Automatic noise control

Abstract

An automatic noise control includes: evaluating the magnitude of an acceleration acting on an acceleration sensor and generating a reference signal representing the magnitude of the acceleration, the acceleration representing an unwanted noise sound generated by a noise source; filtering the reference signal through a noise control transfer function to generate an anti-noise signal; and converting the anti-noise signal into an anti-noise sound through a speaker. The automatic noise control also includes: receiving through a microphone the noise sound after passing through a primary path from the noise source to the microphone according to a primary path transfer function and the anti-noise sound after passing through a secondary path from the speaker to the microphone according to a secondary path transfer function; converting through the microphone the sum of the received noise sound and the received anti-noise sound into an error signal; and controlling the noise control transfer function based on the error signal from the microphone and a filtered or unfiltered reference signal from the acceleration sensor so that the anti-noise sound after passing through the secondary path is the inverse of the noise sound after passing through the primary path. The automatic noise control also includes: controlling a shadow noise control transfer function based on a shadow error signal and the filtered or unfiltered reference signal; generating the shadow error signal based on a filtered or unfiltered shadow anti-noise signal and the error signal; and replacing the noise control transfer function with the shadow noise control transfer function if the shadow error signal is less than the error signal.

Description

Technical Field

[0001] The present disclosure relates to systems and methods (generally referred to as "systems") for automatic noise control. Background Art

[0002] Sound is a pressure wave composed of alternating cycles of compression and expansion. To cancel noise, a sound wave is emitted with the same amplitude, but with the compression and expansion in opposite phase to the original sound. The waves combine in a process called interference to form a new wave and effectively cancel each other out—an effect known as destructive interference. Modern active noise control (ANC) is typically implemented using analog and / or digital signal processing. An adaptive algorithm can be designed to analyze the waveform of the background noise, and based on specific analog or digital signal processing, the adaptive algorithm can generate a signal that will phase shift or invert the polarity of the original signal. This inverted signal is then amplified and the transducer generates a sound wave that is proportional to the amplitude of the original waveform but in opposite phase, thereby creating destructive interference. This effectively reduces the amplitude of the perceived noise.

[0003] Land-based vehicles generate low-frequency noise known as road noise as they travel over pavement and other surfaces. As the wheels travel over the road surface, the road noise is at least partially transmitted through vehicle components such as tires, wheels, hubs, chassis components, suspension components, and bodywork, and can be heard within the vehicle cabin. In order to reduce vibrations in vehicle components and thus reduce the road noise experienced by cabin occupants, an ANC system of the type described above may be employed. In the field, situations may arise where an ANC system installed in a vehicle tends to generate unwanted sounds on its own. It is desirable to suppress or avoid such unwanted sounds. Summary of the invention

[0004] An automatic noise control system includes: an acceleration sensor configured to evaluate the magnitude of acceleration acting thereon and generate a reference signal representing the magnitude of acceleration, the acceleration representing unwanted noise sound generated by a noise source; and a noise control filter operably coupled to the acceleration sensor and configured to filter the reference signal using a noise control transfer function to generate an anti-noise signal. The system also includes: a speaker operably coupled to the noise control filter and configured to convert the anti-noise signal into an anti-noise sound; and a microphone configured to receive the noise sound after being transferred via a primary path from the noise source to the microphone according to the primary path transfer function and the anti-noise sound after being transferred via a secondary path from the speaker to the microphone according to the secondary path transfer function, and the microphone is further configured to convert the sum of the received noise sound and the received anti-noise sound into an error signal. The filter controller is operably coupled to the noise control filter, the microphone, and the accelerometer, and is configured to control the noise control transfer function of the noise control filter based on the error signal from the microphone and the filtered or unfiltered reference signal from the accelerometer, so that the anti-noise sound after passing through the secondary path is the inverse of the noise sound after passing through the primary path. The shadow noise control filter is operably coupled to the accelerometer and is configured to filter the reference signal through the shadow noise control transfer function to generate a shadow anti-noise signal. The shadow filter controller is operably coupled to the shadow noise control filter and the accelerometer, and is configured to control the noise control transfer function of the shadow noise control filter based on the shadow error signal from the microphone and the filtered or unfiltered reference signal from the accelerometer. The shadow error signal generator is operably coupled to the shadow noise control filter, the shadow filter controller, and the microphone, and is configured to generate a shadow error signal based on the filtered or unfiltered shadow anti-noise signal from the shadow noise control filter and the error signal from the microphone. A coefficient copy controller is operably coupled to the shadow error signal generator, the shadow noise control filter and the microphone, and is configured to copy current coefficients of a shadow noise transfer function constituting the shadow noise control filter into the noise control filter to replace the current noise control transfer function when the shadow error signal is less than the error signal.

[0005] An automatic noise control method includes: evaluating the magnitude of acceleration acting on an acceleration sensor and generating a reference signal representing the magnitude of acceleration, the acceleration representing unwanted noise sound generated by a noise source; filtering the reference signal through a noise control transfer function to generate an anti-noise signal; and converting the anti-noise signal into an anti-noise sound through a speaker. The method also includes: receiving through a microphone a noise sound after being transmitted through a primary path from a noise source to a microphone according to a primary path transfer function and an anti-noise sound after being transmitted through a secondary path from a speaker to the microphone according to a secondary path transfer function; converting through the microphone a sum of the received noise sound and the received anti-noise sound into an error signal; and controlling the noise control transfer function based on the error signal from the microphone and a filtered or unfiltered reference signal from the acceleration sensor so that the anti-noise sound after being transmitted through the secondary path is the inverse of the noise sound after being transmitted through the primary path. The method also includes: controlling a shadow noise control transfer function based on a shadow error signal and a filtered or unfiltered reference signal; generating a shadow error signal based on a filtered or unfiltered shadow anti-noise signal and the error signal; and replacing the noise control transfer function with the shadow noise control transfer function if the shadow error signal is less than the error signal.

[0006] Other systems, methods, features and advantages will be or will become apparent to those skilled in the art after reviewing the following detailed description and drawings. It is intended that all such additional systems, methods, features and advantages be included in this description, be within the scope of the present invention, and be protected by the appended claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] The system may be better understood with reference to the following drawings and descriptions. The components in the figures are not necessarily drawn to scale, but emphasis is placed on illustrating the principles of the present invention. In addition, the same reference numerals in the figures designate corresponding parts throughout the different views.

[0008] Figure 1 is a schematic diagram illustrating an exemplary basic single-channel or multi-channel feed-forward ANC system using the FXLMS algorithm.

[0009] Figure 2 is shown with additional update controller Figure 1 Schematic diagram of the ANC system shown in .

[0010] Figure 3 is a leakage factor frequency graph showing the frequency-dependent leakage factor λ(f) when the level of the reference signal is equal to or greater than the threshold level.

[0011] Figure 4is a leakage factor frequency graph showing the frequency-dependent leakage factor λ(f) when the level of the reference signal is much smaller than the threshold level.

[0012] Figure 5 is a leakage factor frequency graph showing the frequency-dependent leakage factor λ(f) when the level of the reference signal is much smaller than the threshold level.

[0013] Figure 6 is shown with an additional leakage controller Figure 1 Schematic diagram of the ANC system shown in .

[0014] Figure 7 is a diagram showing a modified version with a shadow filter Figure 6 Schematic diagram of the ANC system shown in .

[0015] Figure 8 is a flow chart illustrating an exemplary method for automatic noise control. DETAILED DESCRIPTION

[0016] Investigations have shown that unwanted sounds generated by the ANC system (and method) installed in the vehicle itself often occur when a situation with a high ambient noise level (e.g., driving on a cobblestone road) transitions to a situation with a low ambient noise level (e.g., driving on a new asphalt road). A closer examination of the filter coefficients of the noise control filter operating under the above conditions shows that these coefficients tend to cause the filter to provide lower amplification / higher attenuation in low noise situations and higher amplification / lower attenuation as noise increases.

[0017] refer to Figure 1 , an exemplary single-channel or multi-channel ANC system may include a plurality of (L≥1) loudspeakers 101 as actuators that convert electrical signals into sound waves and a plurality of (M) error microphones 102 as sensors that convert sound waves into electrical signals. A secondary path 103 transfers sound waves from the loudspeakers 101 to the error microphones 102, which also receive interference sounds d[n] via a primary path 104 based on a reference signal x[n] originating from a noise signal source 105. Sound waves transferred by the primary path 104 having a primary path transfer function P(z) and the secondary path having a secondary path transfer function S(z) interfere with each other, which can be described by a summation operation.

[0018] According to the main path transfer function P(z), the interference sound wave d[n] corresponds to R≥1 reference signals x[n]. The R reference signals x[n] are optionally composed of a signal with transfer function The secondary path modeling filter 106 models the secondary path transfer function S(z) to provide L·M filtered reference signals. The M≥1 signals from the M≥1 microphones 102 (referred to herein as error signals e[n]) represent the performance of the system, for example, taking into account the cancellation performance of the L·M filtered reference signals, and are supplied to a filter controller 107, which generates a transfer function W(z) for updating the controllable noise control filter 108, i.e., a control signal for updating its filter coefficients. The noise control filter 108 filters the R reference signals x[n] with the transfer function W(z) and is connected upstream of the loudspeaker 101 to provide a loudspeaker signal y[n] thereto. The transfer functions P(z), S(z) and can be viewed as a filter matrix and the signals x[n], y[n], d[n], e[n], and y[n] can be viewed as signal vectors. Figure 1 No distinction is made between the acoustic and electrical domains, but all elements and operations shown are in the electrical domain, except for the primary path 104, the secondary path 103, and the acoustic interference at the microphone 102, which are all in the acoustic domain. The loudspeaker 101 and the error microphone 102 can be considered as transducers from the electrical domain to the acoustic domain and from the acoustic domain to the electrical domain, respectively.

[0019] The primary path 104 and the secondary path 103 have spectral behaviors that vary with time. For example, whenever something affects or changes the acoustics, the secondary path 103 is modified. Therefore, the secondary path transfer function matrix S(z) is time-dependent. In this example, the updating of the corresponding transfer function matrix W(z) of the noise control filter 108 is performed according to a filtered X-least mean square (FX-LMS) algorithm, where X represents the input signal, for example, R reference signals x[n]. However, any other suitable algorithm may also be used.

[0020] Investigations have further shown that in ANC systems using acceleration sensors, for example for picking up reference signals, the characteristics of the acceleration sensors have a significant impact on the performance of the ANC system, and in particular on the generation of interference signals by the ANC system itself. Figure 1As can be seen in FIG. 1 , in this example, R≥1 reference signals x[n] provided by an acceleration sensor (e.g., as source 105) are filtered with a transfer function W(z), which means that the amplitude of the reference signal x[n] is weighted with a (frequency-dependent) weight determined by the filter coefficients of the noise control filter 108. For example, when the weight determined by the filter coefficients increases, the signal output by the noise control filter 108 is amplified more and more or attenuated less and less, as the case may be. Therefore, the level of the L signals y[n] provided by the noise control filter 108 to the L loudspeakers increases accordingly, and the level of the anti-noise sound corresponding to the sound broadcast by the loudspeakers via the secondary path to the listening position also increases accordingly. The listening position is defined here by the positions of the M microphones. When the original noise and the anti-noise adapted thereto have higher signal levels, filter coefficients for higher amplification / lower attenuation appear.

[0021] If an acceleration sensor with a small dynamic range (i.e., the range between the minimum and maximum amplitude) and / or otherwise unsuitable (e.g., exhibiting an incorrect bias point and / or an unsuitable acceleration sensing range) is used, and if the raw noise changes from a higher signal level to a lower signal level, the coefficients may freeze for a certain time at a (high) weight corresponding to a high-level anti-noise signal, e.g., in response to a high-level raw noise that occurred previously but is now low-level. This means that in this case, the anti-noise generated does not match the raw noise and, moreover, has a higher level than the raw noise, which is perceived by the listener as an interfering sound. In the field, acceleration sensors with a wider dynamic range are either not available, e.g., for automotive applications and their requirements, or are so costly that conventional ANC systems employing such types of acceleration sensors often generate interfering sounds themselves.

[0022] As described above, an ANC system that has been adapted to a high level noise situation (e.g., driving on a cobblestone road) exhibits filter coefficients that result in a higher amplification or lower attenuation of the reference signal x[n]. After the high level noise situation becomes a low level noise situation, these correspondingly adapted filter coefficients and thus adapted amplification / attenuation are maintained for a certain period of time. For example, since in automotive applications, the sound levels of high level noise situations and low level noise situations are generally not much different at lower frequencies, the change in noise situation here has substantially no adverse effect. However, at intermediate and high frequencies, the levels under different noise situations are significantly different, which prompts the ANC system to produce unwanted sounds and is referred to herein as the waterbed effect. In order to avoid the generation of such unwanted sounds, the adaptive process remains active, which allows the filter coefficients to be quickly brought to the desired values. Various methods of accelerating the adaptive process may be used alternatively or in different combinations.

[0023] For better understanding, the following description refers to L=1, M=1 and R=1, i.e., a single-channel system. However, by combining L·M·R single-channel systems, a system in which at least one of L, M and R is greater than 1 (multi-channel system) can be easily derived.

[0024] exist Figure 2 In one embodiment shown in FIG. 1 , a memory 201 for storing various predetermined filter coefficient sets and a noise condition detector 202 for detecting various different noise conditions are added to the Figure 1 . In addition, the filter controller 107 is connected to the memory 201 and the noise situation detector 202, and if a change in the noise situation is detected by the noise situation detector 202 or based on the noise situation detector, the filter controller is also capable of copying some or all of the stored predetermined filter coefficient sets to the noise control filter 108. The stored predetermined filter coefficient sets may, for example, represent commonly occurring noise situations, or may be previously adapted sets for specific or similar noise situations. The selection of the stored predetermined filter coefficient sets actually copied to the noise control filter 108 may depend on or be independent of the detected noise situation (e.g., performed periodically). Alternatively, if a change in the noise situation is detected, the actual coefficient set may be modified in an appropriate manner, such as by dividing or multiplying the current coefficient set by a constant or a variable, frequency-dependent or independent parameter. For example, the noise situation detector 202 may employ artificial intelligence to evaluate the sound spectra of different noise situations and reliably identify different noise situations based thereon.

[0025] In another exemplary embodiment, a spectral (frequency-dependent) leakage, for example represented by a leakage factor λ(f), is applied to the transfer function W(z) of the noise control filter 108 during the updating of the transfer function W(z). Also referred to as the transfer function W(e) with applied leakage jωt ,n+1), the transfer function W(z) can be described as follows:

[0026]

[0027] Where n is a discrete time point, ω is the angular frequency, t is the time parameter, λ(e jωt ,n) is the frequency and time-dependent leakage factor, μ(e jωt ,n) is the adaptive step size, P XX (e jωt ,n) is the level of the reference signal x[n] and Δ is a fixed factor that is either frequency-dependent or independent. This helps avoid division by zero or small values ​​to keep the resulting update term within a certain robust range. E(e j ωt ,n) is the frequency spectrum of the error signal e[n], and is the spectrum of the filtered reference signal x[n]. In view of the above findings, in most cases, even in the case of reference signals with low signal levels, lower frequencies do not significantly contribute to the generation of unwanted signals (corresponding to unwanted sounds), and leakage may be frequency-dependent in addition. Furthermore, the leakage may additionally or alternatively be made dependent on the current level of the corresponding reference signal x[n], i.e. the signal from the corresponding acceleration sensor. The dependence on the current reference signal level implies a time dependence, so that for example at least at higher frequencies, a higher degree of leakage is applied at a lower reference signal level than at a higher reference signal level, wherein, depending on the circumstances, the leakage factor may even be zero.

[0028] Figure 3 It is shown in P XX ≥P XXTH , which represents the case with a high reference signal level and thus represents the most common case in the art. As can be seen, the frequency at which the leakage factor λ(f) has a value of 1 is constant and is therefore higher than a predetermined minimum leakage factor λ having a value of, for example, 0.99. Min (f) P XXTH Specify a predetermined threshold level.

[0029] Figure 4 It is shown in P XX <P XXTH , which represents the case with a medium reference signal level. As can be seen, the leakage factor λ(f) is at a value of 1 for lower frequencies and decreases with frequency to a value slightly above 0.99, depending on the level and optionally P XX The spectral shape (and limits) of

[0030] Figure 5 It is shown in P XX ≥P XXTH Figure 1 shows the leakage factor frequency diagram of the leakage factor λ(f) as a function of frequency when the reference signal level is high. As can be seen, the leakage factor λ(f) is 1 at the lowest frequency and decreases (and is limited) to 0.99 at the highest frequency, depending on P. XX .

[0031] from Figures 3 to 5 It can be inferred that the reference signal P XX The current level and the predetermined threshold level P XXTH The difference between can be used to scale the frequency-dependent but shape-constant leakage, which means that the curve of the leakage factor λ(f) can be scaled while maintaining its shape. Figures 3 to 5The diagram shown moves vertically within a range where the upper limit is the value 1 and the lower limit is a predetermined minimum leakage factor λ Min (f). Thus, due to leakage, at lower noise levels, the filter coefficients are forced to change in a way that the correspondingly generated weights applied to the reference signal are reduced, but subject to a predetermined minimum leakage factor λ Min (f) unless the adaptive process would counteract this if sufficiently high noise levels were present in a particular frequency range. Otherwise, the filter coefficients are altered in such a way that the correspondingly generated weights applied to the reference signal are also reduced, resulting in the attenuation of such unwanted sounds by lower weights in frequency ranges where higher levels of such unwanted sounds might be expected due to the waterbed effect.

[0032] Alternatively or additionally, leakage may be controlled based on (the weights established by) the filter coefficients.For example, leakage may be applied only when (the weights established by) the filter coefficients exceed one or more predetermined thresholds.

[0033] Another exemplary embodiment of leakage control includes continuously monitoring whether the ANC system generates unwanted sounds in certain frequency ranges. If the generation of such unwanted sounds is detected, leakage can be applied to these specific frequency ranges, for example because the ANC system becomes unstable or a reference signal with a smaller dynamic range, which generates noise or interference due to acceleration, is amplified too much by the corresponding noise control filter.

[0034] like Figure 6 As depicted in FIG. 6 , an adaptive controller 601, an additional noise control filter 602 and a subtractor 603 are added to Figure 1 The ANC system shown in FIG. 1 (when assuming L=1, M=1 and R=1). The adaptive controller 601 is connected to receive the corresponding error signal e[n] from the microphone 102 and the estimated interference signal output by the subtractor 603. The subtractor 603 is connected to receive the corresponding error signal e[n] from the microphone 102 and the output signal from the additional noise control filter 602. The additional noise control filter 602 is connected to receive the filtered reference signal from the corresponding secondary path modeling filter 106 and the corresponding copy of the coefficients of the noise control filter 108 through the filter controller 107. The filter controller 107 is further connected to receive a control signal for controlling the filter coefficients of the noise control filter 107 from the adaptive controller 601.

[0035] Combined with the above Figure 6 Described Figure 1The addition of is used to detect unwanted sounds generated by the corresponding noise control filter 108 and control the noise control filter 108 to suppress the generation of unwanted sounds. To this end, a "real" microphone signal (i.e., a microphone signal derived when the noise control filter 108 is activated) is compared (spectrally) with a "virtual" microphone signal (i.e., a microphone signal derived when the noise control filter 108 is not activated). When the noise control filter 108 is activated, the desired microphone signal is the error signal e[n] provided by the microphone 102. When the noise control filter 108 is not activated, the error signal e[n] cannot be used as is, and is therefore simulated, i.e., artificially generated, based on the current error signal e[n]. Since the error signal e[n] does not contain the sound provided by the noise control filter 108 when the noise control filter 108 is not activated, i.e., there is no anti-noise, the anti-noise is modeled by the secondary path modeling filter 106 and the additional noise control filter 602 based on the reference signal x[n], and then subtracted from the current error signal e[n], i.e., the error signal e[n] that does not contain the anti-noise. Thus, the adaptive controller 601 (e.g., continuously) compares the (most recently) picked-up microphone signal when the noise control filter 108 was activated, i.e., the error signal e[n], with the (most recently) simulated microphone signal, i.e., the estimated interference signal In comparison.

[0036] For example, if Where TH is an optional threshold value, which indicates that the microphone signal when the corresponding noise control filter 108 is activated, that is, the error signal e[n] is greater than the threshold TH and when the corresponding noise control filter 108, that is, the estimated interference signal The leakage is applied if the error signal e[n] is multiplied by the microphone signal when not activated. Optionally, this analysis can be performed at each frequency, for example for a number of subsequent frequency ranges, so that the leakage is only applied to those frequency ranges that meet the above requirements. The leakage can vary and can depend, for example, on the error signal e[n] and the estimated interference signal The difference between , i.e. the higher the unwanted sound, the higher the leakage, which is automatically controlled similarly to the automatic gain control amplifier. To this end, the leakage increases until the error signal e[n] (in the corresponding frequency range) starts to decrease and approaches the estimated interference signal However, the estimated interference signal is not weakened. If the error signal e[n] weakens the corresponding estimated interference signal Then the leakage will be too large and it will not be possible to recognize when to stop producing the unwanted sound. Therefore, the leakage is controlled so that

[0037] Adaptive controller 601, additional noise control filter 602 and subtractor 603 embody a leakage controller that assesses the type of noise situation and adapts the leakage of the noise control transfer function to the assessed noise situation. Other ways of controlling leakage, such as the various options outlined above may additionally or alternatively be implemented in the leakage controller.

[0038] refer to Figure 7 In another embodiment, Figure 6 The adaptive controller 601 of the ANC system shown in FIG. 1 is replaced by a shadow filter arrangement. The shadow filter arrangement comprises: a coefficient copy controller 701 connected to receive an error signal e[n]; a shadow filter coefficient set W SF (z); and the shadow filter error signal e SF [n], the shadow filter error signal is connected to send or not send the shadow filter coefficient set W to the filter controller 107 under the control of the coefficient copy controller 701 SF (z). Shadow filter error signal e SF [n] is provided by adder 702, which is connected to receive signal and the output signal of the additional secondary path modeling filter 703, the secondary path modeling filter having a transfer function that models the secondary path transfer function S(z) The additional secondary path modeling filter 703 is connected to receive the signal y from the shadow filter 704 SF [n], the shadow filter has a shadow filter transfer function W SF (z) and connected to receive the reference signal x(n) from the R accelerometers 105 and use the shadow filter transfer function W SF (z) filtering the reference signal. The shadow filter 704 is also connected to be controlled by a filter controller 705, which is connected to receive the filtered reference signal from the secondary path modeling filter 106 and the shadow filter error signal e from the adder 702. SF The level controlled coefficient storage and retrieval controller 706 is connected to receive the reference signal x[n] and is configured to control the copying of coefficients from the level controlled coefficient storage and retrieval controller 706 to the filter controller 705 and vice versa.

[0039] If you can Figure 7 It can be seen that when better results can be achieved by the coefficients of the shadow filter 704, that is, when the error signal e SF When [n] is less than the error signal e[n], the shadow filter transfer function W is implemented SFThe filter coefficients of (z) are copied from the shadow filter 704 to the noise control filter 108 (and the additional noise control filter 602). Optionally, additionally and as above in combination Figure 2 As described above, one or more sets of filter coefficients may be stored in a memory ( Figure 7 The reference signal x[n] may be copied from the memory to the shadow filter 704 and, as the case may be, to the noise control filter 108 (and the additional noise control filter 602) if a change in the noise situation is monitored or under any other appropriate conditions, i.e. when the level of the reference signal x[n] is within a predetermined level range.

[0040] In order to avoid multiple switching between different detected noise conditions (e.g., at range limits), a hysteresis function may be applied. The stored set of predetermined filter coefficients may, for example, represent commonly occurring noise conditions, or may be a previously adapted set for a specific or similar noise condition. The selection of the stored set of predetermined filter coefficients that is actually copied into the noise control filter 108 may depend on or be independent of the detected noise conditions. Alternatively or additionally, the leakage ( Figure 7 can be applied to Figure 7 The ANC system depicted in FIG. 1 , however, is combined with the above Figure 6 The leakage functions and implementations described are the same or similar. Figure 7 The system shown in not only overcomes the drawbacks described in the background section above, but also allows detecting instabilities of the ANC system. Furthermore, the amplification of the signal from the acceleration sensor can be selected to adapt the bias point of the acceleration sensor to the ANC system.

[0041] although Figure 7 The system shown in Figure 6 The system shown in , but it can also be based on Figure 1 The system shown in . Figure 2 The system shown in Figure 6 and Figure 7 The system combination shown in .

[0042] Figure 8An automatic noise control method is shown, which includes: evaluating the magnitude of acceleration acting on an acceleration sensor (process 801) and generating a reference signal representing the magnitude of acceleration (process 802), the acceleration representing an unwanted noise sound generated by a noise source; filtering the reference signal through a noise control transfer function to generate an anti-noise signal (process 803); and converting the anti-noise signal into an anti-noise sound through a speaker (process 804). The method also includes receiving through a microphone a noise sound after passing through a primary path from a noise source to a microphone according to a primary path transfer function and an anti-noise sound after passing through a secondary path from a speaker to a microphone according to a secondary path transfer function (process 805); and converting the sum of the received noise sound and the received anti-noise sound into an error signal through the microphone (process 806). The method also includes controlling the noise control transfer function based on the error signal from the microphone and the filtered or unfiltered reference signal from the acceleration sensor so that the anti-noise sound after passing through the secondary path is the anti-phase of the noise sound after passing through the primary path (process 807). The method also includes: controlling a shadow noise control transfer function based on a shadow error signal and a filtered or unfiltered reference signal (process 808); generating a shadow error signal based on a filtered or unfiltered shadow anti-noise signal and an error signal (process 809); and replacing the noise control transfer function with the shadow noise control transfer function if the shadow error signal is less than the error signal (process 810).

[0043] The above methods may be encoded in a computer readable medium such as a CD ROM, disk, flash memory, RAM or ROM, electromagnetic signal or other machine readable medium as instructions executed by a processor. Alternatively or additionally, any type of logic may be utilized and may be implemented as analog or digital logic using: hardware such as one or more integrated circuits (including amplifiers, adders, delays, and filters), or one or more processors that execute instructions for amplification, addition, delay, and filtering; or software in an application programming interface (API) or dynamic link library (DLL), functions available in shared memory or defined as local or remote procedure calls; or a combination of hardware and software.

[0044] The method may be implemented by software and / or firmware stored on or in a computer-readable medium, a machine-readable medium, a propagation signal medium, and / or a signal-bearing medium. The medium may include any device that contains, stores, communicates, propagates, or transmits executable instructions for use by or in conjunction with an instruction-executable system, device, or apparatus. The machine-readable medium may be, but is not limited to, an electronic, magnetic, optical, electromagnetic, or infrared signal or semiconductor system, device, apparatus, or propagation medium. A non-exhaustive list of examples of machine-readable media includes: a magnetic or optical disk; a volatile memory, such as a random access memory "RAM", a read-only memory "ROM", an erasable programmable read-only memory (i.e., EPROM), or a flash memory; or an optical fiber. The machine-readable medium may also include a tangible medium on which executable instructions are printed, because the logic may be electronically stored as an image or other format (e.g., by optical scanning), and then compiled and / or interpreted or otherwise processed. The processed medium may then be stored in a computer and / or machine memory.

[0045] The system may include additional or different logic and may be implemented in many different ways. The controller may be implemented as a microprocessor, a microcontroller, an application specific integrated circuit (ASIC), discrete logic, or a combination of other types of circuits or logic. Similarly, the memory may be a DRAM, SRAM, flash memory, or other types of memory. Parameters (e.g., conditions and thresholds) and other data structures may be stored and managed separately, may be merged into a single memory or database, or may be logically and physically organized in many different ways. Programs and instruction sets may be part of a single program, a separate program, or distributed in multiple memories and processors. The system may be included in a variety of electronic devices, including cellular phones, headsets, hands-free devices, hands-free phones, communication interfaces, or infotainment systems.

[0046] The description of the embodiments has been presented for illustration and description purposes. Suitable modifications and variations to the embodiments may be made in accordance with the above description or may be obtained from the practice methods. For example, unless otherwise indicated, one or more of the described methods may be performed by a suitable device and / or combination of devices. In addition to the sequence described in this application, the described methods and associated actions may also be performed in various sequences in parallel and / or simultaneously. The described systems are exemplary in nature and may include additional elements and / or omitted elements.

[0047] As used in this application, elements or steps stated in the singular and beginning with the word "a" or "an" should be understood as not excluding the plural form of the elements or steps, unless such exclusion is stated. In addition, reference to "one embodiment" or "an example" of the present disclosure is not intended to be interpreted as excluding the existence of additional embodiments that also include the described features. The terms "first", "second", and "third" etc. are used only as labels and are not intended to impose numerical requirements or specific positional order on their objects.

[0048] Although various embodiments of the present invention have been described, it will be apparent to those of ordinary skill in the art that many more embodiments and implementations are possible within the scope of the present invention. In particular, the skilled person will recognize the interchangeability of various features from different embodiments. Although these techniques and systems have been disclosed in the context of certain embodiments and examples, it will be understood that these techniques and systems can be extended beyond the specifically disclosed embodiments to other embodiments and / or uses and obvious modifications thereof.

Claims

1. An automatic noise control system, comprising: an acceleration sensor configured to evaluate a magnitude of an acceleration acting thereon and to generate a reference signal representative of said magnitude of said acceleration, said acceleration being representative of an unwanted noise sound generated by a noise source; a noise control filter operatively coupled to the acceleration sensor and configured to filter the reference signal through a noise control transfer function to produce an anti-noise signal; a speaker operably coupled to the noise control filter and configured to convert the anti-noise signal into anti-noise sound; a microphone configured to receive the noise sound after being transferred via a primary path from the noise source to the microphone according to a primary path transfer function and the anti-noise sound after being transferred via a secondary path from the speaker to the microphone according to a secondary path transfer function, and the microphone is further configured to convert a sum of the received noise sound and the received anti-noise sound into an error signal; a filter controller operably coupled to the noise control filter, the microphone, and the acceleration sensor and configured to control the noise control transfer function of the noise control filter based on the error signal from the microphone and a filtered or unfiltered reference signal from the acceleration sensor so that the anti-noise sound after passing via the secondary path is an anti-phase of the noise sound after passing via the primary path; a shadow noise control filter operatively coupled to the acceleration sensor and configured to filter the reference signal through a shadow noise control transfer function to produce a shadow anti-noise signal; a shadow filter controller operatively coupled to the shadow noise control filter and the acceleration sensor and configured to control the noise control transfer function of the shadow noise control filter based on a shadow error signal from the microphone and a filtered or unfiltered reference signal from the acceleration sensor; a shadow error signal generator operably coupled to the shadow noise control filter, the shadow filter controller, and the microphone and configured to generate the shadow error signal based on a filtered or unfiltered shadow anti-noise signal from the shadow noise control filter and the error signal from the microphone; as well as a coefficient copy controller operatively coupled to the shadow error signal generator, the shadow noise control filter, and the microphone, and configured to copy current coefficients of the shadow noise transfer function constituting the shadow noise control filter into the noise control filter to replace a current noise control transfer function if the shadow error signal is less than the error signal; The system further comprises: an additional noise control filter operably coupled to the acceleration sensor and configured to filter a filtered or unfiltered reference signal from the acceleration sensor by a transfer function that is the same as the noise control transfer function of the noise control filter to produce an additional anti-noise signal; and a subtractor operatively coupled to the additional noise control filter and the microphone and configured to subtract the additional anti-noise signal provided by the additional noise control filter based on the error signal provided by the microphone to produce an estimated interference signal, the estimated interference signal being an estimate of an interference sound, the interference sound being the noise sound after passing through the primary path from the noise source to the microphone; The shadow error signal generator includes an adder, which is operably coupled to the subtractor and the shadow noise control filter and is configured to generate the shadow error signal based on a filtered or unfiltered shadow anti-noise signal from the shadow noise control filter and the estimated interference signal.

2. The system of claim 1 further comprises a level-controlled coefficient storage and retrieval controller, which is operably coupled to the acceleration sensor and the shadow filter controller and is configured to store a copy of the coefficients of the shadow noise filter from the shadow filter controller and provide the stored copy of the coefficients to the shadow filter controller based on the reference signal from the acceleration sensor.

3. A system as described in claim 2, wherein the level-controlled coefficient storage and recovery controller is also configured to store a copy of the coefficients of the shadow noise filter when a first condition is detected and provide a copy of the stored coefficients to the shadow filter controller when a second condition is detected.

4. The system of any one of claims 1 to 3, further comprising a secondary path modeling filter connected between the acceleration sensor and at least one of the filter controller and the leakage controller, and configured to filter the reference signal through the secondary path transfer function before providing the reference signal to the filter controller and the leakage controller.

5. The system of any one of claims 1 to 3, further comprising an additional secondary path modeling filter connected between the shadow noise control filter and the shadow error signal generator and configured to filter the shadow anti-noise signal through the secondary path transfer function before providing the shadow anti-noise signal to the shadow error signal generator.

6. An automatic noise control method, comprising: evaluating a magnitude of an acceleration acting on an acceleration sensor and generating a reference signal representative of said magnitude of said acceleration, said acceleration representative of an unwanted noise sound generated by a noise source; filtering the reference signal through a noise control transfer function to produce an anti-noise signal; converting the anti-noise signal into anti-noise sound through a speaker; receiving, by a microphone, the noise sound after being transferred via a primary path from the noise source to the microphone according to a primary path transfer function and the anti-noise sound after being transferred via a secondary path from the speaker to the microphone according to a secondary path transfer function, and converting a sum of the received noise sound and the received anti-noise sound into an error signal by the microphone; controlling the noise control transfer function based on the error signal from the microphone and a filtered or unfiltered reference signal from the acceleration sensor so that the anti-noise sound after passing via the secondary path is the anti-phase of the noise sound after passing via the primary path; controlling a shadow noise control transfer function based on the shadow error signal and the filtered or unfiltered reference signal; generating the shadow error signal based on a filtered or unfiltered shadow anti-noise signal and the error signal; as well as If the shadow error signal is less than the error signal, replacing the noise control transfer function with the shadow noise control transfer function; The method further comprises: filtering the filtered or unfiltered reference signal from the acceleration sensor by a transfer function that is the same as the noise control transfer function of the noise control filter to produce an additional anti-noise signal; and subtracting the additional anti-noise signal provided by the additional noise control filter from the error signal provided by the microphone to produce an estimated interference signal, the estimated interference signal being an estimate of the interference sound after passing through the primary path from the noise source to the microphone; and The shadow error signal is generated based on the filtered or unfiltered shadow anti-noise signal from a shadow noise control filter and the estimated interference signal.

7. The method of claim 6, further comprising replacing the shadow noise control transfer function with the shadow noise control transfer function or replacing the shadow noise control transfer function with the shadow noise control transfer function based on the reference signal.

8. The method of claim 7, wherein: A copy of the coefficients representing the shadow noise filter is stored if a first condition is detected, and the shadow noise control transfer function is replaced with the stored copy of the shadow noise control transfer function if a second condition is detected.

9. The method of any one of claims 6 to 8, further comprising filtering the reference signal by the secondary path transfer function prior to at least one of controlling the noise control transfer function and controlling leakage.

10. The method of any one of claims 6 to 8, further comprising filtering the shadow anti-noise signal by the secondary path transfer function before generating the shadow error signal.

11. A computer program product comprising instructions which, when said program is executed by a computer, cause said computer to perform the method as claimed in claims 6 to 10.

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