System and method for adapting to estimated secondary paths

Abstract

A noise cancellation system with secondary path adaptation, comprising: a noise cancellation filter configured to receive a reference signal representing a noise source within a predetermined volume and to generate a noise cancellation signal based at least in part on the reference signal, the noise cancellation signal, when transduced by a loudspeaker, produces a noise cancellation acoustic signal that reduces noise in a cancellation zone within the predetermined volume; a secondary path estimate filter configured to receive an input signal and to implement an estimate of a secondary path transfer function, the secondary path transfer function being a transfer function between the loudspeaker and the cancellation zone, the secondary path estimate filter outputs an output signal based at least in part on the estimate of the secondary path transfer function and the input signal; an adaptation module configured to adjust coefficients of the noise cancellation filter according to a first adaptation algorithm based at least in part on the estimated output signal; and a secondary path adaptation module configured to adjust coefficients of the secondary path estimate filter according to a second adaptation algorithm, wherein an adaptation rate of the second adaptation algorithm is based at least in part on a coherence between the reference signal and an error signal representing residual noise within the cancellation zone.

Description

[0001] Cross-reference to related applications

[0002] This application claims priority to U.S. Patent Application Serial No. 17 / 025,382, filed September 18, 2020, entitled “Systems and Methods for Adapting Estimated Secondary Path,” the entire disclosure of which is incorporated herein by reference. Background Technology

[0003] This disclosure relates in general to systems and methods for estimating the transfer function of secondary paths in adaptive systems. Summary of the Invention

[0004] All examples and features mentioned below can be combined in any technically possible way.

[0005] According to one aspect, a noise cancellation system with secondary path adaptation includes: a noise cancellation filter configured to receive a reference signal representing a noise source within a predetermined volume, and to generate a noise cancellation signal at least partially based on the reference signal, the noise cancellation signal generating a noise-canceling acoustic signal upon being converted by a loudspeaker, the noise-canceling acoustic signal reducing noise in a cancellation zone within the predetermined volume; and a secondary path estimation filter configured to receive an input signal and perform estimation of a secondary path transfer function, the secondary path transfer function being the transfer function between the loudspeaker and the cancellation zone. The secondary path estimation filter outputs an output signal based at least in part on the estimation of the secondary path transfer function and the input signal; an adaptive module configured to adjust the coefficients of the noise cancellation filter according to a first adaptive algorithm based at least in part on the estimated output signal; and a secondary path adaptive module configured to adjust the coefficients of the secondary path estimation filter according to a second adaptive algorithm, wherein the adaptation rate of the second adaptive algorithm is based at least in part on the coherence between the reference signal and an error signal representing residual noise in the cancellation region.

[0006] In one example, the input signal is the error signal, and the output signal is the estimated error, which is phase-shifted relative to the error signal to remove the delay between the speaker and the cancellation zone, wherein the delay is determined based on the estimate of the secondary path transfer function.

[0007] In one example, the input signal is the reference signal, and the output signal is the estimated reference signal, which is phase-shifted relative to the error signal to introduce a delay between the loudspeaker and the cancellation zone, the delay being estimated based on the estimation of the secondary path transfer function.

[0008] In one example, the adaptation rate is monotonically correlated with the coherence between the reference signal and the error signal.

[0009] In one example, the coherence between the reference signal and the error signal is determined by the coherence between the noise cancellation signal and the error signal, or by the coherence between the error signal and the estimate of the noise cancellation signal at the cancellation region, the estimate of the noise cancellation signal at the cancellation region being determined based on the estimate of the secondary path transfer function.

[0010] In one example, the error signal includes the output of a projection filter that receives input from an error sensor located outside the cancellation zone and configured to estimate residual noise within the cancellation zone.

[0011] In one example, both the first adaptive algorithm and the second adaptive algorithm are least mean square algorithms.

[0012] In one example, the error signal includes the output of an echo canceller that receives input from an error sensor and cancels the component of that input that is attributable to the output of the loudspeaker or at least the second loudspeaker in the predetermined volume.

[0013] In one example, the noise cancellation system further includes an echo canceller that receives a program content signal, which is converted into a program content audio signal by the loudspeaker. The echo canceller includes an echo canceller filter that implements the estimation of the secondary path transfer function such that the echo canceller filter outputs an estimated program content signal that estimates the program content audio signal at the cancellation region. The estimated program content signal is subtracted from the input received from the error sensor to eliminate components attributable to the program content audio signal at that input.

[0014] According to another aspect, a non-transitory storage medium includes program code that, when executed by a processor, performs the following steps: receiving a reference signal representing a noise source within a predetermined volume, and generating a noise cancellation signal based at least partially on the reference signal using a noise cancellation filter, the noise cancellation signal generating a noise cancellation acoustic signal when converted by a loudspeaker, the noise cancellation acoustic signal reducing noise in a cancellation zone within the predetermined volume; outputting an estimated output using a secondary path estimation filter based on an estimate of a secondary path transfer function and an input signal, the secondary path transfer function being a transfer function between the loudspeaker and the cancellation zone; adjusting the coefficients of the noise cancellation filter according to a first adaptive algorithm based at least partially on the estimated output signal; and adjusting the coefficients of the secondary path estimation filter according to a second adaptive algorithm, wherein the adaptation rate of the second adaptive algorithm is based at least partially on the coherence between the reference signal and an error signal representing residual noise in the cancellation zone.

[0015] In one example, the input signal is the error signal, and the output signal is the estimated error, which is phase-shifted relative to the error signal to remove the delay between the speaker and the cancellation zone, wherein the delay is determined based on the estimate of the secondary path transfer function.

[0016] In one example, the input signal is the reference signal, and the output signal is the estimated reference signal, which is phase-shifted relative to the error signal to introduce a delay between the loudspeaker and the cancellation zone, the delay being estimated based on the estimation of the secondary path transfer function.

[0017] In one example, the adaptation rate is monotonically correlated with the coherence between the reference signal and the error signal.

[0018] In one example, the coherence between the reference signal and the error signal is determined by the coherence between the noise cancellation signal and the error signal, or by the coherence between the error signal and the estimate of the noise cancellation signal at the cancellation region, the estimate of the noise cancellation signal at the cancellation region being determined based on the estimate of the secondary path transfer function.

[0019] In one example, the error signal includes the output of a projection filter that receives input from an error sensor located outside the cancellation zone and configured to estimate residual noise within the cancellation zone.

[0020] In one example, both the first adaptive algorithm and the second adaptive algorithm are least mean square algorithms.

[0021] According to another aspect, a noise cancellation system with secondary path adaptation includes: a noise cancellation filter configured to receive a reference signal representing a noise source within a predetermined volume, and to generate a noise cancellation signal at least partially based on the reference signal, the noise cancellation signal generating a noise cancellation acoustic signal when converted by a loudspeaker, the noise cancellation acoustic signal reducing noise in a cancellation zone within the predetermined volume; a secondary path estimation filter configured to calculate an estimate of a secondary path transfer function, the secondary path transfer function being a transfer function between the loudspeaker and the cancellation zone; and a secondary path adaptation module configured to perform a second adaptive calculation... The algorithm adjusts the coefficients of the secondary path estimation filter, wherein the adaptation rate of the second adaptive algorithm is based at least in part on the coherence between the reference signal and the error signal representing residual noise within the cancellation region; and an echo canceller that receives a program content signal, which is converted into a program content audio signal by the loudspeaker, the echo canceller including an echo canceller filter that implements the estimation of the secondary path transfer function such that the echo canceller filter outputs an estimated program content signal that estimates the program content audio signal at the cancellation region, the estimated program content signal being subtracted from the error signal to eliminate the input component attributable to the program content audio signal.

[0022] In one example, the adaptation rate is monotonically correlated with the coherence between the reference signal and the error signal.

[0023] In one example, the coherence between the reference signal and the error signal is determined by the coherence between the noise cancellation signal and the error signal, or by the coherence between the error signal and the estimate of the noise cancellation signal at the cancellation region, the estimate of the noise cancellation signal at the cancellation region being determined based on the estimate of the secondary path transfer function.

[0024] In one example, the error signal includes the output of a projection filter that receives input from an error sensor located outside the cancellation zone and configured to estimate residual noise within the cancellation zone.

[0025] Details of one or more specific embodiments are set forth in the accompanying drawings and the following description. Other features, objects, and advantages will be apparent from the specification, drawings, and claims. Attached Figure Description

[0026] In the accompanying drawings, similar reference numerals generally refer to the same parts in all different views. Furthermore, the drawings are not necessarily drawn to scale, and the focus is usually on illustrating the principles governing the various aspects.

[0027] Figure 1 A schematic diagram of a noise cancellation system implemented in a vehicle according to an example is shown.

[0028] Figure 2A A block diagram of a noise cancellation system based on an example is shown.

[0029] Figure 2B A block diagram of an adaptive secondary path estimation module based on an example is shown.

[0030] Figure 3A A block diagram of a noise cancellation system based on an example is shown.

[0031] Figure 3B A block diagram of an adaptive secondary path estimation module based on an example is shown.

[0032] Figure 4 A block diagram of a noise cancellation system with an echo canceller is shown according to an example.

[0033] Figure 5 An adaptive noise cancellation method using secondary path estimation is shown based on an example. Detailed Implementation

[0034] Adaptive noise cancellation systems that eliminate noise within a predetermined volume (e.g., inside a vehicle compartment) typically employ an estimate of the secondary path transfer function (i.e., the path from the speaker to the cancellation zone). However, the physical secondary path transfer function can change over time due to alterations in the vehicle's acoustic characteristics (e.g., speaker aging) and changes within the predetermined volume (e.g., changing seat positions, introducing a suitcase into the compartment). If the adaptive noise cancellation system does not adapt to changes in the secondary transfer function, its performance will degrade. Therefore, it is necessary to adapt the estimated secondary path transfer function over time.

[0035] Figure 1 This is a schematic diagram of an exemplary noise cancellation system 100. The noise cancellation system 100 can be configured to destructively interfere with unwanted sounds in at least one cancellation zone 102 within a predefined volume 104 (such as a vehicle compartment). In a high-level state, an example of the noise cancellation system 100 may include a reference sensor 106, an error sensor 108, a speaker 110, and a controller 112.

[0036] In one example, reference sensor 106 is configured to generate a reference signal 114 representing an unwanted sound or the source of an unwanted sound within a predefined volume 104. For example, as Figure 1As shown, the reference sensor 106 can be one or more accelerometers, which are mounted and configured to detect vibrations transmitted through the vehicle structure 116. The vibrations transmitted through the vehicle structure 116 are converted by the structure into unwanted sounds (perceived as road noise) within the vehicle compartment, and therefore the accelerometers mounted to the structure provide signals representing these unwanted sounds.

[0037] The speaker 110 may be, for example, a speaker distributed at discrete locations around the perimeter of a predefined volume. In one example, four or more speakers may be arranged inside the vehicle compartment, each of the four speakers located within a corresponding door of the vehicle and configured to project sound into the vehicle compartment. In another example, the speakers may be located within headrests or other locations within the vehicle compartment.

[0038] Noise cancellation signal 118 can be generated by controller 112 and provided to one or more loudspeakers 110 (also referred to as actuators, loudspeakers being any device configured to receive electrical signals and convert them into acoustic signals) in a predefined volume. The loudspeakers convert the noise cancellation signal 118 into acoustic energy (i.e., sound waves). Since the acoustic energy generated by the noise cancellation signal 118 is approximately 180° out of phase with the unwanted sound within the cancellation zone 102, it undergoes destructive interference with the unwanted sound. The combination of the sound waves generated from the noise cancellation signal 118 and the unwanted noise in the predefined volume results in the cancellation of the unwanted noise, which is perceived by a listener in the cancellation zone.

[0039] Since noise cancellation cannot be equal across the entire predefined volume, the noise cancellation system 100 is configured to produce maximum noise cancellation within one or more predefined cancellation zones 102 within that predefined volume. Noise cancellation within a cancellation zone can reduce unwanted sounds by approximately 3 dB or more (although different amounts of noise cancellation may occur in different examples). Furthermore, noise cancellation can eliminate sounds within a certain frequency range, such as frequencies below approximately 350 Hz (although other ranges are also possible).

[0040] An error sensor 108, positioned within a predefined volume, generates an error signal 120 based on the detection of residual noise, which is produced by a combination of sound waves generated from the noise cancellation signal 118 and unwanted sounds in the cancellation zone. The error signal 120 is provided as feedback to the controller 112, representing residual noise that was not eliminated by the noise cancellation signal. The error sensor 108 may be, for example, at least one microphone installed within the vehicle cabin (e.g., on the roof, headrest, pillar, or other location within the cabin).

[0041] It should be noted that the cancellation region can be located away from the error sensor 108. In this case, the error signal 120 can be filtered to represent an estimate of the residual noise in the cancellation region. In either case, the error signal will be interpreted as representing the residual unwanted noise in the cancellation region.

[0042] In one example, controller 112 may include non-transitory storage medium 122 and processor 124. In one example, non-transitory storage medium 122 may store program code that, when executed by processor 124, implements the various filters and algorithms described below. Controller 112 may be implemented in hardware and / or software. For example, the controller may be implemented by a SHARC floating-point DSP processor, but it should be understood that the controller may be implemented by any other processor, FPGA, ASIC, or other suitable hardware.

[0043] Go to Figure 2A A block diagram of an example noise cancellation system 100 is shown, which includes multiple filters implemented by a controller 112. As shown, the controller may define W... adapt The control system of filter 126 and adaptive processing module 128.

[0044] W adapt Filter 126 is configured to receive reference signal 114 from reference sensor 106 and generate noise cancellation signal 118. As described above, noise cancellation signal 118 is input to speaker 110, where it is converted into noise cancellation audio signal, which cancels out unwanted sounds in predefined cancellation region 102. adapt Filter 126 can be implemented as any suitable linear filter, such as a multiple-input multiple-output (MIMO) finite impulse response (FIR) filter. adapt The filter 126 employs a set of coefficients that define the noise cancellation signal 118 and can be adjusted to adapt to varying vehicle behavior in response to road inputs (or other inputs in a non-vehicle noise cancellation environment).

[0045] The adjustment of the coefficients can be performed by the adaptive processing module 128, which receives the error signal 120 (as operated by the adaptive secondary path estimation module 132, as described below) and the reference signal 114 as inputs, and uses those inputs to generate the filter update signal 130. The filter update signal 130 is based on W... adapt The filter coefficients are updated as implemented in filter 126. This is achieved by updating W. adapt The noise cancellation signal 118 generated by filter 126 will minimize the error signal 120, and thus minimize the unwanted noise in the cancellation region.

[0046] W at time step n can be updated using the following formula. adapt Coefficients of filter 126:

[0047]

[0048] in The physical transfer function T between the loudspeaker 110 and the noise cancellation zone 102 (or the secondary path) is... dc The estimate, yes The conjugate transpose of , e is the error signal 120, and x is the reference signal 114. In the update formula, the reference signal x divided by the norm of x is denoted as ‖x‖2, and μ W This is the step size (which determines the adaptation rate). In this formula, the convolution of the error signal e with... The conjugate transpose of actually causes a backoff of the time-domain delay (i.e., phase shift) caused by the secondary path, thus aligning the reference signal x (which does not similarly traverse the secondary path) and the error signal e in time. Secondary path transfer function The estimated initial value (therefore, the conjugate transpose) The value can be determined a priori from a signal received, for example, from a test microphone located inside the vehicle compartment during the tuning phase; however, as described below, the value will be adapted during operation.

[0049] In applications, the total number of filters is typically equal to the number of reference sensors (M) multiplied by the number of speakers (N). Each reference sensor signal is filtered N times, and then each speaker signal is obtained as the sum of M signals (each sensor signal is filtered by its corresponding filter).

[0050] As mentioned above, over time, the secondary path transfer function T dc The acoustic characteristics and composition of the carriages change. Therefore, it is necessary to adapt the secondary path transfer function. The estimate and therefore adapted to the conjugate transpose The estimate is used to explain the variation in the physical secondary path transfer function. This is in Figure 2A The estimation of the secondary path is completed by the adaptive secondary path estimation module 132, which adaptively calculates the estimated secondary path transfer function. In this example, the adaptive secondary path estimation module 132 receives the error signal 120 and outputs the estimated error signal. The estimated secondary path transfer function The phase shift is removed. According to formula (1), the adaptive secondary path estimation module 132 receives the error signal e and outputs... It is removed from the error signal e in the time domain. The phase shift.

[0051] Figure 3A An alternative example of the noise cancellation system 100 is shown. In this example, the noise cancellation system 100 employs a filtered x algorithm, which instead removes the noise from the error signal e by the secondary path transfer function T. dc Estimation of the resulting phase shift, secondary path transfer function T dc The phase shift estimate is added to the reference signal x as follows:

[0052]

[0053] Therefore, in this example, the adaptive secondary path estimation module 132 calculates the secondary path transfer function. And the delay (phase shift) of this function is added to the reference signal x to output the estimated reference signal. (It is actually equal to) This is to ensure that the reference signal x and the error signal e are time-aligned.

[0054] Figure 2B An exemplary secondary path propagation module 132 is illustrated. In this example, the adaptive secondary path estimation module 132 includes a secondary path estimation filter 134 and a secondary path adaptive processing module 136. The secondary path estimation filter 134 implements the estimated secondary path. The transfer function, therefore, acts on the input signal to generate a representation of the secondary path T that has been traversed. dc The output is an estimate of the input signal.

[0055] The secondary path adaptive processing module 136 adjusts the coefficients of the secondary path estimation filter 134 according to the following update formula to minimize the error signal 120:

[0056]

[0057] It can be rewritten as

[0058]

[0059] Where d is W adapt The noise cancellation signal 118 is output by filter 126.

[0060] Equations (1) and (4) are updated together to minimize the error signal e. However, in an n-variable problem, the set of correct step directions points only to the correct set of quadrants to be moved, not the exact direction determined by the step size. Figure 2A In the example, the step size μ of formula (4) TdcThe adaptive rate calculator 138 determines the following based on the coherence between the noise cancellation signal d (also called the noise cancellation signal 118) and the error signal e in the cancellation region (denoted as y):

[0061]

[0062] To perform this calculation, the adaptive rate calculator 138 receives the error signal e and the noise cancellation signal of the cancellation region y as inputs from the output of the secondary path estimation filter 134. The secondary path estimation filter 134 itself receives the noise cancellation signal d and therefore outputs the noise cancellation signal in the cancellation region y.

[0063] Generally, if the adaptive algorithms of the adaptive processing module 128 and the secondary path adaptive processing module 136 have converged, the coherence between the error signal e and the noise-cancelled signal at the cancellation region y should be zero or close to zero; however, if the adaptive algorithm has not converged, the coherence between the error signal e and the noise-cancelled signal at the cancellation region y will increase towards 1 to a certain value (which represents the total coherence between the error e and the noise-cancelled signal at the cancellation region y). In one example, the step size μ in the frequency domain... Tdc , and coherence C ye Proportional, as follows:

[0064]

[0065] Where μ0 is related to the coherence C ye With step size μ Tdc The relevant proportional constant. Equation (6) appears in the frequency domain because coherence is determined across frequencies. Therefore, this requires that the calculation of each update occurs in the frequency domain and that each frequency grid is multiplied by the frequency domain value μ before being converted back to the time domain. Tde (f).

[0066] It should be understood that the step size μ Tdc The value does not need to be related to coherence C ye It is directly proportional to the coherence C. Conversely, the value of the step size can be related to the coherence C. ye Monotonic correlation, i.e., coherence μ Tdc The step size is usually determined by whether the step size increases or decreases. Therefore, in one example, the frequency domain step size μ Tdc It can be determined using the following formula:

[0067]

[0068] Within the example frequency range of interest [40, 450 Hz], the frequency domain step size μ Tdc With coherence C ye With average coherence C at frequency ye,avgThe sum is proportional. Coherence C is proportional to... ye With average coherence C ye,avg Adding them together helps to eliminate the ringing effect that usually exists in other ways.

[0069] Because W adapt Filter 126 and physical transfer function T dc Both are linear processes. The coherence C between the noise-cancelled signal in the cancellation region y and the estimated error signal e is... ye The coherence or multicoherence between the noise cancellation signal d and the error signal e, C de The same, and the coherence or multicoherence C between the reference signal x and the error signal e. xe The same. Therefore, coherence C ye It can be regarded as calculating coherence C de and C xe One way to calculate the value of C. Generally speaking, in terms of practicality, calculating C... ye Comparison of calculation C de Or C xe This is preferable because there are typically a certain number of N reference signals x and a certain number of M noise cancellation signals d. Calculate C. de Or C xe The inverse PSD matrix needs to be computed on an order of magnitude equal to the number of inputs (i.e., the reference signal or the noise-cancelled signal). Such computations are processing-intensive and difficult to perform in real-time applications. In contrast, only a single noise-cancelled signal is computed in the cancellation region y, so the coherence C is computed much less. ye Multicoherence is not required; only the noise-cancelled signal at the cancellation region y needs to be calculated, for example, by the secondary path estimation filter 134. This requires convolution or matrix multiplication, which are computationally much faster than matrix inversion.

[0070] Step size μ Tdc The calculation assumption W adapt It has converged to its optimal solution, and is therefore practically constant. This is a reasonable assumption because the step size μ... W Typically, it is greater than the step size μ Tdc Much faster. Therefore, this can be attributed to W, which has not yet converged. adapt Any non-zero coherent value C of filter 126 ye (or C) de Or C xe ) will most likely be resolved (i.e., W) adapt Filter 126 will converge, provided that the estimated secondary path estimation filter 134 has adapted. In other words, in W... adapt Any residual coherence C after the fast convergence of filter 126 yeThis can be attributed to the incorrect estimation of the secondary path T by the estimated secondary path estimation filter 134. de And therefore can depend on adjusting the step size μ Tdc .

[0071] In the alternative example, it does not depend on coherence C. ye The step size μ can be determined by the amplitude of the error signal e. Tdc The size. For example, the adaptation rate calculator 138 can set the step size μ. Tdc It is proportional to or otherwise monotonically correlated with the amplitude of the error signal e. However, the coherence C ye It is generally preferable because it is always positive and bounded.

[0072] Once the step size μ is determined from the adaptive rate calculator 138 according to formula (4) Tdc Adjust the estimated secondary path The result is then time-flipped, yielding a time-flipped secondary path estimation filter 140. Therefore, the time-flipped secondary path estimation filter 140 will convert the secondary path transfer function... The time-flipped estimation is applied to the input error signal e. (Since the output of the time-flipped secondary path estimation filter 140 is based on the secondary path transfer function...) The time-flipped secondary path estimation filter 140 can be considered a version of the secondary path estimation filter 134. The output of the time-flipped secondary path estimation filter 140 is the estimated error signal e, in which the estimated secondary path transfer function is removed. The delay (phase shift).

[0073] Temporarily transferred to Figure 3B The process is the same, except that the reference signal x is received at the secondary path estimation filter 134, and its output is the estimated secondary transfer function added. The phase shift of the reference signal x. In this way, both the adaptive secondary path estimation modules 132 and 132' calculate the estimated secondary path transfer function and And generate an output signal (the estimated error signal) or the estimated reference signal This signal is based at least on the input signal (error signal e or reference signal x) and the secondary path transfer function. The estimate.

[0074] Go to Figure 4An example of an echo canceller 142 using a secondary path estimation filter 134 is shown. More specifically, the echo canceller 142 takes a program content signal 144 (e.g., music, navigation, etc.) converted into an acoustic signal by the speaker 110 and inputs it to the secondary path estimation filter 134 to output an estimate of the program content signal in the cancellation zone, which is then subtracted from the error signal 120 to eliminate echoes attributable to the conversion of the program content signal 144. When the secondary path estimation filter 134 is updated by the secondary path adaptive processing module 136, it will also adapt to change the physical transfer function T. dc .

[0075] same, Figures 1 to 4 The noise cancellation system 100 provided is merely an example of such a system. This system, variations thereof, and other suitable noise cancellation systems may be used within the scope of this disclosure. For example, although a minimum mean square filter (LMS / NLMS) has been described... Figure 1 Similar to the system in Figure 2, but in other examples, different types of filters can be implemented, such as filters implemented using recursive least squares (RLS) filters. Similarly, while a noise cancellation system with feedback has been described, in alternative examples such systems can employ a feedforward topology. Furthermore, although a noise cancellation system implemented for road noise cancellation using vehicles has been described, any suitable noise cancellation system with some form of secondary path adaptation can be used.

[0076] Figure 5 A flowchart of a method 500 for estimating the secondary path transfer function and adapting it accordingly to a noise cancellation system is shown. As described above, this method can be implemented by a computing device such as a controller 112. Generally, the steps of a computer-implemented method are stored in a non-transitory storage medium and executed by the processor of the computing device. However, at least some steps can be executed in hardware rather than by software.

[0077] In step 502, a noise cancellation signal is generated by the noise cancellation filter. This noise cancellation signal, when converted by the loudspeaker, produces a noise-cancelled acoustic signal that reduces noise in the cancellation zone within a predetermined volume. An example of this noise cancellation filter could be W. adapt Filter 126 is used, but other suitable adaptive filters, such as RLS filters, can be used. The signal is provided to at least one loudspeaker to generate a noise-cancelling acoustic signal within a predetermined volume.

[0078] In step 504, based on the input signal (e.g., error signal 120 or reference signal 114) and the estimation of the secondary path transfer function implemented by the secondary path estimation filter, the estimated output signal is output from the secondary path estimation filter (e.g., secondary path estimation filter 134 or time-flipped secondary path estimation filter 140). In other words, the secondary path estimation filter receives the input signal and acts on it to output the estimated output signal, which is an estimate of the input signal, wherein a phase shift is performed according to the estimated secondary path.

[0079] It should be understood that the error signal can be the output of an error sensor (e.g., a microphone positioned within the cancellation zone). Alternatively, the error signal can be the filtered output of a microphone positioned outside the cancellation zone, which estimates the error signal within the cancellation zone. Such filtered error signals are described, for example, in US 10,629,183, entitled "Systems and methods for noise-cancellation using microphone projection," the entire contents of which are incorporated herein by reference.

[0080] This error signal can also remove echoes from speakers playing program content signals (e.g., music, navigation, etc.). Echoes can be determined by inputting the program content signal into a secondary path estimation filter to determine the estimated program content representing the program content signal in the cancellation zone. This estimated program content signal can then be removed from the error signal (e.g., microphone output or filtered output).

[0081] In step 506, the coefficients of the adaptive filter are updated based on, for example, formula (1) or (2) and the estimated output signal determined in step 504. In the example of filtering error (e.g., as...) Figure 2B As shown), the estimated output signal can be an error signal with the phase shift of the estimated secondary path removed (where the secondary path estimation filter is time-flipped). Alternatively, in the filtering reference example (e.g., as shown), Figure 3B As shown, the estimated output signal can be a reference with the phase shift of the estimated secondary path added. In an alternative example, different update formulas (e.g., RLS) can be used to update the coefficients of the adaptive filter.

[0082] In step 508, the coefficients of the secondary path estimation filter are updated using, for example, Equation (4). The adaptation rate (e.g., step size) can be determined based on the coherence between the error signal and the estimated noise-cancelled signal in the cancellation region. For example, the estimate of the noise-cancelled signal in the cancellation region can be determined by inputting the noise-cancelled signal into the secondary path estimation filter. Alternatively, the adaptation rate can be determined based on the coherence between the error signal and the noise-cancelled signal, or between the error signal and a reference signal. In one example, the adaptation rate is proportional to or otherwise monotonically correlated with the coherence between the error signal and the noise-cancelled signal (or the noise-cancelled signal or the reference signal) in the cancellation region. In another example, the adaptation rate can be determined based on the amplitude of the error signal rather than on the coherence between the error signal and another signal.

[0083] Regarding the use of notation in this document, uppercase letters (e.g., H) generally denote terms, signals, or quantities in the frequency or spectral domain, and lowercase letters (e.g., h) generally denote terms, signals, or quantities in the time domain. The relationships between the time and frequency domains are generally well-known and described, at least within the fields of Fourier mathematics or analysis, and therefore will not be repeated here. Additionally, signals, transfer functions, or other terms or quantities represented by symbols in this document can be manipulated, considered, or analyzed in analog or discrete form. In the case of time-domain terms or quantities, the analog time exponent (e.g., t) and / or the discrete sample exponent (e.g., n) may be interchanged or omitted in various cases. Similarly, in the frequency domain, the analog frequency exponent (e.g., f) and the discrete frequency exponent (e.g., k) are omitted in most cases. Furthermore, as those skilled in the art will understand, the relationships and calculations disclosed herein can generally exist or be performed in the time or frequency domain as well as in the analog or discrete domain. Therefore, this document does not provide various examples to illustrate every possible variation in the time or frequency domain and in the analog or discrete domain.

[0084] The functions described herein, or parts thereof, and various modifications thereof (hereinafter referred to as "functions") may be implemented at least in part by computer program products, such as computer programs tangibly implemented in an information carrier, such as one or more non-transitory machine-readable media or storage devices, for performing or controlling the operation of one or more data processing devices, such as programmable processors, computers, multiple computers and / or programmable logic components.

[0085] Computer programs can be written in any programming language, including compiled or interpreted languages, and can be deployed in any form, including as standalone programs or as modules, components, subroutines, or other units suitable for use in a computing environment. Computer programs can be deployed on a single computer, distributed across one or more sites, or executed on multiple computers interconnected via a network.

[0086] The actions associated with implementing all or part of the functionality can be performed by one or more programmable processors executing one or more computer programs to perform the functions of the calibration process. All or part of the functionality can be implemented as special-purpose logic circuitry, such as FPGAs and / or ASICs (Application-Specific Integrated Circuits).

[0087] Processors suitable for executing computer programs include, for example, both general-purpose microprocessors and special-purpose microprocessors, as well as any one or more processors in any type of digital computer. Generally, a processor receives instructions and data from read-only memory or random access memory, or both. The components of a computer include a processor for executing instructions and one or more memory devices for storing instructions and data.

[0088] While several embodiments of the invention have been described and illustrated herein, those skilled in the art will readily conceive of a variety of other means and / or structures for performing the functions described herein and / or obtaining one or more of the results and / or advantages described herein, and each of such variations and / or modifications is considered to be within the scope of the embodiments of the invention described herein. More generally, those skilled in the art will readily understand that all parameters, dimensions, materials, and configurations described herein are intended to be exemplary, and actual parameters, dimensions, materials, and / or configurations will depend on one or more specific applications using the teachings of this invention. Those skilled in the art will recognize, or can determine, many equivalents of the specific embodiments of the invention described herein using only conventional experimentation. Therefore, it should be understood that the above embodiments are presented by way of example only, and that the embodiments of the invention may be practiced in ways other than those specifically described and claimed within the scope of the appended claims and their equivalents. The embodiments of the invention disclosed herein relate to each individual feature, system, article of manufacture, material, and / or method described herein. Furthermore, any combination of two or more such features, systems, articles of manufacture, materials, and / or methods is included within the scope of the invention disclosed herein, provided that such features, systems, articles of manufacture, materials, and / or methods do not contradict each other.

Claims

1. A noise cancellation system with secondary path adaptation, the noise cancellation system comprising: A noise cancellation filter is configured to receive a reference signal representing a noise source within a predetermined volume, and to generate a noise cancellation signal based at least in part on the reference signal, the noise cancellation signal generating a noise cancellation acoustic signal when converted by a loudspeaker, the noise cancellation acoustic signal reducing noise in a cancellation zone within the predetermined volume; A secondary path estimation filter is configured to receive an input signal and perform estimation of a secondary path transfer function, the secondary path transfer function being the transfer function between the loudspeaker and the cancellation zone. The secondary path estimation filter outputs an estimated output signal, which is an estimate of the input signal, wherein phase shifting is performed based on the estimated secondary path. An adaptive module, configured to adjust the coefficients of the noise cancellation filter according to a first adaptive algorithm, at least in part based on the estimated output signal; and A secondary path adaptive module is configured to adjust the coefficients of the secondary path estimation filter according to a second adaptive algorithm, wherein the adaptation rate of the second adaptive algorithm is monotonically correlated with the coherence between the reference signal and the error signal representing residual noise in the cancellation region.

2. The noise cancellation system of claim 1, wherein the input signal is the error signal, wherein the output signal is the estimated error, the estimated error being phase-shifted relative to the error signal to remove the delay between the loudspeaker and the cancellation zone, wherein the delay is determined based on the estimation of the secondary path transfer function.

3. The noise cancellation system of claim 1, wherein the input signal is the reference signal, wherein the output signal is an estimated reference signal, the estimated reference signal being phase-shifted relative to the error signal to introduce a delay between the loudspeaker and the cancellation zone, the delay being estimated based on the estimation of the secondary path transfer function.

4. The noise cancellation system of claim 1, wherein the coherence between the reference signal and the error signal is determined by the coherence between the noise cancellation signal and the error signal, or by the coherence between the error signal and an estimate of the noise cancellation signal at the cancellation region, the estimate of the noise cancellation signal at the cancellation region being determined based on the estimate of the secondary path transfer function.

5. The noise cancellation system of claim 1, wherein the error signal includes the output of a projection filter that receives an input from an error sensor located outside the cancellation region and configured to estimate the residual noise within the cancellation region.

6. The noise cancellation system according to claim 1, wherein both the first adaptive algorithm and the second adaptive algorithm are least mean square algorithms.

7. The noise cancellation system of claim 1, wherein the error signal includes the output of an echo canceller that receives an input from an error sensor and cancels a component of the input that can be attributed to the output of the loudspeaker or at least the second loudspeaker in the predetermined volume.

8. The noise cancellation system of claim 1, further comprising an echo canceller receiving a program content signal, the program content signal being converted into a program content sound signal by the loudspeaker, the echo canceller including an echo canceller filter implementing the estimation of the secondary path transfer function such that the echo canceller filter outputs an estimated program content signal estimating the program content signal sound signal at the cancellation region, the estimated program content signal being subtracted from the input received from the error sensor to eliminate components of the input attributable to the program content sound signal.

9. A non-transitory storage medium comprising program code, said program code performing the following steps when executed by a processor: A reference signal representing a noise source within a predetermined volume is received, and a noise cancellation signal is generated based at least in part on the reference signal using a noise cancellation filter. The noise cancellation signal generates a noise cancellation sound signal when converted by a loudspeaker, and the noise cancellation sound signal reduces the noise in the cancellation zone within the predetermined volume. The secondary path estimation filter outputs an estimated output signal based on the estimation of the secondary path transfer function and the input signal. The secondary path transfer function is the transfer function between the loudspeaker and the cancellation zone. The estimated output signal is an estimate of the input signal, and phase shifting is performed based on the estimated secondary path. The coefficients of the noise cancellation filter are adjusted according to a first adaptive algorithm, at least in part, based on the estimated output signal. as well as The coefficients of the secondary path estimation filter are adjusted according to a second adaptive algorithm, wherein the adaptation rate of the second adaptive algorithm is monotonically correlated with the coherence between the reference signal and the error signal representing the residual noise in the cancellation region.

10. The non-transient storage medium of claim 9, wherein the input signal is the error signal, wherein the output signal is the estimated error, the estimated error being phase-shifted relative to the error signal to remove the delay between the speaker and the cancellation region, wherein the delay is determined based on the estimation of the secondary path transfer function.

11. The non-transient storage medium of claim 9, wherein the input signal is the reference signal, wherein the output signal is the estimated reference signal, the estimated reference signal being phase-shifted relative to the error signal to introduce a delay between the speaker and the cancellation region, the delay being estimated based on the estimation of the secondary path transfer function.

12. The non-transient storage medium of claim 9, wherein the coherence between the reference signal and the error signal is determined by the coherence between the noise cancellation signal and the error signal, or by the coherence between the error signal and an estimate of the noise cancellation signal at the cancellation region, the estimate of the noise cancellation signal at the cancellation region being determined based on the estimate of the secondary path transfer function.

13. The non-transitory storage medium of claim 9, wherein the error signal includes the output of a projection filter that receives an input from an error sensor located outside the cancellation region and configured to estimate the residual noise within the cancellation region.

14. The non-transitory storage medium according to claim 9, wherein both the first adaptive algorithm and the second adaptive algorithm are least mean square algorithms.

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