DroneEARS: Robust Acoustic Source Localization with Aerial Drones

Misra, Prasant; Kumar, Anil; Mohapatra, Pragyan; Balamuralidhar, P.

doi:10.1109/icra.2018.8461223

Cited by 6 publications

(6 citation statements)

References 14 publications

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“…Since microphone arrays are generally used for direction estimation, additional measures should be taken to obtain the sound source location. One approach is to move around the sound source and observe the sound source from multiple points of view [14][15][16]. By projecting directional spectrum to a 2D/3D field, we can obtain the locational spectrum and estimate the source location.…”

Section: Sound Source Tracking Using Microphone Arraysmentioning

confidence: 99%

Placement Planning for Sound Source Tracking in Active Drone Audition

Yamada

Itoyama

Nishida

et al. 2023

Drones

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This paper addresses a placement planning method for drones to improve the performance of source tracking by multiple drones equipped with microphone arrays. By equipping the drone with a microphone array, the drone will be able to locate the person in need of rescue, and by deploying multiple drones, the 3D location of the sound source can be estimated. However, effective drone placement for sound source tracking has not been well explored. Therefore, this paper proposes a new drone placement planning method to improve the performance of sound source tracking. By placing multiple drones close to the sound source with multiple angles, it is expected that tracking will be performed with small variance. The placement planning algorithm is also extended to be applicable to multiple sound sources. Through numerical simulations, it is confirmed that the proposed method reduces the sound source tracking error. In conclusion, the contribution of this research is to extend the field of drone audition to active drone audition that allows drones to move by themselves to achieve better tracking results.

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Section: Sound Source Tracking Using Microphone Arraysmentioning

confidence: 99%

Placement Planning for Sound Source Tracking in Active Drone Audition

Yamada

Itoyama

Nishida

et al. 2023

Drones

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“…Sasaki et al [5] and Su et al [6] presented 3D sound source localization algorithms using a disk-shaped sound detector and a linear microphone array such as Kinect and PS3 Eye. Misra et al [7] suggested a robust localization method in noisy environments using a drone. This approach requires the accumulation of steady acoustic signals at different positions, and thus cannot be applied to a transient sound event or to stationary sound detectors.…”

Section: Related Workmentioning

confidence: 99%

“…Recently, many techniques have been proposed to estimate the location of a sound source [5], [6], [7]. Sasaki et al [5] and Su et al [6] presented 3D sound source localization algorithms using a disk-shaped sound detector and a linear microphone array such as Kinect and PS3 Eye.…”

Section: Related Workmentioning

confidence: 99%

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Diffraction-Aware Sound Localization for a Non-Line-of-Sight Source

Lee

Choi

et al. 2019

2019 International Conference on Robotics and Automation (ICRA)

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We present a novel sound localization algorithm for a non-line-of-sight (NLOS) sound source in indoor environments. Our approach exploits the diffraction properties of sound waves as they bend around a barrier or an obstacle in the scene. We combine a ray tracing based sound propagation algorithm with a Uniform Theory of Diffraction (UTD) model, which simulate bending effects by placing a virtual sound source on a wedge in the environment. We precompute the wedges of a reconstructed mesh of an indoor scene and use them to generate diffraction acoustic rays to localize the 3D position of the source. Our method identifies the convergence region of those generated acoustic rays as the estimated source position based on a particle filter. We have evaluated our algorithm in multiple scenarios consisting of a static and dynamic NLOS sound source. In our tested cases, our approach can localize a source position with an average accuracy error, 0.7m, measured by the L2 distance between estimated and actual source locations in a 7m×7m×3m room. Furthermore, we observe 37% to 130% improvement in accuracy over a state-of-the-art localization method that does not model diffraction effects, especially when a sound source is not visible to the robot.

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“…In [24,25], the authors studied how to attach microphone arrays to drones and embedded systems for signal acquisition. In [26][27][28], the authors presented an arrival angle detection algorithm for sound sources based on beamforming. In addition, valid results for the detection of sound sources were shown through verification experiments on near-field sound sources in a well-refined indoor environment.…”

Section: Introductionmentioning

confidence: 99%

An Acoustic Source Localization Method Using a Drone-Mounted Phased Microphone Array

Choi

2021

Drones

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Currently, the detection of targets using drone-mounted imaging equipment is a very useful technique and is being utilized in many areas. In this study, we focus on acoustic signal detection with a drone detecting targets where sounds occur, unlike image-based detection. We implement a system in which a drone detects acoustic sources above the ground by applying a phase difference microphone array technique. Localization methods of acoustic sources are based on beamforming methods. The background and self-induced noise that is generated when a drone flies reduces the signal-to-noise ratio for detecting acoustic signals of interest, making it difficult to analyze signal characteristics. Furthermore, the strongly correlated noise, generated when a propeller rotates, acts as a factor that degrades the noise source direction of arrival estimation performance of the beamforming method. Spectral reduction methods have been effective in reducing noise by adjusting to specific frequencies in acoustically very harsh situations where drones are always exposed to their own noise. Since the direction of arrival of acoustic sources estimated from the beamforming method is based on the drone’s body frame coordinate system, we implement a method to estimate acoustic sources above the ground by fusing flight information output from the drone’s flight navigation system. The proposed method for estimating acoustic sources above the ground is experimentally validated by a drone equipped with a 32-channel time-synchronized MEMS microphone array. Additionally, the verification of the sound source location detection method was limited to the explosion sound generated from the fireworks. We confirm that the acoustic source location can be detected with an error performance of approximately 10 degrees of azimuth and elevation at the ground distance of about 150 m between the drone and the explosion location.

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DroneEARS: Robust Acoustic Source Localization with Aerial Drones

Cited by 6 publications

References 14 publications

Placement Planning for Sound Source Tracking in Active Drone Audition

Placement Planning for Sound Source Tracking in Active Drone Audition

Diffraction-Aware Sound Localization for a Non-Line-of-Sight Source

An Acoustic Source Localization Method Using a Drone-Mounted Phased Microphone Array

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