A directionally tunable but frequency-invariant beamformer on an acoustic velocity-sensor triad to enhance speech perception

Herein investigated are computationally simple microphone-array beamformers that are independent of the frequency-spectra of all signals, all interference, and all noises. These beamformers allow the listener to tune the desired azimuth-elevation “look direction.” No prior information is needed of the interference. These beamformers deploy a physically compact triad of three collocated but orthogonally oriented velocity sensors. These proposed schemes’ efficacy is verified by a jury test, using simulated data constructed with Mandarin Chinese (a.k.a. Putonghua) speech samples. For example, a desired speech signal, originally at a very adverse signal-to-interference-and-noise power ratio (SINR) of -30 dB, may be processed to become fully intelligible to the jury

Novel techniques of polarization diversity and extended-aperture spatial diversity for sensor-array direction-finding in radar, sonar, and wireless communications

An array of diversely polarized antennas can resolve impinging sources based on the sources\u27 different polarizational states in addition to the sources\u27 different directions-of arrival (DOA). Alternately in the sonar environment, an array of diversely oriented velocity-hydrophones can exploit DOA information embedded in the acoustic particle velocity vector-field, in addition to the scalar pressure field. Array aperture extension using sparse array configurations enhances direction-finding (DF) accuracy and resolution capabilities without undue increase in hardware and software costs. The main part of this presentation involves the use of electromagnetic vector-sensors, each of which is composed of six spatially co-located, orthogonally oriented, diversely polarized antennas, distinctly measuring all six electromagnetic-field components of an incident multi-source wave-field. The pivotal insight is that the DOA\u27s may be estimated from the Poynting-vector estimates obtainable from each vector-sensor\u27s steering vector. This vector-sensor based DF provides DOA estimates independent of the traditional estimation based on the phase shifts between the sensor-array\u27s spatially displaced elements as in interferometry. These two separate approaches to DOA estimation allow: (1) extension of intervector-sensor spacing in a uniform array geometry beyond the Nyquist half-wavelength maximum in a closed-form ESPRIT-based DF algorithm, while disambiguating the resultant cyclic ambiguity using the Poynting-vector DOA estimates as coarse references, (2) derivation of coarse DOA estimates to initiate a MUSIC-based iterative search algorithm for any irregularly spaced array of vector-sensors, (3) closed-form DF using only one vector-sensor under certain signal scenarios, (4) closed-form DF using any array of sonar vector-sensors at unknown and arbitrary locations. (The sonar vector-sensor is composed of co-located but orthogonally oriented velocity-hydrophones & a pressure-hydrophone.) Two other DF methods not using the aforementioned vector-sensors are: (5) a close-form Root-MUSIC-based DF algorithm allowing adjacent spatially displaced antennas to have different polarizational states, and (6) an extended-aperture ESPRIT-based algorithm applicable with identical scalar-sensors spaced in a novel geometry with dual sizes of spatial invariances. These various novel DF methods result in order-of-magnitude improvements in estimation accuracy and resolution capability compared with customary non-diversely-polarized half-wavelength spaced interferometry-type DF approaches

Linearly constrained minimum-"geometric power" adaptive beamforming using logarithmic moments of data containing heavy-tailed noise of unknown statistics

This letter presents a new adaptive beamforming approach, against arbitrary algebraically tailed impulse noise of otherwise unknown statistics. (This includes all symmetric Q-stable noises with infinite variance or even infinite mean.) This new beamformer iteratively minimizes the "geometric power" of the beamformer's output Y, subject to a prespecified set of linear constraints. This geometric power is defined in terms of the "logarithmic moment" .E{log|Y|}, as an alternative to the customary "fractional lower order moments" (FLOM). This logarithmic-moment beamformer offers these advantages over the FLOM beamformer: 1) simpler computationally in general, 2) needing no prior information nor estimation of the numerical value of the impulse noise's effective characteristic exponent, and 3) applicable to a wider class of heavy-tailed Impulse noises.Department of Electronic and Information Engineerin