Noise power spectral density scaled SNR response estimation with restricted range search for sound source localisation using unmanned aerial vehicles

Abstract A method to locate sound sources using an audio recording system mounted on an unmanned aerial vehicle (UAV) is proposed. The method introduces extension algorithms to apply on top of a baseline approach, which performs localisation by estimating the peak signal-to-noise ratio (SNR) response in the time-frequency and angular spectra with the time difference of arrival information. The proposed extensions include a noise reduction and a post-processing algorithm to address the challenges in a UAV setting. The noise reduction algorithm reduces influences of UAV rotor noise on localisation performance, by scaling the SNR response using power spectral density of the UAV rotor noise, estimated using a denoising autoencoder. For the source tracking problem, an angular spectral range restricted peak search and link post-processing algorithm is also proposed to filter out incorrect location estimates along the localisation path. Experimental results show the proposed extensions yielded improvements in locating the target sound source correctly, with a 0.0064–0.175 decrease in mean haversine distance error across various UAV operating scenarios. The proposed method also shows a reduction in unexpected location estimations, with a 0.0037–0.185 decrease in the 0.75 quartile haversine distance error.

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Estimating Power Spectral Density of Unmanned Aerial Vehicle Rotor Noise Using Multisensory Information

2018 26th European Signal Processing Conference (EUSIPCO) ◽

10.23919/eusipco.2018.8553140 ◽

2018 ◽

Author(s):

Benjamin Yen ◽

Yusuke Hioka ◽

Brian Mace

Keyword(s):

Spectral Density ◽

Power Spectral Density ◽

Unmanned Aerial Vehicle ◽

Rotor Noise ◽

Power Spectral ◽

Aerial Vehicle ◽

Multisensory Information

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Noise power spectral density estimation for binaural noise reduction exploiting direction of arrival estimates

2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) ◽

10.1109/waspaa.2017.8170030 ◽

2017 ◽

Cited By ~ 7

Author(s):

Daniel Marquardt ◽

Simon Doclo

Keyword(s):

Spectral Density ◽

Noise Reduction ◽

Density Estimation ◽

Power Spectral Density ◽

Noise Power ◽

Spectral Density Estimation ◽

Noise Power Spectral Density ◽

Power Spectral ◽

Binaural Noise Reduction ◽

Power Spectral Density Estimation

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Time-Frequency Analysis of Daily Activities for Fall Detection

Signals ◽

10.3390/signals2010001 ◽

2021 ◽

Vol 2 (1) ◽

pp. 1-12

Author(s):

Quoc T. Huynh ◽

Binh Q. Tran

Keyword(s):

Spectral Density ◽

Power Spectral Density ◽

Frequency Analysis ◽

Fall Detection ◽

Detection Sensitivity ◽

Daily Activities ◽

Activity Data ◽

Time Frequency Analysis ◽

Time Frequency ◽

Power Spectral

Fall events in elderly populations often result in serious injury and may lead to long-term disability and/or death. While many fall detection systems have been developed using wearable sensors to distinguish falls from other daily activities, detection sensitivity and specificity decreases when exposed to more rigorous activities such as running and jumping. This research uses time-frequency analysis of accelerometer-only activity data to develop a strategy for improving fall detection accuracy. In this study, a wireless sensor system (WSS) consisting of a three-axis accelerometer, microprocessor and wireless communications module is used to collect daily activities performed following a script in the laboratory setting. Experiments were conducted on 36 healthy human subjects performing four types of falls (i.e., forward, backward, and left/right sideway falls) as well as normal movements such as standing, walking, stand-to-sit, sit-to-stand, stepping, running and jumping. In total, 1227 different activities were collected and analyzed. The developed algorithm computes the magnitude of three-axis accelerometer data to detect if a critical fall threshold is passed, then analyzes the power spectral density within a critical fall duration window (500 ms) to differentiate fall events from other rigorous activities. Fall events were observed with high energy in the 2–3.5 Hz range and distinct from other rigorous activities such as running (3.5–5.5 Hz) and jumping (1–2 Hz). Preliminary results indicate the power spectral density (PSD)-based algorithm can detect falls with high sensitivity (98.4%) and specificity (98.6%) using lab-based daily activity data. The proposed algorithm has the benefit of improved accuracy over existing time-domain only strategies and multisensor strategies.

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Development of Gas-Liquid Slug Flow Measurement Using Continuous-Wave Doppler Ultrasound and Bandpass Power Spectral Density

ChemEngineering ◽

10.3390/chemengineering5010002 ◽

2021 ◽

Vol 5 (1) ◽

pp. 2

Author(s):

Somtochukwu Godfrey Nnabuife ◽

Prafull Sharma ◽

Ebuwa Iyore Aburime ◽

Pauline Long’or Lokidor ◽

Abdulrauf Bello

Keyword(s):

Multiphase Flow ◽

Spectral Density ◽

Power Spectral Density ◽

Doppler Ultrasound ◽

Continuous Wave ◽

Test Facility ◽

Internal Diameter ◽

Time Frequency ◽

Continuous Wave Doppler ◽

Power Spectral

This paper addresses the issues of slug detection and characterization in air-water two-phase flow in a vertical pipeline. A novel non-invasive measurement technique using continuous-wave Doppler ultrasound (CWDU) and bandpass power spectral density (BPSD) is proposed for multiphase flow applications and compared with the more established gamma-ray densitometry measurement. In this work, analysis using time-frequency analysis of the CWDU is performed to infer the applicability of the BPSD method for observing the slug front and trailing bubbles in a multiphase flow. The CWDU used a piezo transmitter/receiver pair with an ultrasonic frequency of 500 kHz. Signal processing on the demodulated signal of Doppler frequency was done using the Butterworth bandpass filter on the power spectral density which reveals slugs from background bubbles. The experiments were carried out in the 2” vertical pipeline-riser at the process system engineering laboratory at Cranfield University. The 2-inch test facility used in this experiment is made up of a 54.8 mm internal diameter and 10.5 m high vertical riser connected to a 40 m long horizontal pipeline. Taylor bubbles were generated using a quick-closing air valve placed at the bottom of the riser underwater flow, with rates of 0.5 litres/s, 2 litres/s, and 4 litres/s. The CWDU spectrum of the measured signal along with the BPSD method is shown to describe the distinctive nature of the slugs.

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