level of the acoustic array used. This paper presents an ‘enhanced’ version of the HR-CLEAN-SC algorithm which benefits from low maximum sidelobe level array design. The source marker constraint μ is adapted to the maximum sidelobe level at each frequency. Application to up to four synthetic sound sources shows that the sources can be resolved at half the frequency associated with the Rayleigh resolution limit, when an acoustic array optimized for low maximum sidelobe level is used in combination with Enhanced HR-CLEAN-SC. This improves source discrimination compared to when the HR-CLEAN-SC algorithm is used with a benchmark acoustic array design. The results are confirmed by experimental validation in which up to four loudspeakers and the same array configurations as in the synthesized data case are used.

Most acoustic imaging methods assume the presence of point sound sources and, hence, may fail to correctly estimate the sound emissions of distributed sound sources, such as trailing-edge noise. In this contribution, three integration techniques are suggested to overcome this issue based on models considering a single point source, a line source, and several line sources, respectively. Two simulated benchmark cases featuring distributed sound sources are employed to compare the performance of these integration techniques with respect to other well-known acoustic imaging methods. The considered integration methods provide the best performance in retrieving the source levels and require short computation times. In addition, the negative effects of the presence of unwanted noise sources, such as corner sources in wind-tunnel measurements, can be eliminated. A sensitivity analysis shows that the integration technique based on a line source is robust with respect to the choice of the integration area (shape, position, and mesh fineness). This technique is applied to a trailing-edge-noise experiment in an open-jet wind tunnel featuring a NACA 0018 airfoil. The location and far-field noise emissions of the trailing-edge line source were calculated.

Studies on porous trailing edges, manufactured with open-cell Ni-Cr-Al foams with sub-millimeter pore sizes, have shown encouraging results for the mitigation of turbulent boundary-layer trailing-edge noise. However, the achieved noise mitigation is typically dependent upon the pore geometry, which is fixed after manufacturing. In this study, a step to control the aeroacoustics effect of such porous trailing edges is taken, by applying a polymeric coating onto the internal foam structure. Using this method, the internal topology of the foam is maintained, but its permeability is significantly affected. This study opens a new possibility of aeroacoustic control, since the polymeric coatings are temperature responsive, and their thickness can be controlled inside the foam. Porous metallic foams with pore sizes of 580, 800, and 1200 μm are (internally) spray-coated with an elastomeric coating. The uncoated and coated foams are characterized in terms of reduced porosity, average coating thickness and air-flow resistance. Subsequently, the coated and uncoated foams are employed to construct tapered inserts installed at the trailing edge of an NACA 0018 airfoil. The noise mitigation performances of the coated metal foams are compared to those of uncoated metal foams with either similar pore size or permeability value, and both are compared to the solid trailing edge reference case. Results show that that the permeability of the foam can be easily altered by the application of an internal coating on the metallic foams. The noise reduction characteristics of the coated foams are similar to equivalent ones with metallic materials, provided that the coating material is rigid enough not to plastically deform under flow conditions.