Probability of detection of electric vehicles with and without added warning sounds.

Detection performance as a function of distance was measured for 16 subjects who pressed a button upon aurally detecting the approach of an electric vehicle. The vehicle was equipped with loudspeakers that broadcast one of four additive warning sounds. Other test conditions included two vehicle approach speeds [10 and 20 km/h (kph)] and two background noise conditions (55 and 60 dBA). All of the test warning sounds were designed to be compliant with FMVSS 141 proposed regulations in regard to the overall sound pressure levels around the vehicle and in 1/3 octave band levels. Previous work has provided detection results as average vehicle detection distance. This work provides the results as probability of detection (Pd) as a function of distance. The curves provide insight into the false alarm rate when the vehicle is far away from the listeners as well and the Pd at the mean detection distance. Results suggest that, although the test sounds provide an average detection distance that exceeds the National Highway Traffic Safety Administration minimum at the two test speeds, Pd is not always 100% at those distances, particularly at the 10 kph. At the higher speed of 20 kph, the tire-road interaction noise becomes dominant, and the detection range is greatly extended.

High-frequency soundfield microphone for the analysis of bat biosonar.

Numerous bat species emit wideband frequency-modulated signals for echolocation to hunt prey and avoid obstacles. Research investigating the behavioral and physiological responses of bats to echoes typically includes analysis of acoustic signals from microphones and/or microphone arrays, using time difference of arrival between array elements or the microphones to locate flying bats (azimuth and elevation). This has provided insight into transmission adaptations such as pulse duration and duty cycle with respect to target distance, clutter, and interferers. Microphones recording transmitted signals and echoes near a stationary bat provide sound pressure as a function of time but no directional information. In this work, the authors propose a spatial audio/soundfield microphone array to both track bats in flight and pinpoint the directions of echoes received by a bat. The authors introduce an ultrasonic (20-80 kHz) tetrahedral soundfield microphone to capture bat sounds up to 80 kHz. A spatial audio decoding technique called high angular resolution planewave expansion (HARPEx) supplies angle and elevation estimates, either for a flying bat based on the bat pulses or for targets based on echoes. Experiments using the soundfield microphone and HARPEx show that the approach accurately estimates the sound direction of arrival in both scenarios.

Acoustic source separation for the detection of coronary artery sounds.

Coronary artery disease (CAD) is the leading cause of death in the United States, being responsible for more than 20% of all deaths in the country. This is in large part due to the difficulty of diagnostic screening for CAD. Phonoangiography seeks to detect CAD via the acoustic signature associated with turbulent flow near an abnormally constricted, or stenosed, region. However, the usefulness of the technique is severely hindered by the low strength of the CAD signal compared to the background noise within the chest. In this work, acoustic finite element analysis (FEA) was performed on physiologically accurate chest geometries to demonstrate the feasibility of an original acoustic source separation methodology for isolating coronary sounds. This approach is based upon pseudoinversion of mixing matrices determined through a combination of experiment and computation. This allows calculation of the sound emitted by the coronary arteries based upon measurements of the acoustic velocity on the chest surface. This work demonstrates the feasibility of such a technique computationally and examines the vulnerability of the proposed approach to measurement errors.

Adaptive near-field beamforming techniques for sound source imaging.

Phased array signal processing techniques such as beamforming have a long history in applications such as sonar for detection and localization of far-field sound sources. Two sometimes competing challenges arise in any type of spatial processing; these are to minimize contributions from directions other than the look direction and minimize the width of the main lobe. To tackle this problem a large body of work has been devoted to the development of adaptive procedures that attempt to minimize side lobe contributions to the spatial processor output. In this paper, two adaptive beamforming procedures-minimum variance distorsionless response and weight optimization to minimize maximum side lobes--are modified for use in source visualization applications to estimate beamforming pressure and intensity using near-field pressure measurements. These adaptive techniques are compared to a fixed near-field focusing technique (both techniques use near-field beamforming weightings focusing at source locations estimated based on spherical wave array manifold vectors with spatial windows). Sound source resolution accuracies of near-field imaging procedures with different weighting strategies are compared using numerical simulations both in anechoic and reverberant environments with random measurement noise. Also, experimental results are given for near-field sound pressure measurements of an enclosed loudspeaker.

Blind deconvolution applied to acoustical systems identification with supporting experimental results.

Many acoustical applications require the analysis of a signal that is corrupted by an unknown filtering function. Examples arise in the areas of noise or vibration control, room acoustics, structural vibration analysis, and speech processing. Here, the observed signal can be modeled as the convolution of the desired signal with an unknown system impulse response. Blind deconvolution refers to the process of learning the inverse of this unknown impulse response and applying it to the observed signal to remove the filtering effects. Unlike classical deconvolution, which requires prior knowledge of the impulse response, blind deconvolution requires only reasonable prior estimates of the input signal's statistics. The significant contribution of this work lies in experimental verification of a blind deconvolution algorithm in the context of acoustical system identification. Previous experimental work concerning blind deconvolution in acoustics has been minimal, as previous literature concerning blind deconvolution uses computer simulated data. This paper examines experiments involving three classical acoustic systems: driven pipe, driven pipe with open side branch, and driven pipe with Helmholtz resonator side branch. Experimental results confirm that the deconvolution algorithm learns these systems' inverse impulse responses, and that application of these learned inverses removes the effects of the filters.