8
ments of acoustic velocity and pressure ce localization using acoustic intensit Literature Survey Presentation Khalid Miah MD-DSP 05/05/05

Measurements of acoustic velocity and pressure vectors

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Measurements of acoustic velocity and pressure vectors in source localization using acoustic intensity sensor. Literature Survey Presentation Khalid Miah MD-DSP 05/05/05. INTRODUCTION. Estimation of DOA (direction of arrival) of a single source - PowerPoint PPT Presentation

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Page 1: Measurements of acoustic velocity and pressure vectors

Measurements of acoustic velocity and pressure vectorsin source localization using acoustic intensity sensor

Literature Survey Presentation Khalid Miah

MD-DSP05/05/05

Page 2: Measurements of acoustic velocity and pressure vectors

INTRODUCTION

• Estimation of DOA (direction of arrival) of a single source using vector natured Acoustic intensity measurements

• MSAE (Mean Square Angular Error)

• Free Space and Reflecting boundary case

Page 3: Measurements of acoustic velocity and pressure vectors

• Statistical Distributions of acoustic quantities are independent of the shape of the room boundaries and arrangements [Budhianto & Hixson,1996]

• Traditional Acoustic intensity measurements using scalar sensors is ineffective in terms of source localization

Statistical Distributions of Fundamental AcousticQuantities (Pressure/Particle velocity/Intensity)

Page 4: Measurements of acoustic velocity and pressure vectors

Single-Source Single Vector sensor measurements for DOA estimation in Free Space

• 4-D Intensity Based Algorithm [ Nehorai & Paldi, 1994]

- Key Assumptions: Plane wave at the sensor, Band limited Signal Spectrum - MSAE = 1+/v p where v = s

2 /2v and p = s

2 /2p

- MSAE is nearly optimal

• 3-D Velocity-Covariance-Based Algorithm - Use Covariance matrix to estimate u - MSAE = = -1 + -2 where = v [ Nehorai & Paldi, 1993]

- MSAE is optimal in Gaussian noise case

Page 5: Measurements of acoustic velocity and pressure vectors

Measurements for DOA estimation using Intensity based Algorithm in Reflecting boundary case

• Key assumptions: Single bandlimited acoustic source radiating bandlimited spherical waves (different from free space case)

• The image Source is obtained by reflecting the original source in boundary (which adds Reflection Coefficient in the calculations)

• MSAE is calculated under the assumption that both signal and noise has Gaussian distributions

• MSAE is a function of SNR and the elevation angle [Hawkes & Nehorai, 2003]

Page 6: Measurements of acoustic velocity and pressure vectors

SOURCE

Microphone Array

Four Element Microphone Array Setup

x

y

z

[B. Kirkwood, 2003]

oo

y

x

z

Page 7: Measurements of acoustic velocity and pressure vectors

DOA estimation using Intensity based velocity vector sensors and Pressure sensors

Free-Space Scenario Reflecting Boundary Case

[Hawkes & Nehorai, 2000]Incidence Angle

Page 8: Measurements of acoustic velocity and pressure vectors

Implementation of Different Methods

Bad: Any experimental data and/or software/source code were not available for third party use.

Not too Bad: A Four-element single vector sensor array with “medieval” DAQ board and barely obsolete software (runs on WIN3.x) is available in Eletroacoustic Research lab. (ENS 630)