EP1919251A1 - Anpassung der Gewichtsfaktoren für Strahlformung zur effizienten Implementierung von Breitband-Strahlformern - Google Patents

Anpassung der Gewichtsfaktoren für Strahlformung zur effizienten Implementierung von Breitband-Strahlformern Download PDF

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Publication number
EP1919251A1
EP1919251A1 EP06022602A EP06022602A EP1919251A1 EP 1919251 A1 EP1919251 A1 EP 1919251A1 EP 06022602 A EP06022602 A EP 06022602A EP 06022602 A EP06022602 A EP 06022602A EP 1919251 A1 EP1919251 A1 EP 1919251A1
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Prior art keywords
beamforming
filter
channel
weights
weight
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EP06022602A
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French (fr)
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EP1919251B1 (de
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Franck Beaucoup
Michael Tetelbaum
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Mitel Networks Corp
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Mitel Networks Corp
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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
    • 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
    • H04R2430/00—Signal processing covered by H04R, not provided for in its groups
    • H04R2430/03—Synergistic effects of band splitting and sub-band processing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R2430/00—Signal processing covered by H04R, not provided for in its groups
    • H04R2430/20—Processing of the output signals of the acoustic transducers of an array for obtaining a desired directivity characteristic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R25/00—Deaf-aid sets, i.e. electro-acoustic or electro-mechanical hearing aids; Electric tinnitus maskers providing an auditory perception
    • H04R25/40—Arrangements for obtaining a desired directivity characteristic
    • H04R25/407—Circuits for combining signals of a plurality of transducers

Definitions

  • the present invention relates to a beam forming design method and a real-time implementation structure that reduces the computational complexity of broadband beamformers.
  • Sensor array processing also known as beamforming
  • Beamforming consists of combining the signals received by several omni-directional sensors to provide spatial directivity (see H.L.Van Trees, "Optimum array processing (detection, estimation and modulation theory, part IV),” John Wiley and Sons, 2002 for a general presentation). Beamforming has been used for several decades for applications such as radar, sonar, hearing aids and smart antennas for telecommunications.
  • microphone arrays have also been used for low-cost desktop products such as end-point speech processing devices for Personal Computers (PC) applications (see M.Brandstein and D.Ward, "Microphone arrays, signal processing techniques and applications," Springer, 2001 ) and audio conference phones (see M.Tetelbaum and F.B imp, "Design and implementation of a conference phone based on microphone array technology" Proceedings of Global Signal Processing Conference and Expo (GSPx) 2004, San Jose, CA, Sep 2004 ).
  • PC Personal Computers
  • GSPx Global Signal Processing Conference and Expo
  • the computational complexity of array processing depends on such factors as the number of sensors (respectively sources), the amount of spatial directivity desired from the array, and the bandwidth of operation compared to its average frequency (narrow-band or broad-band beamforming, as defined in H.L.Van Trees, "Optimum array processing (detection, estimation and modulation theory, part IV),” John Wiley and Sons, 2002 and M.Brandstein and D.Ward, “Microphone arrays, signal processing techniques and applications,” Springer, 2001 ). For cost-sensitive applications and in scenarios where the number of sensors is large, this computational complexity can be a critical issue.
  • a beamformer can be described as a weighted summation of signals received by an array of sensors.
  • the signals are only submitted to pure delays, resulting in a beamformer known as the delay-and-sum beamformer (or conventional beamformer).
  • the weights applied to the various channels can use both magnitude and phase information to create more effective spatial filtering. In the traditional complex-domain representation of signals, these weights are therefore complex numbers.
  • these beamforming weights are chosen to optimise a criterion related to the directivity of the beamformer, such as in the popular Minimum Variance Distortionless Response (MVDR) and Linearly Constrained Minimum Variance (LCMV) beamformers (see H.L. Van Trees, “Optimum array processing (detection, estimation and modulation theory, part IV),” John Wiley and Sons, 2002 and M.Brandstein and D.Ward, “Microphone arrays, signal processing techniques and applications,” Springer, 2001 ).
  • MVDR Minimum Variance Distortionless Response
  • LCMV Linearly Constrained Minimum Variance
  • DFT Discrete Fourier Transform
  • H.L.Van Trees "Optimum array processing (detection, estimation and modulation theory, part IV),” John Wiley and Sons, 2002 ).
  • the principle is to make use of fast convolution in the frequency domain in order to reduce the computational complexity of the beamforming process.
  • Each sensor signal is transformed into the frequency domain with a DFT operation, and narrow-band beamforming is then performed independently on each individual bin in the frequency domain.
  • the resulting frequency-domain beamformer output is then brought back into the time domain with an Inverse DFT (IDFT).
  • IDFT Inverse DFT
  • This frequency domain technique may be implemented with block processing or with sample processing with the sliding DFT algorithm as explained in M.L.Van Trees, "Optimum array processing (detection, estimation and modulation theory, part IV),” John Wiley and Sons, 2002 .
  • the filtering operation in the frequency-domain can be performed with the traditional techniques of overlap-add or overlap-save (see S.Haykin, "Adaptive filter theory,” Prentice Hall, 1996 ).
  • the frequency domain weights correspond to time-domain filters that are as short as possible.
  • short time-domain filters are fitted to the original frequency-domain weights as described for time-domain implementations, followed by use of the frequency response of these time-domain filters to perform narrow-band beamforming on each bin in the frequency domain.
  • the step of designing short time-domain beamforming filters is an important step towards computational efficiency.
  • the present invention describes a novel design procedure that produces a more efficient time-domain representation of the frequency-domain weights and therefore results in more efficient real-time implementations, both in the time domain and in the frequency domain.
  • the conditioning stage is implemented so as to remove from all beamforming channels (by division in the frequency domain, and therefore without affecting the spatial directivity) some common characteristics in their weights' frequency responses.
  • the conditioning stage facilitates the filter fit on each channel, thereby reducing the filter order and consequently the computational complexity of the beamforming structure, whether time-domain or frequency-domain.
  • the resulting change in the beamformer's response to its look direction can be compensated for by a single-channel "conditioning equalisation" filter placed on the output of the beamformer.
  • an improvement of the beamforming design method comprising modifying each beamforming weight in the frequency domain by dividing each beamforming weight by a common characteristic established in the frequency response across an array of sensors prior to fitting each beamforming weight to a filter.
  • a weight-conditioning beamformer for providing spatial directivity, said beamformer comprising an array of sensors, corresponding beamforming filters fitted with conditioned beamforming weights, wherein each conditioned beamforming weight is obtained by dividing each beamforming weight by a common characteristic established in the frequency response across an array of sensors prior to fitting each beamforming weight to the filter, and a summer for summing the outputs of said filters.
  • Figure 1 is a block diagram of a time-domain implementation of a broadband beamformer.
  • Figure 2 is a block diagram of a frequency-domain implementation of a broadband beamformer.
  • Figure 3 is a process diagram of a broadband beamformer according to an embodiment of the invention.
  • Figure 4 is a block diagram of the embodiment shown in Figure 3, illustrating a time-domain implementation of a broadband beamformer with weight conditioning.
  • Figure 5 is a graph showing multi-channel normalized filter-fit quality according to a multi-channel normalised filter-fit error criterion with and without the weights condition step.
  • one approach for designing the time-domain filters is to first calculate complex-domain weights at discrete frequencies across the desired frequency range, and then fit a time-domain filter to the frequency response consistent of the complex beamforming weights over the whole frequency range for each particular channel.
  • each output from the array of sensors 12 is then filtered by the corresponding time-domain filter F k 14; the resulting outputs are then summed 16 and outputted for subsequent processing.
  • DFT beamforming makes use of fast convolution in the frequency domain in order to reduce the computational complexity of the beamforming process from an array of sensors 22.
  • Each sensor signal is transformed into the frequency domain with a DFT operation 24, and narrow-band beamforming 26 is then performed independently on each individual bin in the frequency domain.
  • the resulting frequency-domain beamformer output is then summed 28 brought back into the time domain with an Inverse DFT 30.
  • this approach is shown using the Fast Fourier Transform (FFT) algorithm.
  • FFT Fast Fourier Transform
  • the directivity of a beamformer regardless of the exact indicator that is used to measure it (e.g. directivity index, front-back ratio, signal-to-interference-plus-noise ratio, etc... see H.L.Van Trees, "Optimum array processing (detection, estimation and modulation theory, part IV),” John Wiley and Sons, 2002 or M.Brandstein and D.Ward, "Microphone arrays, signal processing techniques and applications," Springer, 2001 ) is homogeneous as a function of the beamforming weights or filters. Multiplying all channels by the same complex number at any given frequency does not alter the directivity of the resulting beamformer. For broad-band beamformers, multiplying weights for all channels by the same "frequency response" does not alter the directivity of the resulting beamformer (although it clearly affects its response in the look direction over the frequency range).
  • the exact indicator that is used to measure it e.g. directivity index, front-back ratio, signal-to-interference-plus
  • the weights are then filter fit 44.
  • the beamformer is then implemented 46 as a time-domain or frequency-domain beamformer. Note that since the conditioning stage affects the beamformer's frequency response in its look direction, compensation, if required, can be achieved by placing a "conditioning equalisation” filter at the output of the beamformer. This equalisation filter only affects the frequency response of the beamformer and not its directivity.
  • the present invention is not intended to be restricted to a specific conditioning function.
  • one of the beamforming channel weights, or a delayed version of it, is used as the conditioning function.
  • One advantage of this conditioning is that one channel becomes a trivial channel (pure delay) that does not need FIR filtering in the final implementation.
  • the resulting beamforming structure with the conditioning equalisation filter is shown In Figure 4 for a time-domain implementation. As shown, each output from the array of sensors 52 is filtered by the corresponding conditioned time-domain filter F k 54; the resulting outputs are then summed 60 and outputted for subsequent processing.
  • the summed signal is then subjected to a conditioning equalization filter 62; it will be appreciated that the conditioning equalization filter is optional, depending on the particular implementation. Although shown for time-domain implementation; one skilled in the art can easily derive the corresponding structure for a frequency-domain (DFT) implementation.
  • DFT frequency-domain
  • a "multi-channel normalised filter-fit error” is introduced as a cost function.
  • W j ( v k ), 1 ⁇ j ⁇ M , 1 ⁇ k ⁇ N denotes the complex-domain beamforming weights of the M channels over the discrete set of frequencies v k , 1 ⁇ k ⁇ N , and [ ⁇ 1 ⁇ 2 ... ⁇ N ] the (complex) values of the conditioning function on these same frequencies.
  • These weights are assumed to yield a distortionless beamformer in its look direction (e.g. MVDR or LCMV).
  • the cost function is defined as a .
  • ⁇ M ⁇ M ] v 1 ) denotes the frequency response at frequency v 1 of the filter adjusted (according to a given filter-fit procedure, for instance a simple least-squares fit (see S.Haykln, "Adaptive filter theory,” Prentice Hall, 1996 ) to the j th channel weight W , dot-multiplied (that is, multiplied element-wise) by the conditioning function [ ⁇ 1 ⁇ 2 , ... ⁇ M ]. Note that the reason for the normalisation factor
  • Figure 5 shows the values of this filter-fit quality criterion as a function of the filter order, with and without the weights conditioning step, for a regularised MVDR beamformer over the frequency range [300Hz, 3300Hz] on a 6-microphone uniform linear array of 15cm in length.
  • the weights conditioning step reduces the length of the beamforming filters by roughly 30% for the same quality of filter fit (and therefore the same directivity).
  • the present invention describes a beamforming design method and a real-time implementation structure that can significantly reduce the computational complexity of broadband beamformers without affecting their performance in terms of spatial directivity or robustness to uncorrelated noise.
  • the invention applies equally to arrays of sources for spatially directive transmitters.
  • the time-domain filters fitted with the conditioned weights would be applied to the input signals to the transmitter, as opposed to the output signals of the sensors.
  • the present invention pertains to the design procedure making use of conditioning function, and is not restricted to a specific conditioning function. Many choices are possible for the conditioning function; the present invention in intended to cover all choices as long as they fit in the framework of the design procedure shown in Figure 3.
  • one skilled in the art could search for a function that would be optimal according to some criterion related to the quality of the filter fit, or the directivity cost function used to calculate the frequency-domain beamforming weights.
  • the multi-channel normalised filter-fit error function described above could represent such a criterion.
  • a traditional gradient-based optimisation procedure could be used to determine the vector [ ⁇ 1 ⁇ 2 ... ⁇ M ] that minimises this function.
  • the unknown vector must be normalised one way or another in order to have access to local minima.
  • fix ⁇ 1 1 and therefore look for a conditioning vector of the form [1 ⁇ 2 ... ⁇ M ].
  • the above discussion relates to the present invention in the context of an audio conferencing environment.
  • other applications making use of fixed beamforming in the presence of some kind of isotropic noise (e.g. any audio processing) could potentially benefit from it.
  • adaptive beamforming and specifically adaptive interference cancellation the outcome is less certain because there is no a-priori guarantee that all frequency-domain beamforming weights will indeed present a strong common pattern in their frequency response and therefore benefit from the conditioning stage.
  • the use of the aforementioned beamforming weights conditioning stage in a real-time scenario would also fall within the scope of the present invention.

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  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Otolaryngology (AREA)
  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Acoustics & Sound (AREA)
  • Signal Processing (AREA)
  • Circuit For Audible Band Transducer (AREA)
  • Obtaining Desirable Characteristics In Audible-Bandwidth Transducers (AREA)
EP20060022602 2006-10-30 2006-10-30 Anpassung der Gewichtsfaktoren für Strahlformung zur effizienten Implementierung von Breitband-Strahlformern Active EP1919251B1 (de)

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Cited By (16)

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Publication number Priority date Publication date Assignee Title
GB2495128A (en) * 2011-09-30 2013-04-03 Skype Computing beamformer coefficients making use of a plurality of sets of theoretical statistical data
CN103969630A (zh) * 2014-05-14 2014-08-06 哈尔滨工程大学 一种基于频率响应不变的稳健宽带波束形成方法
US8824693B2 (en) 2011-09-30 2014-09-02 Skype Processing audio signals
CN104133205A (zh) * 2014-06-30 2014-11-05 电子科技大学 一种树形宽带波束形成器
US8891785B2 (en) 2011-09-30 2014-11-18 Skype Processing signals
US8981994B2 (en) 2011-09-30 2015-03-17 Skype Processing signals
US9031257B2 (en) 2011-09-30 2015-05-12 Skype Processing signals
US9042574B2 (en) 2011-09-30 2015-05-26 Skype Processing audio signals
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US9111543B2 (en) 2011-11-25 2015-08-18 Skype Processing signals
US9269367B2 (en) 2011-07-05 2016-02-23 Skype Limited Processing audio signals during a communication event
WO2016026970A1 (de) * 2014-08-22 2016-02-25 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Fir-filterkoeffizientenberechnung für beamforming-filter
CN106911991A (zh) * 2015-12-22 2017-06-30 奥迪康有限公司 包括传声器控制系统的听力装置
CN107925818A (zh) * 2015-10-15 2018-04-17 华为技术有限公司 用于声音处理节点装置的声音处理节点
CN112327305A (zh) * 2020-11-06 2021-02-05 中国人民解放军海军潜艇学院 一种快速频域宽带mvdr声纳波束形成方法
CN116301195B (zh) * 2023-05-16 2023-09-05 湖南工商大学 函数波束优化方法与装置

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GB2496660B (en) 2011-11-18 2014-06-04 Skype Processing audio signals

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US9269367B2 (en) 2011-07-05 2016-02-23 Skype Limited Processing audio signals during a communication event
GB2495128B (en) * 2011-09-30 2018-04-04 Skype Processing signals
US8981994B2 (en) 2011-09-30 2015-03-17 Skype Processing signals
US8891785B2 (en) 2011-09-30 2014-11-18 Skype Processing signals
GB2495128A (en) * 2011-09-30 2013-04-03 Skype Computing beamformer coefficients making use of a plurality of sets of theoretical statistical data
US9031257B2 (en) 2011-09-30 2015-05-12 Skype Processing signals
US9042574B2 (en) 2011-09-30 2015-05-26 Skype Processing audio signals
US8824693B2 (en) 2011-09-30 2014-09-02 Skype Processing audio signals
US9042573B2 (en) 2011-09-30 2015-05-26 Skype Processing signals
US9111543B2 (en) 2011-11-25 2015-08-18 Skype Processing signals
US9042575B2 (en) 2011-12-08 2015-05-26 Skype Processing audio signals
CN103969630A (zh) * 2014-05-14 2014-08-06 哈尔滨工程大学 一种基于频率响应不变的稳健宽带波束形成方法
CN103969630B (zh) * 2014-05-14 2016-09-14 哈尔滨工程大学 一种基于频率响应不变的稳健宽带波束形成方法
CN104133205B (zh) * 2014-06-30 2016-10-12 电子科技大学 一种树形宽带波束形成器
CN104133205A (zh) * 2014-06-30 2014-11-05 电子科技大学 一种树形宽带波束形成器
US10419849B2 (en) 2014-08-22 2019-09-17 Fraunhofer-Gesellschaft Zur Foerderung Der Angewandten Forschung E.V. FIR filter coefficient calculation for beam-forming filters
CN107223345A (zh) * 2014-08-22 2017-09-29 弗劳恩霍夫应用研究促进协会 用于波束成形滤波器的fir滤波器系数计算
JP2017531971A (ja) * 2014-08-22 2017-10-26 フラウンホッファー−ゲゼルシャフト ツァ フェルダールング デァ アンゲヴァンテン フォアシュンク エー．ファオ ビームフォーミングフィルタのためのｆｉｒフィルタ係数の算出
WO2016026970A1 (de) * 2014-08-22 2016-02-25 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Fir-filterkoeffizientenberechnung für beamforming-filter
CN107223345B (zh) * 2014-08-22 2020-04-07 弗劳恩霍夫应用研究促进协会 用于波束成形滤波器的fir滤波器系数计算
CN107925818A (zh) * 2015-10-15 2018-04-17 华为技术有限公司 用于声音处理节点装置的声音处理节点
CN107925818B (zh) * 2015-10-15 2020-10-16 华为技术有限公司 用于声音处理节点装置的声音处理节点
CN106911991A (zh) * 2015-12-22 2017-06-30 奥迪康有限公司 包括传声器控制系统的听力装置
CN106911991B (zh) * 2015-12-22 2021-01-05 奥迪康有限公司 包括传声器控制系统的听力装置
CN112327305A (zh) * 2020-11-06 2021-02-05 中国人民解放军海军潜艇学院 一种快速频域宽带mvdr声纳波束形成方法
CN116301195B (zh) * 2023-05-16 2023-09-05 湖南工商大学 函数波束优化方法与装置

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