US20030147539A1 - Audio system based on at least second-order eigenbeams - Google Patents

Audio system based on at least second-order eigenbeams Download PDF

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US20030147539A1
US20030147539A1 US10/315,502 US31550202A US2003147539A1 US 20030147539 A1 US20030147539 A1 US 20030147539A1 US 31550202 A US31550202 A US 31550202A US 2003147539 A1 US2003147539 A1 US 2003147539A1
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sensors
eigenbeam
sensor
order
sphere
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Gary Elko
Robert Kubli
Jens Meyer
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MH Acoustics a Delaware Corp LLC
MH Acoustics LLC
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Assigned to MH ACOUSTICS LLC reassignment MH ACOUSTICS LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: ELKO, GARY W., KUBLI, ROBERT A., MEYER, JENS M.
Priority to EP03702059A priority patent/EP1466498B1/fr
Priority to AU2003202945A priority patent/AU2003202945A1/en
Priority to PCT/US2003/000741 priority patent/WO2003061336A1/fr
Priority to DE60336377T priority patent/DE60336377D1/de
Priority to US10/500,938 priority patent/US7587054B2/en
Publication of US20030147539A1 publication Critical patent/US20030147539A1/en
Priority to US12/501,741 priority patent/US8433075B2/en
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R5/00—Stereophonic arrangements
    • H04R5/027—Spatial or constructional arrangements of microphones, e.g. in dummy heads
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R3/00—Circuits for transducers, loudspeakers or microphones
    • H04R3/005—Circuits for transducers, loudspeakers or microphones for combining the signals of two or more microphones
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R2201/00—Details of transducers, loudspeakers or microphones covered by H04R1/00 but not provided for in any of its subgroups
    • H04R2201/40—Details of arrangements for obtaining desired directional characteristic by combining a number of identical transducers covered by H04R1/40 but not provided for in any of its subgroups
    • H04R2201/401—2D or 3D arrays of transducers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04S—STEREOPHONIC SYSTEMS 
    • H04S2400/00—Details of stereophonic systems covered by H04S but not provided for in its groups
    • H04S2400/15—Aspects of sound capture and related signal processing for recording or reproduction
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04S—STEREOPHONIC SYSTEMS 
    • H04S3/00—Systems employing more than two channels, e.g. quadraphonic

Definitions

  • the present invention relates to acoustics, and, in particular, to microphone arrays.
  • a microphone array-based audio system typically comprises two units: an arrangement of (a) two or more microphones (i.e., transducers that convert acoustic signals (i.e., sounds) into electrical audio signals) and (b) a beamformer that combines the audio signals generated by the microphones to form an auditory scene representative of at least a portion of the acoustic sound field.
  • This combination enables picking up acoustic signals dependent on their direction of propagation.
  • microphone arrays are sometimes also referred to as spatial filters.
  • Their advantage over conventional directional microphones, such as shotgun microphones, is their high flexibility due to the degrees of freedom offered by the plurality of microphones and the processing of the associated beamformer.
  • the directional pattern of a microphone array can be varied over a wide range. This enables, for example, steering the look direction, adapting the pattern according to the actual acoustic situation, and/or zooming in to or out from an acoustic source. All this can be done by controlling the beamformer, which is typically implemented in software, such that no mechanical alteration of the microphone array is needed.
  • the spherical array has several advantages over the other geometries.
  • the beampattern can be steered to any direction in three-dimensional (3-D) space, without changing the shape of the pattern.
  • the spherical array also allows full 3-D control of the beampattern. Notwithstanding these advantages, there is also one major drawback.
  • Conventional spherical arrays typically require many microphones. As a result, their implementation costs are relatively high.
  • the present invention is directed to microphone array-based audio systems that are designed to support representations of auditory scenes using second-order (or higher) harmonic expansions based on the audio signals generated by the microphone array.
  • the present invention comprises a plurality of microphones (i.e., audio sensors) mounted on the surface of an acoustically rigid sphere.
  • the number and location of the audio sensors on the sphere are designed to enable the audio signals generated by those sensors to be decomposed into a set of eigenbeams having at least one eigenbeam of order two (or higher).
  • Beamforming e.g., steering, weighting, and summing
  • Beamforming can then be applied to the resulting eigenbeam outputs to generate one or more channels of audio signals that can be utilized to accurately render an auditory scene.
  • a full set of eigenbeams of order n refers to any set of mutually orthogonal beampatterns that form a basis set that can be used to represent any beampattern having order n or lower.
  • the present invention is a method for processing audio signals.
  • a plurality of audio signals are received, where each audio signal has been generated by a different sensor of a microphone array.
  • the plurality of audio signals are decomposed into a plurality of eigenbeam outputs, wherein each eigenbeam output corresponds to a different eigenbeam for the microphone array and at least one of the eigenbeams has an order of two or greater.
  • the present invention is a microphone comprising a plurality of sensors mounted in an arrangement, wherein the number and positions of sensors in the arrangement enable representation of a beampattern for the microphone as a series expansion involving at least one second-order eigenbeam.
  • the present invention is a method for generating an auditory scene.
  • Eigenbeam outputs are received, the eigenbeam outputs having been generated by decomposing a plurality of audio signals, each audio signal having been generated by a different sensor of a microphone array, wherein each eigenbeam output corresponds to a different eigenbeam for the microphone array and at least one of the eigenbeam outputs corresponds to an eigenbeam having an order of two or greater.
  • the auditory scene is generated based on the eigenbeam outputs and their corresponding eigenbeams.
  • FIG. 1 shows a block diagram of an audio system, according to one embodiment of the present invention
  • FIG. 2 shows a schematic diagram of a possible microphone array for the audio system of FIG. 1;
  • FIG. 3B shows the mode amplitude for a continuous array elevated over the surface of an acoustically rigid sphere
  • FIG. 7 shows velocity modes on the surface of a soft sphere
  • FIGS. 8 A-D show normalized pressure mode amplitude on the surface of a rigid sphere for spherical wave incidence for various distances r, of the sound source;
  • FIG. 9 identifies the positions of the centers of the faces of a truncated icosahedron in spherical coordinates, where the angles are specified in degrees;
  • FIG. 10 shows the 3-D directivity pattern of a third-order hypercardioid pattern at 4 kHz using the truncated icosahedron array on the surface of a sphere of radius 5 cm;
  • FIG. 12 shows the principle filter shape to generate a hypercardioid pattern with a guaranteed minimum WNG
  • FIG. 17 provides a generalized representation of audio systems of the present invention.
  • FIG. 18 represents the structure of an eigenbeam former, such as the generic decomposer of FIG. 17 and the second-order decomposer of FIG. 1;
  • FIG. 19 represents the structure of steering units, such as the generic steering unit of FIG. 17 and the second-order steering unit of FIG. 1;
  • FIG. 20A shows the frequency weighting function of the output of the decomposer of FIG. 1, while FIG. 20B shows the corresponding frequency response correction that should be applied by the compensation unit of FIG. 1;
  • FIG. 21 shows a graphical representation of Equation (61).
  • FIGS. 22A and 22B show mode strength for second-order and third-order modes, respectively;
  • FIG. 22C graphically represents normalized sensitivity of a circular patch-microphone to a spherical mode of order n;
  • FIGS. 23 A-D shows principle pressure distribution for real parts of third-order harmonics, from left to right: Y 3 0 , Y 3 1 , Y 3 2 , and Y 3 3 (where ⁇ direction has to be scaled by sin ⁇ );
  • FIG. 24 shows a preferred patch microphone layout for a 24-element spherical array
  • FIG. 25 illustrates an integrated microphone scheme involving standard electret microphone point sensors and patch sensors
  • FIG. 26 illustrates a sampled patch microphone
  • FIG. 26A illustrates a sensor mounted at an elevated position over the surface of a (partially depicted) sphere
  • FIG. 27 shows a block diagram of a portion of the audio system of FIG. 1 according to an implementation in which an equalization filter is configured between each microphone and the modal decomposer;
  • FIG. 28 shows a block diagram of the calibration method for the n th microphone equalization filter v n (t), according to one embodiment of the present invention.
  • FIG. 29 shows a cross-sectional view of the calibration configuration of a calibration probe over an audio sensor of a spherical microphone array, such as the array of FIG. 2, according to one embodiment of the present invention.
  • a microphone array generates a plurality of (time-varying) audio signals, one from each audio sensor in the array.
  • the audio signals are then decomposed (e.g., by a digital signal processor or an analog multiplication network) into a (time-varying) series expansion involving discretely sampled, (at least) second-order (e.g., spherical) harmonics, where each term in the series expansion corresponds to the (time-varying) coefficient for a different three-dimensional eigenbeam.
  • second-order e.g., spherical harmonics
  • the set of eigenbeams form an orthonormal set such that the inner-product between any two discretely sampled eigenbeams at the microphone locations, is ideally zero and the inner-product of any discretely sampled eigenbeam with itself is ideally one.
  • This characteristic is referred to herein as the discrete orthonormality condition. Note that, in real-world implementations in which relatively small tolerances are allowed, the discrete orthonormality condition may be said to be satisfied when (1) the inner-product between any two different discretely sampled eigenbeams is zero or at least close to zero and (2) the inner-product of any discretely sampled eigenbeam with itself is one or at least close to one.
  • eigenbeam outputs The time-varying coefficients corresponding to the different eigenbeams are referred to herein as eigenbeam outputs, one for each different eigenbeam. Beamforming can then be performed (either in real-time or subsequently, and either locally or remotely, depending on the application) to create an auditory scene by selectively applying different weighting factors to the different eigenbeam outputs and summing together the resulting weighted eigenbeams.
  • embodiments of the present invention are based on microphone arrays in which a sufficient number of audio sensors are mounted on the surface of a suitable structure in a suitable pattern.
  • a number of audio sensors are mounted on the surface of an acoustically rigid sphere in a pattern that satisfies or nearly satisfies the above-mentioned discrete orthonormality condition.
  • a structure is acoustically rigid if its acoustic impedance is much larger than the characteristic acoustic impedance of the medium surrounding it.
  • the highest available order of the harmonic expansion is a function of the number and location of the sensors in the microphone array, the upper frequency limit, and the radius of the sphere.
  • FIG. 1 shows a block diagram of a second-order audio system 100 , according to one embodiment of the present invention.
  • Audio system 100 comprises a plurality of audio sensors 102 configured to form a microphone array, a modal decomposer (i.e., eigenbeam former) 104 , and a modal beamformer 106 .
  • modal beamformer 106 comprises steering unit 108 , compensation unit 110 , and summation unit 112 , each of which will be discussed in further detail later in this specification in conjunction with FIGS. 18 - 20 .
  • Each audio sensor 102 in system 100 generates a time-varying analog or digital (depending on the implementation) audio signal corresponding to the sound incident at the location of that sensor.
  • Modal decomposer 104 decomposes the audio signals generated by the different audio sensors to generate a set of time-varying eigenbeam outputs, where each eigenbeam output corresponds to a different eigenbeam for the microphone array.
  • These eigenbeam outputs are then processed by beamformer 106 to generate an auditory scene.
  • the term “auditory scene” is used generically to refer to any desired output from an audio system, such as system 100 of FIG. 1. The definition of the particular auditory scene will vary from application to application.
  • the output generated by beamformer 106 may correspond to one or more output signals, e.g., one for each speaker used to generate the resultant auditory scene.
  • beamformer 106 may simultaneously generate beampatterns for two or more different auditory scenes, each of which can be independently steered to any direction in space.
  • FIG. 2 shows a schematic diagram of a possible microphone array 200 for audio system 100 of FIG. 1.
  • microphone array 200 comprises 32 audio sensors 102 of FIG. 1 mounted on the surface of an acoustically rigid sphere 202 in a “truncated icosahedron” pattern. This pattern is described in further detail later in this specification in conjunction with FIG. 9.
  • Each audio sensor 102 in microphone array 200 generates an audio signal that is transmitted to the modal decomposer 104 of FIG. 1 via some suitable (e.g., wired or wireless) connection (not shown in FIG. 2).
  • beamformer 106 exploits the geometry of the spherical array of FIG. 2 and relies on the spherical harmonic decomposition of the incoming sound field by decomposer 104 to construct a desired spatial response.
  • Beamformer 106 can provide continuous steering of the beampattern in 3 -D space by changing a few scalar multipliers, while the filters determining the beampattern itself remain constant.
  • the shape of the beampattern is invariant with respect to the steering direction. Instead of using a filter for each audio sensor as in a conventional filter-and-sum beamformer, beamformer 106 needs only one filter per spherical harmonic, which can significantly reduce the computational cost.
  • Audio system 100 with the spherical array geometry of FIG. 2 enables accurate control over the beampattern in 3 -D space.
  • system 100 can also provide multi-direction beampatterns or toroidal beampatterns giving uniform directivity in one plane. These properties can be useful for applications such as general multichannel speech pick-up, video conferencing, or direction of arrival (DOA) estimation. It can also be used as an analysis tool for room acoustics to measure directional properties of the sound field.
  • DOA direction of arrival
  • Audio system 100 offers another advantage: it supports decomposition of the sound field into mutually orthogonal components, the eigenbeams (e.g., spherical harmonics) that can be used to reproduce the sound field.
  • the eigenbeams are also suitable for wave field synthesis (WFS) methods that enable spatially accurate sound reproduction in a fairly large volume, allowing reproduction of the sound field that is present around the recording sphere. This allows all kinds of general real-time spatial audio applications.
  • WFS wave field synthesis
  • r represents the distance from the origin (i.e., the center of the microphone array)
  • ⁇ is the angle in the horizontal (i.e., x-y) plane from the x-axis
  • ⁇ is the elevation angle in the vertical direction from the z-axis
  • k represents the wavenumber, equal to ⁇ /c, where c is the speed of sound and ⁇ is the frequency of the sound in radians/second;
  • t is time
  • i is the imaginary constant (i.e., ⁇ square root ⁇ square root over ( ⁇ 1) ⁇ );
  • j n stands for the spherical Bessel function of the first kind of order n.
  • P n denotes the Legendre function.
  • G can be seen as a function that describes the behavior of a plane-wave from the z-direction with unity magnitude and referenced to the origin.
  • Equation (1) the sound velocity for an impinging plane-wave on the surface of a sphere can be derived using Euler's Equation.
  • the sphere is acoustically rigid, then the sum of the radial velocities of the incoming and the reflected sound waves on the surface of the sphere is zero.
  • a is the radius of the sphere
  • a prime (′) denotes the derivative with respect to the argument
  • h n (2) represent the spherical Hankel function of the second kind of order n.
  • Equation (3) Equation (3)
  • Equation (2) Equation (3)
  • Equation (3) Equation (3)
  • Equation (3) Equation (3)
  • Equation (3) Equation (3)
  • Equation (3) Equation (3)
  • Equation (3) Equation (3)
  • Equation (4) Equation (4)
  • Equation (4) Equation (4)
  • i n ⁇ ⁇ m - n n ⁇ ⁇ ( n - m ) ! ( n + m ) !
  • R is the distance between the source and the microphone
  • R may be given according to Equation (10) as follows:
  • Equation (13) h n ( 2 ) ⁇ ( kr l ) ⁇ ⁇ n + 1 ⁇ ⁇ ⁇ ⁇ ⁇ ⁇ kr l kr l ⁇ ⁇ for ⁇ ⁇ kr l ⁇ 1 ( 13 )
  • Equation (14) equals the farfield solution, given in Equation (6).
  • Equation (14) equals the farfield solution, given in Equation (6).
  • Modal beamforming is a powerful technique in beampattern design. Modal beamforming is based on an orthogonal decomposition of the sound field, where each component is multiplied by a given coefficient to yield the desired pattern. This procedure will now be described in more detail for a continuous spherical pressure sensor on the surface of a rigid sphere.
  • ⁇ symbolizes the 4 ⁇ space.
  • the array factor is first computed for a single mode n′m′, where n′ is the order and m′ is the degree.
  • n′ is the order and m′ is the degree.
  • a spherical scatterer with plane-wave incidence is assumed. Changes to adopt this derivation for a soft scatterer and/or spherical wave incidence are straightforward.
  • the array factor equals the aperture weighting function. This results in the following steps to implement a desired beampattern:
  • Equation (18) is a spherical harmonic expansion of the array factor. Since the spherical harmonics Y are mutually orthogonal, a desired beampattern can be easily designed. For example, if C 00 and C 10 are chosen to be unity and all other coefficients are set to zero, then the superposition of the omnidirectional mode (Y 0 ) and the dipole mode (Y 1 0 ) will result in a cardioid pattern.
  • Equation (19) From Equation (19), the term i n b n plays an important role in the beamforming process. This term will be analyzed further in the following sections. Also, the corresponding terms for a velocity sensor, a soft sphere, and spherical wave incidence will be given.
  • Equation (5) For an array on a rigid sphere, the coefficients b, are given by Equation (5). These coefficients give the strength of the mode dependent on the frequency.
  • the first mode is down by 20 dB. At higher frequencies, more modes emerge.
  • FIG. 3B shows the mode coefficients for an elevated array, where the distance between the array and the spherical surface is 2 a .
  • the frequency response shown in FIG. 3B has zeros. This limits the usable bandwidth of such an array.
  • One advantage is that the amplitude at low frequencies is significantly higher, which allows higher directivity at lower frequencies.
  • a drawback of the velocity modes is their characteristic to have singularities in the modes in the desired operating frequency range. This means that, before a mode is used for a directivity pattern, it should be checked to see if it has a singularity for a desired frequency. Fortunately, the singularities do not appear frequently but show up only once per mode in the typical frequency range of interest. The singularities in the velocity modes correspond to the maxima in the pressure modes. They also experience a 90° phase shift (compare Equations (20) and (6)).
  • a velocity microphone is implemented as an equalized first-order pressure differential microphone. Comparing this to Equation (20), the coefficients b n are then scaled by k. Since usually the pressure differential is approximated by only the pressure difference between two omnidirectional microphones, an additional scaling of 20log(l) is taken into account, where l is the distance between the two microphones.
  • the pressure mode coefficients become i n b n (s) .
  • the magnitude of these is plotted in FIG. 6 for a distance of 1.1a. They look like a mixture of the pressure modes and the velocity modes for the rigid sphere. For low frequencies, only the zero-order mode is present. With increasing frequency, more and more modes emerge. The rising slope is about 6n dB, where n is the order of the mode. Similar to the velocity in front of a rigid surface, the pressure in front of a soft surface becomes zero at a distance of half of a wavelength away from the surface.
  • the effect of decreasing mode magnitude with an increasing number of modes is compensated by the fact that the pressure increases for a fixed distance until the distance is a quarter wavelength. Therefore, the mode magnitude remains more or less constant up to this point.
  • Equation (12) the mode coefficients for spherical sound incidence are given by Equation (23) as follows:
  • FIGS. 8 A-D the magnitude of the modes is plotted for various distances r l of the sound source.
  • the scaling factor has a slope of about ⁇ 6n dB, which compensates the 6n dB slope of b n and results in a constant.
  • the appearance of the higher-order modes at low ka's becomes clear by keeping in mind that the modes correspond to a spherical harmonic decomposition of the sound pressure distribution on the surface of the sphere. The shorter the distance of the source from the sphere, the more unequal will be the sound pressure distribution even for low frequencies, and this will result in higher-order terms in the spherical harmonics series. This also means that, for short source distances, a higher directivity at low frequencies could be achieved since more modes can be used for the beampattern.
  • the design distance is r l
  • the actual source distance is denoted r l .
  • the mode magnitude in FIGS. 8 A-D is normalized so that mode zero is unity (about 0 dB) for ka ⁇ 0. This normalization removes the 1/r l dependency for point sources.
  • FIG. 9 identifies the positions of the centers of the faces of a truncated icosahedron in spherical coordinates, where the angles are specified in degrees.
  • FIG. 2 illustrates the microphone locations for a TIA on the surface of a sphere.
  • each microphone positioned at the center of a pentagon has five neighbors at a distance of 0.65a, where a is the radius of the sphere.
  • Each microphone positioned at the center of a hexagon has six neighbors, of which three acre at a distance of 0.65a and the other three are at a distance of 0.73a.
  • Equation (16) the index s denotes the s-th sensor.
  • spatial aliasing should be taken into account. Similar to time aliasing, spatial aliasing occurs when a spatial function, e.g., the spherical harmonics, is undersampled. For example, in order to distinguish 16 harmonics, at least 16 sensors are needed. In addition, the positions of the sensors are important. For this description, it is assumed that there are a sufficient number of sensors located in suitable positions such that spatial aliasing effects can be neglected.
  • ⁇ nm a correction factor ⁇ nm can be introduced. For best performance, this factor should be close to one for all n,m of interest.
  • the white noise gain (WNG), which is the inverse of noise sensitivity, is a robustness measure with respect to errors in the array setup. These errors include the sensor positions, the filter weights, and the sensor self-noise.
  • the numerator is the signal energy at the output of the array, while the denominator can be seen as the output noise caused by the sensor self-noise.
  • the sensor noise is assumed to be independent from sensor to sensor. This measure also describes the sensitivity of the array to errors in the setup.
  • N is the highest-order mode used for the beamforming.
  • the number of all spherical harmonics up to N th order is (N+1) 2 .
  • ⁇ n 0 N ⁇ C ⁇ n ⁇ ( ⁇ ) ⁇ Y n ⁇ ( ⁇ s , ⁇ s ) ⁇
  • ⁇ n 0 N ⁇ C n ⁇ ( ) i n ⁇ b n ⁇ ( ⁇ ) ⁇ 2 ⁇ n + 1 4 ⁇ ⁇ ⁇ P n ⁇ ( cos ⁇ ⁇ ⁇ s ) ⁇
  • Equations (32) and (33) a general prediction of the WNG is difficult. Two special cases will be treated here: first, for a desired pattern that has only one mode and, second, for a superdirectional pattern for which b N ⁇ b N ⁇ 1 (compare FIG. 3A).
  • WNG ⁇ ( ⁇ ) M 2
  • 2 ⁇ 2 ⁇ N + 1 4 ⁇ ⁇ ⁇ ⁇ s 0 M - 1
  • 2 M 2
  • 2 ⁇ s 0 M - 1 ⁇ ⁇ P N ⁇ ( cos ⁇ ⁇ ⁇ s ) ⁇ 2 ( 34 )
  • ⁇ n 0 N ⁇ C n ⁇ ( ⁇ ) ⁇ 2 ⁇ n + 1 4 ⁇ ⁇ ⁇
  • 2 ⁇ ⁇ s 0 M - 1 ⁇ ⁇ P N ⁇ ( cos ⁇ ⁇ ⁇ s ) ⁇ 2 ⁇ ⁇ b n ⁇ ( ⁇ ) ⁇ 2 ( 35 )
  • Equation (35) can be further simplified if the term C n ⁇ square root ⁇ (2n+1/(4 ⁇ )) is constant for all modes. This would result in a sinc-shaped pattern.
  • Equation (34) This result is similar to Equation (34), except that the WNG is increased by a factor of (N+1) 2 . This is reasonable, since every mode that is picked up by the array increases the output signal level.
  • This section will give two suggestions on how to get the coefficients C nm that are used to compute the sensor weights h, according to Equation (27).
  • the first approach implements a desired beampattern h( ⁇ , ⁇ , ⁇ ), while the second one maximizes the directivity index (DI).
  • DI directivity index
  • There are many more ways to design a beampattern. Both methods described below will assume a look direction towards ⁇ 0. After those two methods, the subsequent section describes how to turn the pattern, e.g., to steer the main lobe to any desired direction in 3-D space.
  • FIG. 10 shows the 3-D pattern of a third-order hypercardioid at 4 kHz, where the microphones are positioned on the surface of a sphere of radius 5 cm at the center of the faces of a truncated icosahedron.
  • the pattern should be frequency independent, but, due to the sampling of the spherical surface, aliasing effects show up at higher frequencies.
  • a small effect caused by the spatial sampling can be seen in the second side lobe.
  • the pattern is not perfectly rotationally symmetric. This effect becomes worse with increasing frequency. On a sphere of radius 5 cm, this sampling scheme will yield good results up to about 5 kHz.
  • This section describes a method to compute the coefficients C that result in a maximum achievable directivity index (DI).
  • DI maximum achievable directivity index
  • WNG white noise gain
  • the directivity index is defined as the ratio of the energy picked up by a directive microphone to the energy picked up by an omnidirectional microphone in an isotropic noise field, where both microphones have the same sensitivity towards the look direction. If the directive microphone is operated in a spherically isotropic noise field, the DI can be seen as the acoustical signal-to-noise improvement achieved by the directive microphone.
  • the vector h contains the sensor weights at frequency ⁇ 0 according to Equation (39) as follows:
  • T denotes “transpose.”
  • G 0 is a vector describing the source array transfer function for the look direction at ⁇ 0 .
  • R is the spatial cross-correlation matrix.
  • Equation (27) The last required piece is to express the sensor weights using the coefficients C nm . This is provided by Equation (27), which can again be written in matrix notation according to Equation (42) as follows:
  • the vector c contains the spherical harmonic coefficients C nm for the beampattern design. This is the vector that has to be determined.
  • Equation (45) is a generalized eigenvalue problem. Since A, R, and I are full rank, the solution is the eigenvector corresponding to Equation (46) as follows:
  • Equation 45 [0167] where ⁇ (.) means “eigenvalue from.” Unfortunately, Equation 45 cannot be solved for ⁇ . Therefore, one way to find the maximum DI for a desired WNG is as follows:
  • Step (1) Find the solution to Equation (46) for an arbitrary ⁇ .
  • Step (2) From the resulting vector c, compute the WNG.
  • Step (3) If the WNG is larger than desired, then return to Step (1) using a smaller ⁇ . If the WNG is too small, then return to Step (1) using a larger ⁇ . If the WNG matches the desired WNG, then the process is complete.
  • FIG. 13 shows the maximum DI that can be achieved with the TIA using spherical harmonics up to order N without a constraint on the WNG.
  • FIG. 14 shows the WNG corresponding to the maximum DI in FIG. 13. As long as the pattern is superdirectional, the WNG increases at about 6N dB per octave. The maximum WNG that can be achieved is about 10logM, which for the TIA is about 15 dB. This is the value for an array in free field. In FIG. 14, for the sphere-baffled array, the maximum WNG is a bit higher, about 17 dB. Once the maximum is reached, it decreases. This is due to fact that the mode number in the array pattern is constant. Since the mode magnitude decreases once a mode has reached its maximum, the WNG is expected to decrease as soon as the highest mode has reached its maximum. For example, the third-order mode shows this for f ⁇ 3 kHz (compare FIG. 3A).
  • FIG. 15 shows the maximum DI that can be achieved with a constraint on the WNG for a pattern that contains the spherical harmonics up to third order.
  • WNG the tradeoff between WNG and DI.
  • FIGS. 16 A-B give the magnitude and phase, respectively, of the coefficients computed according to the procedure described above in this section, where N was set to 3, and the minimum required WNG was about ⁇ 5 dB. Coefficients are normalized so that the array factor for the look direction is unity. Comparing the coefficients from FIGS. 16 A-B with the coefficients from FIG. 12, one finds that they are basically the same. Only the band transitions are more precise in FIGS. 16 A-B in order to keep the WNG constant.
  • Equation (49) enables control of the ⁇ and ⁇ directions independently. Also the pattern itself can be implemented independently from the desired look direction.
  • This section provides a layout for the beamformer based on the theory described in the previous sections.
  • the spherical array can be implemented using a filter-and-sum beamformer as indicated in Equation (28).
  • the filter-and-sum approach has the advantage of utilizing a standard technique. Since the spherical array has a high degree of symmetry, rotation can be performed by shifting the filters.
  • the TIA can be divided into 60 very similar triangles. Only one set of filters is computed with a look direction normal to the center of one triangle. Assigning the filters to different sensors allows steering the array to 60 different directions.
  • FIG. 17 provides a generalized representation of audio systems of the present invention.
  • Decomposer 1704 corresponding to decomposer 104 of FIG. 1, performs the orthogonal modal decomposition of the sound field measured by sensors 1702 .
  • the beamformer is represented by steering unit 1706 followed by pattern generation 1708 followed by frequency response correction 1710 followed by summation node 1712 . Note that, in general, not all of the available eigenbeam outputs have to be used when generating an auditory scene.
  • beamformer 106 comprises steering unit 108 , compensation unit 110 , and summation unit 112 .
  • the frequency-response correction of compensation unit 110 is applied prior to pattern generation, which is implemented by summation unit 112 . This differs from the representation in FIG.
  • correction unit 1710 performs frequency-response correction after pattern generation 1708 .
  • Either implementation is viable.
  • any order of steering unit, pattern generation, and correction is possible.
  • the mathematical analysis of the decomposition was discussed previously for complex spherical harmonics. To simplify a time domain implementation, one can also work with the real and imaginary parts of the spherical harmonics. This will result in real-valued coefficients which are more suitable for a time-domain implementation.
  • the sensitivity equals the imaginary part of a spherical harmonic
  • the beampattern of the corresponding array factor will also be the imaginary part of this spherical harmonic.
  • the output spherical harmonic is frequency weighted. To compensate for this frequency dependence, compensation unit 110 of FIG. 1 may be implemented as described below in conjunction with FIG. 20.
  • the continuous spherical sensor is replaced by a discrete spherical array.
  • the integrals in the equations become sums.
  • FIG. 18 represents the structure of an eigenbeam former, such as generic decomposer 1704 of FIG. 17 and second-order decomposer 104 of FIG. 1.
  • Decomposers can be conveniently described using matrix notation according to Equation (54) as follows:
  • f d describes the output of the decomposer
  • s is a vector containing the sensor signals
  • Y is a (2N+1) 2 ⁇ S matrix, where N is the highest order in the spherical harmonic expansion.
  • the columns of Y give the real and imaginary parts of the spherical harmonics for the corresponding sensor position.
  • Table 2 shows the convention that is used for numbering the rows of matrix Y up to fifth-order spherical harmonics, where n corresponds to the order of the spherical harmonic, m corresponds to the degree of the spherical harmonic, and the label nm identifies the row number.
  • FIG. 19 represents the structure of steering units, such as generic steering unit 1706 of FIG. 17 and second-order steering unit 108 of FIG. 1. Steering units are responsible for steering the look direction by [ ⁇ 0 , ⁇ 0 ].
  • the output of the decomposer is frequency dependent.
  • Frequency-response correction as performed by generic correction unit 1710 of FIG. 17 and second-order compensation unit 110 of FIG. 1, adjusts for this frequency dependence to get a frequency-independent representation of the spherical harmonics that can be used, e.g., by generic summation node 1712 of FIG. 17 and second-order summation unit 112 of FIG. 1, in generating the beampattern.
  • FIG. 20A shows the frequency-weighting function of the decomposer output
  • FIG. 20B shows the corresponding frequency-response correction that should be applied, where the frequency-response correction is simply the inverse of the frequency-weighting function.
  • the transfer function for frequency-response correction may be implemented as a band-stop filter comprising a first-order high-pass filter configured in parallel with an n-order low-pass filter, where n is the order of the corresponding spherical harmonic output. At low ka, the gain has to be limited to a reasonable factor.
  • FIG. 20 only shows the magnitude; the corresponding phase can be found from Equation (19).
  • Summation unit 112 of FIG. 1 performs the actual beamforming for system 100 .
  • Summation unit 112 weights each harmonic by a frequency response and then sums up the weighted harmonics to yield the beamformer output (i.e., the auditory scene). This is equivalent to the processing represented by pattern generation unit 1708 and summation node 1712 of FIG. 17.
  • WNG white noise gain
  • the best choices are big spheres with large numbers of sensors.
  • the number of sensors may be restricted in a real-time implementation by the ability of the hardware to perform the required processing on all of the signals from the various sensors in real time.
  • the number of sensors may be effectively limited by the capacity of available hardware. For example, the availability of 32-channel processors (24-channel processors for mobile applications) may impose a practical limit on the number of sensors in the microphone array. The following sections will give some guidance to the design of a practical system.
  • FIG. 21 shows a graphical representation of Equation (56), representing the maximum frequency for no spatial aliasing as a function of the radius. This figure gives an idea of which radius to choose in order to get a desired upper frequency limit for a given number of sensors. Note that this is only an approximation.
  • the minimum number of sensors required to pick up all harmonic components is (N+1) 2 , where N is the order of the pattern. This means that, for a second-order array, at least nine elements are needed and, for a third-order array, at least 16 sensors are needed to pick up all harmonic components. These numbers assume the ability to generate an arbitrary beampattern of the given order. If the beampatterns can be restricted somehow, e.g., the look direction is fixed or needs to be steered only in one plane, then the number of sensors can be reduced since, in those situations, all of the harmonic components (i.e., the full set of eigenbeams) are not needed.
  • Equation (57) A general expression of the white noise gain (WNG) as a function of the number of microphones and radius of the sphere cannot be given, since it depends on the sensor locations and, to a great extent, on the beampattern. If the beampattern consists of only a single spherical harmonic, then an approximation of the WNG is given by Equation (57) as follows:
  • the factor b n represents the mode strength (see FIG. 20A).
  • the above proportionality is also valid if the array is operated in a superdirectional mode, meaning that the strength of the highest harmonic is significantly less than the strength of the lower-order harmonics. This is a typical operational mode at lower frequencies.
  • Table 3 shows the gain that is achieved due to the number of sensors. It can be seen that the gain in general is quite significant, but increases by only 6 dB when the number of sensors is doubled. TABLE 3 WNG due to the number of microphones. S 12 16 20 24 32 20 log(S) [dB] 22 24 26 28 30
  • FIGS. 22A and 22B show mode strength for second-order and third-order modes, respectively.
  • the figures show the mode strength as a function of frequency for five different array radii from 5 mm to 50 mm.
  • this mode strength is directly proportional to the WNG, where the WNG is proportional to the radius squared. This means that the radius should be chosen as large as possible to achieve a good WNG in order achieve a high directivity at low frequencies.
  • the minimum number of sensors is 16.
  • the maximum number of sensors is assumed to be 24.
  • the radius of the sphere should be no larger than about 4 cm. On the other hand, it should not be much smaller because of the WNG.
  • a good compromise seems to be an array with 20 sensors on a sphere with radius of 37.5 mm (about 1.5 inches).
  • a good choice for the sensor locations is the center of the faces of an icosahedron, which would result in regular sensor spacing on the surface of the sphere. Table 4 identifies the sensor locations for one possible implementation of the icosahedron sampling scheme.
  • Table 5 identifies the sensor locations for one possible implementation of the extended icosahedron sampling scheme.
  • Table 5 identifies the sensor locations for one possible implementation of the extended icosahedron sampling scheme.
  • Another possible configuration is based on a truncated icosahedron scheme of FIG. 9. Since this scheme involves 32 sensors, it might not be practical for some applications (e.g., mobile solutions) where available processors cannot support 32 incoming audio signals.
  • Table 6 identifies the sensor locations for one possible six-element spherical array, and Table 7 identifies the sensor locations for one possible four-element spherical array.
  • Spatial aliasing is a serious problem that causes a limitation of usable bandwidth.
  • a modal low-pass filter may be employed as an anti-aliasing filter. Since this would suppress higher-order modes, the frequency range can be extended. The new upper frequency limit would then be caused by other factors, such as the computational capability of the hardware, the A/D conversion, or the “roundness” of the sphere.
  • J is the Bessel function
  • a is the radius of the piston
  • ⁇ is the angle off-axis.
  • This is referred to as a spatial low-pass filter since, for small arguments (ka sin ⁇ 1), the sensitivity is high, while, for large arguments, the sensitivity goes to zero. This means, that only sound from a limited region is recorded. Generally this behavior is true for pressure sensors with a significant (relative to the acoustic wavelength) membrane size.
  • the following provides a derivation for an expression for a conformal patch microphone on the surface of a rigid sphere.
  • ⁇ s symbolizes the integration over the microphone area
  • G is the sound pressure at location [ ⁇ s , ⁇ s ] on the surface of the sphere caused by plane wave incidence from direction [ ⁇ , ⁇ ], assuming plane wave incidence with unity magnitude.
  • M nm is the sensitivity to mode n,m.
  • FIG. 22C indicates that the patch microphone has to have a significant size in order to attenuate the higher-order modes.
  • FIGS. 23 A-D depict the basic pressure distributions of the spherical modes of third order, where the lines mark the zero crossings. For the other harmonics, the shapes look similar. These patterns suggest a rectangular shape for the patches to somehow achieve a good match between the patches and the modes. The patches should be fairly large. A good solution is probably to cover the whole spherical surface. Another consideration is the area size of the sensors. Intuitively, it seems reasonable to have all sensors of equal size. Putting all these arguments together yields the sensor layout depicted in FIG.
  • Equation (70) which satisfies the orthogonality constraint of Equation (70) up to third order.
  • the layout in FIG. 24 does not appear to involve sensors of equal area, this is an artifact of projecting the 3-D curved shapes onto a 2-D rectilinear graph.
  • the fifth-order modes are already significantly suppressed. As such, the fourth-order modes can be seen as a transition region.
  • EMFi is a charged cellular polymer that shows piezo-electric properties. The reported sensitivity of this material to air-borne sound is about 0.7 mV/Pa.
  • the polymer is provided as a foil with a thickness of 70 ⁇ m.
  • the material is a thin polymer, it can be glued directly onto the surface of the sphere. Also the shape of the sensor can be arbitrary. A problem might be encountered with the sensor self-noise. An equivalent noise level of about 50 dBA is reported for a sensor of size of 3.1 cm 2 .
  • FIG. 25 illustrates an integrated scheme of standard electret microphone point sensors 2502 and patch sensors 2504 designed to reduce the noise problem.
  • signals from the point sensors are used.
  • a low sensor self-noise is especially important at lower frequencies where the beampattern tends to be superdirectional.
  • signals from the patch sensors are used.
  • the patch sensors can be glued on the surface of the sphere on top of the standard microphone capsules. In that case, the patches should have only a small hole 2506 at the location of the point sensor capsule to allow sound to reach the membrane of the capsules.
  • the crossover frequency will depend on the array dimensions. For a 24-element array with a radius of 37.5 mm, a crossover frequency of 3 kHz could be chosen if all modes up to third order are to be used.
  • the crossover frequency is a compromise between the WNG, the aliasing, and the order of the crossover network. Concerning the WNG, the patch sensor array should be used only if there is maximum WNG from the array (e.g., at about 5 kHz). However, at this frequency, spatial aliasing already starts to occur. Therefore, significant attenuation for the point sensor array is desired at 5 kHz. If it is desirable to keep the order of the crossover low (first or second order), the crossover frequency should be about 3 kHz.
  • modal low-pass filters there are other ways to implement modal low-pass filters.
  • a “sampled patch microphone” can be used instead of using a continuous patch microphone. As represented in FIG. 26, this involves taking several microphone capsules 2602 located within an effective patch area 2604 and combining their outputs, as described in U.S. Pat. No. 5,388,163, the teachings of which are incorporated herein by reference.
  • a sampled patch microphone could be implemented using a number of individual electret microphones. Although this solution will also have an upper frequency limit, this limit can be designed to be outside the frequency range of interest. This solution will typically increase the number of sensors significantly. From Equation (61), in order to get twice the frequency range, four times as many microphones would be needed. However, since the signals within a sampled patch microphone are summed before being sampled, the number of channels that have to be processed remains unchanged. This would also extend the lower frequency range, since the noise performance of the sampled patches is 10log (S p ) better than the self-noise of a single sensor, where S p is the number of sensors per patch. This additional noise gain might allow omitting the microphone correction filters that are used to compensate for the differences between the microphone capsules. This would even simplify the processing of the microphone signals.
  • one sensor array covered the whole frequency band. It is also possible to use two or more sensor arrays, e.g., staged on concentric spheres, where the outer arrays are located on soft, “virtual” spheres, elevated over the sphere located at the center, which itself could be either a hard sphere or a soft sphere.
  • FIG. 26A gives an idea of how this array can be implemented. For simplicity, FIG. 26A shows only one sensor. The sensors of different spheres do not necessarily have to be located at the same spherical coordinates ⁇ , ⁇ . Only the innermost array can be on the surface of a sphere.
  • the outermost sphere having the largest radius, would cover the lower frequency band, while the innermost array covers the highest frequencies.
  • the outputs of the individual arrays would be combined using a simple (e.g., passive) crossover network. Assuming the number of microphones is the same for all arrays (this does not necessarily need to be the case), the smaller the radius, the smaller the distance between microphones and the higher the upper frequency limit before spatial aliasing occurs.
  • a particularly efficient implementation is possible if all of the sensor arrays have their sensors located at the same set of spherical coordinates.
  • a single beamformer can be used for all of the arrays, where the signals from the different arrays are combined, e.g., using a crossover network, before the signals are fed into the beamformer.
  • the overall number of input channels can be the same as for a single-array embodiment having the same number of sensors per array.
  • the lower frequency signal would be processed by the entire sensor array, while the higher frequency band would be recorded with just one or a few microphones pointing towards the desired direction.
  • the two frequency bands can be combined by a simple crossover network.
  • an equalization filter 2702 can be added between each microphone 102 and decomposer 104 of audio system 100 of FIG. 1 in order to compensate for microphone tolerances. Such a configuration enables beamformer 106 of FIG. 1 to be designed with a lower white noise gain.
  • Each equalization filter 2702 has to be calibrated for the corresponding microphone 102 . Conventionally, such calibration involves a measurement in an acoustically treaded enclosure, e.g., an anechoic chamber, which can be a cumbersome process.
  • FIG. 28 shows a block diagram of the calibration method for the n th microphone equalization filter v n (t), according to one embodiment of the present invention.
  • a noise generator 2802 generates an audio signal that is converted into an acoustic measurement signal by a speaker 2804 inside a confined enclosure 2806 , which also contains the n th microphone 102 and a reference microphone 2808 .
  • the audio signal generated by the n th microphone 102 is processed by equalization filter 2702 , while the audio signal generated by reference microphone 2808 is delayed by delay element 2810 by an amount corresponding to a fraction (typically one half) of the processing time of equalization filter 2702 .
  • control mechanism 2814 uses both the original audio signal from microphone 102 and the error signal e(t) to update one or more operating parameters in equalization filter 2702 in an attempt to minimize the magnitude of the error signal.
  • Some standard adaption algorithm like NLMS, can be used to do this.
  • FIG. 29 shows a cross-sectional view of the calibration configuration of a calibration probe 2902 over an audio sensor 102 of a spherical microphone array, such as array 200 of FIG. 2, according to one embodiment of the present invention.
  • calibration probe 2902 has a hollow rubber tube 2904 configured to feed an acoustic measurement signal into an enclosure 2906 within calibration probe 2902 .
  • Reference sensor 2808 is permanently configured at one side of enclosure 2906 , which is open at its opposite side.
  • calibration probe 2902 is placed onto microphone array 200 with the open side of enclosure 2906 facing an audio sensor 102 .
  • the calibration probe preferably has a gasket 2908 (e.g., a rubber O-ring) in order to form an airtight seal between the calibration probe and the surface of the microphone array.
  • gasket 2908 e.g., a rubber O-ring
  • enclosure 2906 In order to produce a substantially constant sound pressure field, enclosure 2906 is kept as small as practicable (e.g., 180 mm 3 ), where the dimensions of the volume are preferably much less than the wavelength of the maximum desired measurement frequency. To keep the errors as low as possible for higher frequencies, enclosure 2906 should be built symmetrically. As such, enclosure 2906 is preferably cylindrical in shape, where reference sensor 2808 is configured at one end of the cylinder, and the open end of probe 2902 forms the other end of the cylinder.
  • the size of the microphones 102 used in array 200 determines the minimum diameter of cylindrical enclosure 2906 . Since a perfect frequency response is not necessarily a goal, the same microphone type can be used for both the array and the reference sensor. This will result in relatively short equalization filters, since only slight variations are expected between microphones.
  • the array sphere can be configured with two little holes (not shown) on opposite sides of each sensor, which align with two small pins (not shown) on the probe to ensure proper positioning of the probe during calibration processing.
  • Calibration probe 2902 enables the sensors of a microphone array, like array 200 of FIG. 2, to be calibrated without requiring any other special tools and/or special acoustic rooms. As such, calibration probe 2902 enables in situ calibration of each audio sensor 102 in microphone array 200 , which in turn enables efficient recalibration of the sensors from time to time.
  • the processing of the audio signals from the microphone array comprises two basic stages: decomposition and beamforming. Depending on the application, this signal processing can be implemented in different ways.
  • modal decomposer 104 and beamformer 106 are co-located and operate together in real time.
  • the eigenbeam outputs generated by modal decomposer 104 are provided immediately to beamformer 106 for use in generating one or more auditory scenes in real time.
  • the control of the beamformer can be performed on-site or remotely.
  • modal decomposer 104 and beamformer 106 both operate in real time, but are implemented in different (i.e., non-co-located) nodes.
  • data corresponding to the eigenbeam outputs generated by modal decomposer 104 which is implemented at a first node, are transmitted (via wired and/or wireless connections) from the first node to one or more other remote nodes, within each of which a beamformer 106 is implemented to process the eigenbeam outputs recovered from the received data to generate one or more auditory scenes.
  • modal decomposer 104 and beamformer 106 do not both operate at the same time (i.e., beamformer 106 operates subsequent to modal decomposer 104 ).
  • data corresponding to the eigenbeam outputs generated by modal decomposer 104 are stored, and, at some subsequent time, the data is retrieved and used to recover the eigenbeam outputs, which are then processed by one or more beamformers 106 to generate one or more auditory scenes.
  • the beamformers may be either co-located or non-co-located with the modal decomposer.
  • channels 114 through which the eigenbeam outputs generated by modal decomposer 104 are provided to beamformer 106 .
  • the exact implementation of channels 114 will then depend on the particular application.
  • channels 114 are represented as a set of parallel streams of eigenbeam output data (i.e., one time-varying eigenbeam output for each eigenbeam in the spherical harmonic expansion for the microphone array).
  • a single beamformer such as beamformer 106 of FIG. 1, is used to generate one output beam.
  • the eigenbeam outputs generated by modal decomposer 104 may be provided (either in real-time or non-real time, and either locally or remotely) to one or more additional beamformers, each of which is capable of independently generating one output beam from the set of eigenbeam outputs generated by decomposer 104 .
  • This specification describes the theory behind a spherical microphone array that uses modal beamforming to form a desired spatial response to incoming sound waves. It has been shown that this approach brings many advantages over a “conventional” array. For example, (1) it provides a very good relation between maximum directivity and array dimensions (e.g., DI max of about 16 dB for a radius of the array of 5 cm); (2) it allows very accurate control over the beampattern; (3) the look direction can be steered to any angle in 3 -D space; (4) a reasonable directivity can be achieved at low frequencies; and (5) the beampattern can be designed to be frequency-invariant over a wide frequency range.
  • DI max of about 16 dB for a radius of the array of 5 cm
  • This specification also proposes an implementation scheme for the beamformer, based on an orthogonal decomposition of the sound field.
  • the computational costs of this beamformer are less expensive than for a comparable conventional filter-and-sum beamformer, yet yielding a higher flexibility.
  • An algorithm is described to compute the filter weights for the beamformer to maximize the directivity index under a robustness constraint.
  • the robustness constraint ensures that the beamformer can be applied to a real-world system, taking into account the sensor self-noise, the sensor mismatch, and the inaccuracy in the sensor locations.
  • the beamformer design can be adapted to optimization schemes other than maximum directivity index.
  • the spherical microphone array has great potential in the accurate recording of spatial sound fields where the intended application is for multichannel or surround playback. It should be noted that current home theatre playback systems have five or six channels. Currently, there are no standardized or generally accepted microphone-recording methods that are designed for these multichannel playback systems. Microphone systems that have been described in this specification can be used for accurate surround-sound recording. The systems also have the capability of supplying, with little extra computation, many more playback channels. The inherent simplicity of the beamformer also allows for a computationally efficient algorithm for real-time applications.
  • the multiple channels of the orthogonal modal beams enable matrix decoding of these channels in a simple way that would allow easy tailoring of the audio output for any general loudspeaker playback system that includes monophonic up to in excess of sixteen channels (using up to third-order modal decomposition).
  • the spherical microphone systems described here could be used for archival recording of spatial audio to allow for future playback systems with a larger number of loudspeakers than current surround audio systems in use today.
  • the present invention has been described primarily in the context of a microphone array comprising a plurality of audio sensors mounted on the surface of an acoustically rigid sphere, the present invention is not so limited. In reality, no physical structure is ever perfectly rigid or perfectly spherical, and the present invention should not be interpreted as having to be limited to such ideal structures. Moreover, the present invention can be implemented in the context of shapes other than spheres that support orthogonal harmonic expansion, such as “spheroidal” oblates and prolates, where, as used in this specification, the term “spheroidal” also covers spheres. In general, the present invention can be implemented for any shape that supports orthogonal harmonic expansion of order two or greater.
  • the present invention may be implemented as circuit-based processes, including possible implementation on a single integrated circuit.
  • various functions of circuit elements may also be implemented as processing steps in a software program.
  • Such software may be employed in, for example, a digital signal processor, micro-controller, or general-purpose computer.
  • the present invention can be embodied in the form of methods and apparatuses for practicing those methods.
  • the present invention can also be embodied in the form of program code embodied in tangible media, such as floppy diskettes, CD-ROMs, hard drives, or any other machine-readable storage medium, wherein, when the program code is loaded into and executed by a machine, such as a computer, the machine becomes an apparatus for practicing the invention.
  • the present invention can also be embodied in the form of program code, for example, whether stored in a storage medium, loaded into and/or executed by a machine, or transmitted over some transmission medium or carrier, such as over electrical wiring or cabling, through fiber optics, or via electromagnetic radiation, wherein, when the program code is loaded into and executed by a machine, such as a computer, the machine becomes an apparatus for practicing the invention.
  • program code When implemented on a general-purpose processor, the program code segments combine with the processor to provide a unique device that operates analogously to specific logic circuits.

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WO2003061336A1 (fr) 2003-07-24
DE60336377D1 (de) 2011-04-28
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