In this paper, we present a calibration algorithm for acoustic vector sensors arranged in a uniform linear array configuration. To do so, we do not use a calibrator source, instead we leverage the Toeplitz blocks present in the data covariance matrix. We develop linear estimators for estimating sensor gains and phases. Further, we discuss the differences of the presented blind calibration approach for acoustic vector sensor arrays in comparison with the approach for acoustic pressure sensor arrays. In order to validate the proposed blind calibration algorithm, simulation results for direction-of-arrival (DOA) estimation with an uncalibrated and calibrated uniform linear array based on minimum variance distortion less response and multiple signal classification algorithms are presented. The calibration performance is analyzed using the Cramér-Rao lower bound of the DOA estimates.
Sound visualization techniques have played a key role in the development of acoustics throughout history. The development of measurement apparatus and techniques for displaying sound and vibration phenomena has provided excellent tools for building understanding about specific problems. Traditional methods, such as step-by-step measurements or simultaneous multichannel systems, have a strong tradeoff between time requirements, flexibility, and cost. However, if the sound field can be assumed time stationary, scanning methods allow us to assess variations across space with a single transducer, as long as the position of the sensor is known. The proposed technique, Scan and Paint, is based on the acquisition of sound pressure and particle velocity by manually moving a P-U probe (pressure-particle velocity sensors) across a sound field whilst filming the event with a camera. The sensor position is extracted by applying automatic color tracking to each frame of the recorded video. It is then possible to visualize sound variations across the space in terms of sound pressure, particle velocity, or acoustic intensity. In this paper, not only the theoretical foundations of the method, but also its practical applications are explored such as scanning transfer path analysis, source radiation characterization, operational deflection shapes, virtual phased arrays, material characterization, and acoustic intensity vector field mapping.
This paper presents the foundations of a unidirectional acoustic probe based on the particle velocity gradient. Highly directional characteristics play a key role in reducing the influence of undesired acoustic sources. These characteristics can be achieved by using multiple acoustic sensors in a spatial gradient arrangement. Two particle velocity sensors possessing the figure eight directivity pattern were used in a first-order gradient configuration to yield a unidirectional probe that can reject most excitations originating from both sides and the rear. The effects of key parameters are thoroughly discussed, and the proposed theory is validated in practice.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.