A vector-sensor consisting of a monopole sensor collocated with orthogonally oriented dipole sensors is used for direction of arrival (DOA) estimation in the presence of an isotropic noise-field or internal device noise. A maximum likelihood (ML) DOA estimator is derived and subsequently shown to be a special case of DOA estimation by means of a search for the direction of maximum steered response power (SRP). The problem of SRP maximization with respect to a vector-sensor can be solved with a computationally inexpensive algorithm. The ML estimator achieves asymptotic efficiency and thus outperforms existing estimators with respect to the mean square angular error (MSAE) measure. The beampattern associated with the ML estimator is shown to be identical to that used by the minimum power distortionless response beamformer for the purpose of signal enhancement.
An acoustic vector sensor provides measurements of both the pressure and particle velocity of a sound field in which it is placed. These measurements are vectorial in nature and can be used for the purpose of source localization. A straightforward approach towards determining the direction of arrival (DOA) utilizes the acoustic intensity vector, which is the product of pressure and particle velocity. The accuracy of an intensity vector based DOA estimator in the presence of noise has been analyzed previously. In this paper, the effects of reverberation upon the accuracy of such a DOA estimator are examined. It is shown that particular realizations of reverberation differ from an ideal isotropically diffuse field, and induce an estimation bias which is dependent upon the room impulse responses (RIRs). The limited knowledge available pertaining the RIRs is expressed statistically by employing the diffuse qualities of reverberation to extend Polack's statistical RIR model. Expressions for evaluating the typical bias magnitude as well as its probability distribution are derived.
The optimal weights for a beamformer that provide maximum directivity, are often found to be severely lacking in terms of robustness. Although an ideal implementation of the beamformer with these weights provides high directivity, minor perturbations of the weights or of sensor placement cause severe degradation. Therefore, a robustness constraint is often imposed during the beamformer's design stage. The classical method of diagonal loading is commonly used for this purpose. There are known results in this field which pertain to an array consisting of sensors with identical directivity-patterns and orientations. We extend these results to account for sensors with nonidentical directivity patterns, and sensors which share placement errors. We show that in such cases, modification of the classical loading scheme to incorporate nonidentical diagonal elements and off-diagonal elements is beneficial.Index Terms-robust beamforming, maximum directivity
Smartglasses, in addition to their visual-output capabilities, often contain acoustic sensors for receiving the user's voice. However, operation in noisy environments may lead to significant degradation of the received signal. To address this issue, we propose employing an acoustic sensor array which is mounted on the eyeglasses frames. The signals from the array are processed by an algorithm with the purpose of acquiring the desired near-field speech signal produced by the wearer while suppressing noise signals originating from the environment. The array is comprised of two acoustic vector-sensors (AVSs) which are located at the fore of the glassesâ temples. Each AVS consists of four collocated subsensors: one pressure sensor (with an omnidirectional response) and three particle-velocity sensors (with dipole responses) oriented in mutually orthogonal directions
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