Design model of microphone arrays for multirotor helicopters

Abstract

Unmanned multirotor helicopters have been expected for various critical tasks such as rescue missions, and it is important to sense the environment to achieve those tasks. In order to realize such sensor systems, this paper considers acoustic information recognition from a hovering helicopter which a microphone array system. As the noise of rotors distorts the acoustic information, noise reduction is necessary. Since the rotor noise varies even at the hovering flight, an acoustic model of the rotor noise is derived taking the dynamics of the helicopter into account, and the model is utilized to evaluate the performance of the microphone array. The proposed approach was verified by evaluating the optimality of a real device that was empirically tuned in authors previous work, and the computed configuration of the microphone array and the developed one coincide well, which ensures the validity of the approach. As the validation through a practical application, the signal was processed by Delay-and-Sum Beam Former to localize the sound source. The system was able to find peaks of the power that corresponded to the sound source.

Microphone-Array Ego-Noise Reduction Algorithms for Auditory Micro Aerial Vehicles

“…Unsupervised approaches perform ego-noise reduction using only the microphone signals. To date, only two types of unsupervised approaches have been applied to MAVs, namely fixed beamforming [24], [25] and blind source separation [16].…”

“…However, to obtain satisfactory noise reduction performance, this approach usually requires a large-size array, e.g. 16 microphones in an octagonal array with a diameter of around 2 m [24], [25]. Blind source separation (BSS) recovers unknown source signals from the observed mixture by blindly estimating a demixing network [33].…”

Ear in the sky: Ego-noise reduction for auditory micro aerial vehicles

“…SC Template-based spectral enhancement [10] MC Fixed beamforming [8,11] MC Reference-based noise reduction [7] 3. Noise component modelling…”

“…Multi-channel approaches mainly exploit the phase information and the correlation among multiple microphones for noise reduction. Delay-and-sum (fixed) beamforming was used for target sound acquisition with a microphone array, which was optimally designed in terms of array size and sensor placement [8,11]. Fixed beamforming is robust to low SNR and MAV movement.…”

Development of Robot Audition under Severe Conditions

“…quadrotor with 16 microphones and a result of sound source localization by flying around the sound source. Red and blue circles indicate the ground truth and estimated sound source localization, respectively[13].…”