Acoustical Science and Technology
Online ISSN : 1347-5177
Print ISSN : 1346-3969
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Showing 1-6 articles out of 6 articles from the selected issue
  • Akio Ando, Takafumi Fujita
    2018 Volume 39 Issue 5 Pages 327-334
    Published: September 01, 2018
    Released: September 01, 2018
    Even if three-dimensional multichannel sound becomes available in broadcasting, backward compatibility to conventional sound systems will be necessary. There are two transmission formats that can achieve this requirement. One is the simulcast format, and the other is the channel-scalable format. Although the channel-scalable format is advantageous over the simulcast format in terms of the required data rate, the unmasking artifact cannot be avoided when matrix operations are used to realize scalability. To solve this problem, this paper proposes a novel approach that models the quantization noise signal with a polynomial expansion of a decoded signal and removes it from the decoded signal. A subjective evaluation revealed that the proposed method can alleviate the unmasking artifact in the scalable coding of 8.1- and 22.2-channel audio signals.
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  • Akira Sanada, Kazuhiro Iwata, Hiroshi Nakagawa
    2018 Volume 39 Issue 5 Pages 335-342
    Published: September 01, 2018
    Released: September 01, 2018
    This study proposes a normal-incidence sound absorption coefficient measurement technique in the high-frequency range in which obliquely propagating waves can exist in an impedance tube. To extract the normal-propagating wave factor through a cross section of a cylindrical tube, four microphones are located with one in each quarter of the circumference and their signals are summed. The normal-incidence absorption coefficient is calculated from the frequency response function between the normal-propagating factors of two cross sections, which are placed at a prescribed distance. Using the proposed method, measurement can be performed at about twice the frequency of the conventional method. To verify the validity of the proposed method, numerical simulations by the finite element method (FEM) in cases when there is a slight inclination of the specimen surface, which causes scattering, were conducted. The simulation results prove that the proposed method can cancel the effect of the (1, 0) and (2, 0) modes and enable the normal-incidence absorption coefficient to be measured in the frequency region in which these modes can propagate. Finally, experimental results show the validity and the feasibility of the proposed method.
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  • Hai-Yan Song, Jin-Ping Qin, Chang-Yi Yang, Ming Diao
    2018 Volume 39 Issue 5 Pages 343-354
    Published: September 01, 2018
    Released: September 01, 2018
    A uniform circular array (UCA) can provide 360° azimuthal coverage and can be steered in any direction in two-dimensional (2-D) space without changing the shape of the pattern. These attractive features led to the rapid development of direction-of-arrival (DOA) estimation techniques using a UCA. However, most of the previous work on DOA estimation based on a UCA only utilized the time-space statistical information available from the array signals and did not exploit the inherent sparsity of the underlying signal in space domains. In this paper, we develop a new circular array DOA estimation approach that can achieve spatial sparsity, and thus improve spatial resolution, by imposing penalties based on the l1-norm. Our approach differs from most other circular array DOA estimation methods not only in its recognition of the concept of phase modes but also in how it imposes the spatial sparsity constraint on the impinging signal wave fields to achieve better DOA estimation performance. It turns out that our approach, in essence, applies the compressive sensing technique to the modal array signal processing and does not need to reconstruct the correlation matrix or its inverse, so can work well when the sources are coherent. Computer simulations with several frequently encountered scenarios, such as a single source and two closely spaced coherent sources, indicate the superior DOA estimation resolution of our proposed approach as compared with existing techniques. In addition, from a statistical viewpoint, the performance of our proposed approach is investigated more closely by considering the root-mean-square error (RMSE) versus the signal-to-noise ratio (SNR), number of snapshots, or number of sensors, and its excellent DOA estimation accuracy is demonstrated.
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