Tracking and Characterization of Aircraft Wakes Using Acoustic and Lidar Measurements

Booth, Earl R.; Humphreys, William M.

doi:10.2514/6.2005-2964

Cited by 5 publications

(6 citation statements)

References 9 publications

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“…The various candidate technologies for wake vortex detection have been summarized in [34]. Although optical detection techniques such as LIDAR are often used [35], they have many shortcomings. Optics-based detection offers undeniable advantages, but these technologies are particularly problematic in difficult atmospheric conditions such as rain or snow.…”

Section: Contextmentioning

confidence: 99%

“…Wake vortices have been shown to emit noise. The wake vortices were successfully identified using their acoustic emission captured on a phased array in a number of test campaigns, including at Berlin's Airport Schönefeld [86] and Denver International airport [35,87,88]. The exact sources and mechanisms of aeroacoustic noise from the vortex remain subject to debate, but Hardin and Yang [73] noted the following likely sources:…”

Section: Acoustic Models For Vortex Soundmentioning

confidence: 99%

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Recent Advances in Passive Acoustic Localization Methods via Aircraft and Wake Vortex Aeroacoustics

Joshi

Rahman

Hickey

2022

Fluids

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Passive acoustic aircraft and wake localization methods rely on the noise emission from aircraft and their wakes for detection, tracking, and characterization. This paper takes a holistic approach to passive acoustic methods and first presents a systematic bibliographic review of aeroacoustic noise of aircraft and drones, followed by a summary of sound generation of wing tip vortices. The propagation of the sound through the atmosphere is then summarized. Passive acoustic localization techniques utilize an array of microphones along with the known character of the aeroacoustic noise source to determine the characteristics of the aircraft or its wake. This paper summarizes the current state of knowledge of acoustic localization with an emphasis on beamforming and machine learning techniques. This review brings together the fields of aeroacoustics and acoustic-based detection the advance the passive acoustic localization techniques in aerospace.

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Section: Contextmentioning

confidence: 99%

Section: Acoustic Models For Vortex Soundmentioning

confidence: 99%

Recent Advances in Passive Acoustic Localization Methods via Aircraft and Wake Vortex Aeroacoustics

Joshi

Rahman

Hickey

2022

Fluids

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“…This is followed by an approach on how this selection process might be automated using image processing algorithms. In the following example, data from the 252-element NASA-Volpe microphone array deployed in Denver during September of 2003 is considered 1,2,5,6,9 . This particular case refers to a landing 757 aircraft.…”

Section: Sample Applicationmentioning

confidence: 99%

“…However, when information about the signal composition of the wake is desired, special processing of the raw signal and not of the images produced from broadband microphone signals is needed. One approach to getting this information is using frequency domain beamforming to produce AIDMs corresponding to multiple narrow analysis bands 9 . However, this approach becomes computationally expensive when the signal analyzed is broadband.…”

Section: Introductionmentioning

confidence: 99%

Wake Acoustic Analysis and Image Decomposition via Beamforming of Microphone Signal Projections on Wavelet Subspaces

Wassaf

Volpe

Zhang

et al. 2006

12th AIAA/CEAS Aeroacoustics Conference (27th AIAA Aeroacoustics Conference)

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This paper describes the integration of wavelet analysis and time-domain beamforming of microphone array output signals for analyzing the acoustic emissions from airplane generated wake vortices. This integrated process provides visual and quantitative simultaneous information about the wake signal composition and array resolution for a particular wavelet subspace during a time interval, T. In the results section, an example is given on how image processing algorithms might be used to automate the extraction of this information and select the wavelet subspaces from which to perform image reconstruction. This process begins with the projection of all the microphone signals on wavelet multiresolution subspaces. The projections of these signals on the same wavelet subspace or scale are then beamformed to produce an image of the wake corresponding to that particular scale. Therefore for each time interval T, the process produces a number of images equal to that of the wavelet scales. This is equivalent to a more conventional Fourier-based idea of filtering the microphone signals with band-pass filters having non-uniform bandwidths then beamform in different sub-bands, but offers greater flexibility and enhanced computational speed. Results from both approaches will be shown, which ultimately illustrate the advantages of wavelet analysis over that of the Fourier-based analysis. Amongst the advantages are the speed of the decomposition and ease of the image reconstruction from selected subspaces aided by the perfect reconstruction and orthogonality properties of wavelet analysis.

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“…A non-traditional application of phased microphone arrays has recently been extended to the area of aircraft wake vortices. In particular, there is an ongoing effort to study the viability of using phased arrays to passively detect and track aircraft wake vortices [1][2][3][4][5][6] near airports in order to increase safety as well as more efficiently utilize existing runways. Such arrays and the associated signal processing are designed on the basis of ray theory in an ambient medium.…”

Section: Introductionmentioning

confidence: 99%

Atmospheric Effects on Microphone Array Analysis of Aircraft Vortex Sound

Wassaf

Hardin

Wang

2006

12th AIAA/CEAS Aeroacoustics Conference (27th AIAA Aeroacoustics Conference)

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This paper provides the basis of a comprehensive analysis of vortex sound propagation through the atmosphere in order to assess real atmospheric effects on acoustic array processing. Such effects may impact vortex localization accuracy and detection probability over longer distances. The paper shows that propagation through the atmosphere can significantly alter the propagation time of the rays from the source to the receiver from that which would be experienced in an ambient atmosphere. More importantly, it can also change the delay time between microphones on which the array processing is based. Implications of these results on the design and resolution of microphone arrays are discussed.

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Tracking and Characterization of Aircraft Wakes Using Acoustic and Lidar Measurements

Cited by 5 publications

References 9 publications

Recent Advances in Passive Acoustic Localization Methods via Aircraft and Wake Vortex Aeroacoustics

Recent Advances in Passive Acoustic Localization Methods via Aircraft and Wake Vortex Aeroacoustics

Wake Acoustic Analysis and Image Decomposition via Beamforming of Microphone Signal Projections on Wavelet Subspaces

Atmospheric Effects on Microphone Array Analysis of Aircraft Vortex Sound

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