Verification of stored secondary path accuracy for vehicle-based active noise control systems

Abstract

An active noise cancellation (ANC) system may include providing for verifying the accuracy of a modeled transfer characteristic stored in a secondary path filter, which provides an estimate of the secondary path (i.e., the transfer function between a loudspeaker and an error microphone). Using the estimated anti-noise or music signal to adjust an error signal from the error microphone, a signal analysis controller may detect ANC instability or a rise in noise. Such a rise in noise may indicate that the stored transfer characteristic in the secondary path filter does not accurately represent the actual secondary path. Therefore, upon detecting a rise in noise, the stored transfer characteristic of the secondary path filter may be modified.

Description

Technical Field

[0001] The present disclosure relates to an active noise cancellation system, and more particularly, to verifying the accuracy of a secondary path filter in a feed-forward active noise control framework to prevent noise rise and / or system instability. Background Art

[0002] Active noise control (ANC) systems use feedforward and feedback structures to attenuate unwanted noise to adaptively remove unwanted noise within a listening environment, such as a vehicle cabin. ANC systems typically cancel or reduce unwanted noise by generating cancellation sound waves to destructively interfere with the unwanted audible noise. Destructive interference occurs when noise and "anti-noise" (which is similar in amplitude but opposite in phase to the noise) reduce the sound pressure level (SPL) at a certain location. In a vehicle cabin listening environment, potential sources of unwanted noise come from the engine, the interaction between the vehicle's tires and the road surface (on which the vehicle travels), and / or sound radiated by vibrations from other parts of the vehicle. Therefore, the unwanted noise varies with the vehicle's speed, road conditions, and operating state.

[0003] A road noise cancellation (RNC) system is a specific ANC system implemented in a vehicle to minimize undesirable road noise within the vehicle cabin. RNC systems use vibration sensors to sense road-induced vibrations generated from the tire-road interface, which result in unwanted audible road noise. This unwanted road noise within the vehicle cabin is then canceled or reduced in level by using speakers to generate sound waves that are ideally opposite in phase and equal in amplitude to the noise being reduced at the ears of one or more listeners. Eliminating this road noise results in a more pleasant ride for vehicle occupants and enables automakers to use lighter materials, thereby reducing energy consumption and emissions.

[0004] An engine-order noise cancellation (EOC) system is a specific ANC system implemented on a vehicle to minimize unwanted engine noise inside the vehicle cabin. EOC systems use non-acoustic signals, such as an RPM sensor, to generate a signal representing the engine speed as a reference. This reference signal is used to generate a sound wave that is in phase with the engine noise audible inside the vehicle. Because EOC systems use signals from the RPM sensor, they do not require a vibration sensor.

[0005] RNC systems are typically designed to eliminate broadband signals, while EOC systems are designed and optimized to eliminate narrowband signals, such as individual engine orders. An in-vehicle ANC system can provide both RNC and EOC technologies. Such vehicle-based ANC systems are typically least mean square (LMS) adaptive feedforward systems that continuously adapt a W filter based on noise input (e.g., acceleration input from a vibration sensor in the RNC system) and signals from error microphones located in various locations within the vehicle cabin. A characteristic of LMS-based feedforward ANC systems and corresponding algorithms is the impulse response, or secondary path, stored between each error microphone and each anti-noise speaker in the system. The secondary path is the transfer function between the speaker generating the anti-noise and the error microphone, essentially characterizing how the reactive noise signal is transformed into sound radiated from the speaker, travels through the vehicle cabin to the error microphone, and becomes the microphone output signal.

[0006] ANC systems use estimated modeled transfer characteristics of various secondary paths to adapt the W filter. If the modeled transfer characteristics of the secondary paths stored in the ANC system differ from the actual secondary paths within the vehicle, this can lead to noise cancellation performance degradation, noise gain, or actual instability. When a vehicle significantly differs from a reference vehicle or system in terms of geometry, number of passengers, luggage loading, and so on, the actual secondary paths may deviate from the stored secondary path models, typically measured on a "golden system" by trained engineers. Other discrepancies can include variations between speaker or microphone units, aging or failure, replacement of different speakers, or wiring errors. Summary of the Invention

[0007] In one or more illustrative embodiments, a method for controlling stability in an active noise cancellation (ANC) system is provided. The method may include receiving an error signal from a microphone; and generating a speaker signal to be radiated from a speaker. The speaker signal may include at least a music signal. The method may also include filtering the music signal using a secondary path filter to obtain an estimated music signal. The secondary path filter may be defined by estimating a stored transfer characteristic of a secondary path between the speaker and the microphone. The method may also include modifying the error signal using the estimated music signal to obtain an adjusted error signal; and detecting an occurrence of a noise rise based on a comparison of the error signal with the adjusted error signal.

[0008] Implementations may include one or more of the following features. For example, modifying the error signal using the estimated music signal to obtain an adjusted error signal may include, when the error signal includes music, subtracting the estimated music signal from the error signal to obtain the adjusted error signal. Additionally, detecting the occurrence of a noise boost based on a comparison of the error signal to the adjusted error signal may include detecting the occurrence of a noise boost when an energy in the adjusted error signal exceeds an energy in the error signal. As another example, detecting the occurrence of a noise boost based on a comparison of the error signal to the adjusted error signal may include detecting the occurrence of a noise boost when an energy in the error signal does not exceed an energy in the adjusted error signal by a predetermined threshold. In certain embodiments, the speaker signal may further include an anti-noise signal. Additionally, the method may further include deactivating the speaker signal in response to detecting the occurrence of a noise boost.

[0009] The secondary path filter may also be configured to filter a noise signal from a sensor to obtain a filtered noise signal. An adaptive filter controller may be configured to control an adaptive transfer characteristic based on the filtered noise signal and the error signal. The controllable filter may be configured to generate an anti-noise signal based on the adaptive transfer characteristic and the noise signal. In this manner, the method may further include deactivating the anti-noise signal in response to detecting the occurrence of a noise rise. Optionally, the method may further include modifying the stored transfer characteristic in the secondary path filter in response to detecting the occurrence of a noise rise. Modifying the stored transfer characteristic may include replacing the stored transfer characteristic with another transfer characteristic that provides a different estimate of the secondary path between the speaker and the microphone.

[0010] One or more additional embodiments may be directed to an ANC system. The ANC system may include a first secondary path filter configured to filter a noise signal received from a sensor to obtain a filtered noise signal. The first secondary path filter may be defined by a stored transfer characteristic estimating a secondary path between a speaker and a microphone. The ANC system may also include an adaptive filter controller comprising a processor and a memory, the adaptive filter controller being programmed to control an adaptive transfer characteristic based on the filtered noise signal and an error signal received from a microphone located in a vehicle cabin. The ANC system may also include a controllable filter configured to generate an anti-noise signal based on the adaptive transfer characteristic and the noise signal. The ANC system may also include a signal analysis controller comprising a processor and a memory, the signal analysis controller being programmed to: receive an adjusted error signal based on the error signal; detect an occurrence of a noise rise based on a comparison of the adjusted error signal with one of the error signal and a simulated error signal; and modify the stored transfer characteristic in the first secondary path filter in response to detecting the occurrence of a noise rise.

[0011] Implementations may include one or more of the following features. The signal analysis controller may be programmed to detect a noise increase when the energy in the error signal exceeds the energy in the adjusted error signal or when the energy in the adjusted error signal does not exceed the energy in the error signal by a predetermined threshold. The adjusted error signal may be obtained by filtering the anti-noise signal using a second secondary path filter to obtain an estimated anti-noise signal when the error signal contains anti-noise, and then subtracting the estimated anti-noise signal from the error signal. The second secondary path filter may be a copy of the first secondary path filter.

[0012] Alternatively, the signal analysis controller may be programmed to detect a rise in noise when the energy in the adjusted error signal exceeds the energy in the error signal, or when the energy in the error signal does not exceed the energy in the adjusted error signal by a predetermined threshold. Thus, the adjusted error signal may be obtained by filtering the anti-noise signal using a second secondary path filter to obtain an estimated anti-noise signal when the error signal lacks anti-noise, and then adding the estimated anti-noise signal to the error signal. Alternatively, the adjusted error signal may be obtained by filtering the music signal using a second secondary path filter to obtain an estimated music signal when the error signal contains music, and then subtracting the estimated music signal from the error signal. Similarly, the second secondary path filter may be a copy of the first secondary path filter.

[0013] Furthermore, the simulated error signal may be obtained by filtering a simulated loudspeaker signal using a second secondary path filter, the second secondary path filter being a replica of the first secondary path filter. The simulated loudspeaker signal may include at least one of a music signal and a simulated anti-noise signal. The simulated anti-noise signal may be obtained by filtering the noise signal using a stored adaptive transfer characteristic.

[0014] One or more additional embodiments may be directed to a computer program product, embodied in a non-transitory computer-readable medium, programmed for ANC. The computer program product may include instructions for: receiving an error signal from a microphone; receiving a noise signal from a sensor; filtering the noise signal using a first secondary path filter defined by a stored transfer characteristic of a secondary path between an estimated loudspeaker and the microphone to obtain a filtered noise signal; controlling filter coefficients of a controllable filter based on the filtered noise signal and the error signal; generating an anti-noise signal to be radiated from the loudspeaker based on the noise signal and the filter coefficients; filtering a music signal using a second secondary path filter that is a copy of the first secondary path filter to obtain an estimated music signal; subtracting the estimated music signal from the error signal to obtain an adjusted error signal; and detecting an occurrence of a noise rise based on a comparison of the error signal with the adjusted error signal.

[0015] Implementations may include one or more of the following features. The computer program product may further include instructions for inhibiting radiation of the anti-noise signal by the speaker in response to detecting an occurrence of a noise rise. The computer program product may further include instructions for modifying the stored transfer characteristic in the first secondary path filter in response to detecting an occurrence of a noise rise. The computer program product may further include instructions for filtering the anti-noise signal using the second secondary path filter to obtain an estimated anti-noise signal; and subtracting the estimated anti-noise signal from the error signal to obtain the adjusted error signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is an environmental block diagram of a vehicle having an active noise control (ANC) system including road noise cancellation (RNC) according to one or more embodiments of the present disclosure;

[0017] Figure 2 is a sample schematic diagram illustrating relevant portions of an RNC system expanded to include R accelerometer signals and L speaker signals;

[0018] Figure 3 is a sample schematic block diagram of an ANC system including an engine order noise cancellation (EOC) system and an RNC system;

[0019] Figure 4 is a sample lookup table of the frequency of each engine order for a given RPM in the EOC system;

[0020] Figure 5 is a schematic block diagram illustrating an ANC system including a signal analysis controller according to one or more embodiments of the present disclosure; and

[0021] Figure 6 is a flow chart depicting a method for verifying the accuracy of a secondary path filter in an ANC system according to one or more embodiments of the present disclosure. DETAILED DESCRIPTION

[0022] As required, detailed embodiments of the present invention are disclosed herein; however, it should be understood that the disclosed embodiments are merely exemplary of the invention that may be embodied in various and alternative forms. The drawings are not necessarily drawn to scale; some features may be exaggerated or minimized to illustrate details of particular components. Therefore, the specific structural and functional details disclosed herein should not be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present invention.

[0023] Any one or more of the controllers or devices described herein include computer-executable instructions that can be compiled or interpreted from a computer program created using a variety of programming languages and / or techniques. Generally speaking, a processor (such as a microprocessor) receives instructions, for example, from a memory, a computer-readable medium, etc., and executes the instructions. The processing unit includes a non-transitory computer-readable storage medium capable of executing the instructions of the software program. The computer-readable storage medium can be, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof.

[0024] Figure 1 A road noise cancellation (RNC) system 100 is shown for a vehicle 102 having one or more vibration sensors 108. The vibration sensors are positioned throughout the vehicle 102 to monitor the vibration behavior of the vehicle's suspension, subframe, and other axle and chassis components. The RNC system 100 may be integrated with a broadband feedforward and feedback active noise control (ANC) framework or system 104 that generates anti-noise by adaptively filtering the signals from the vibration sensors 108 using one or more microphones 112. The anti-noise signal may then be played through one or more speakers 124. S(z) represents the transfer function between a single speaker 124 and a single microphone 112. While Figure 1 For simplicity, only a single vibration sensor 108, microphone 112, and speaker 124 are shown, but it should be noted that a typical RNC system uses multiple vibration sensors 108 (e.g., 10 or more), microphones 112 (e.g., 4 to 6), and speakers 124 (e.g., 4 to 8).

[0025] The vibration sensor 108 may include, but is not limited to, accelerometers, dynamometers, geophones, linear variable differential transformers, strain gauges, and force sensors. For example, an accelerometer is a device whose output signal amplitude is proportional to acceleration. A wide variety of accelerometers can be used in RNC systems. These include accelerometers that are sensitive to vibration in one, two, and three, generally orthogonal directions. These multi-axis accelerometers typically have separate electrical outputs (or channels) for vibrations sensed in their X, Y, and Z directions. Thus, single-axis and multi-axis accelerometers can be used as vibration sensors 108 to detect the magnitude and phase of acceleration, and can also be used to sense orientation, motion, and vibration.

[0026] Noise and vibration originating from wheels 106 moving on road surface 150 can be sensed by one or more vibration sensors 108 mechanically coupled to the suspension 110 or chassis components of vehicle 102. Vibration sensors 108 can output a noise signal X(n), which is a vibration signal representing the detected road-induced vibrations. It should be noted that multiple vibration sensors are possible, and their signals can be used individually or combined in various ways known to those skilled in the art. In certain embodiments, microphones can be used in place of vibration sensors to output a noise signal X(n), which is indicative of the noise generated from the interaction of wheels 106 with road surface 150. Noise signal X(n) can be filtered by secondary path filter 122 using a modeled transfer characteristic S'(z), which estimates the secondary path (i.e., the transfer function between anti-noise speaker 124 and error microphone 112).

[0027] Road noise originating from the interaction of the wheels 106 with the road surface 150 is also mechanically and / or acoustically transmitted into the passenger compartment and is received by one or more microphones 112 within the interior of the vehicle 102. The one or more microphones 112 may be located, for example, in the headrests 114 of the seats 116, such as Figure 1 As shown. Optionally, one or more microphones 112 may be located in the roof trim of the vehicle 102 or in some other suitable location to sense the acoustic noise field heard by occupants inside the vehicle 102. Road noise originating from the interaction of the road surface 150 with the wheels 106 is transferred to the microphones 112 according to a transfer characteristic P(z), which represents the primary path (i.e., the transfer function between the actual noise source and the error microphone).

[0028] Microphone 112 may output an error signal e(n) representing the noise present in the cabin of vehicle 102 as detected by microphone 112. In RNC system 100, the adaptive transfer characteristic W(z) of controllable filter 118 may be controlled by adaptive filter controller 120, which may operate according to a known least mean square (LMS) algorithm based on the error signal e(n) and the noise signal X(n) filtered by filter 122 using the modeled transfer characteristic S'(z). Controllable filter 118 is generally referred to as a W filter. An anti-noise signal Y(n) may be generated by the adaptive filter formed by controllable filter 118 and adaptive filter controller 120 based on the identified transfer characteristic W(z) and the vibration signal or combination of vibration signals X(n). Ideally, the anti-noise signal Y(n) has a waveform such that, when played through the speaker 124, anti-noise is generated near the occupant's ear and microphone 112 that is substantially opposite in phase and equal in amplitude to the road noise audible to the occupants of the vehicle cabin. The anti-noise from the speaker 124 can combine with the road noise in the vehicle cabin near the microphone 112, resulting in a reduction in the road noise-induced sound pressure level (SPL) at this location. In certain embodiments, the RNC system 100 can receive sensor signals from other acoustic sensors within the passenger cabin (such as an acoustic energy sensor, an acoustic intensity sensor, or an acoustic particle velocity or acceleration sensor) to generate the error signal e(n).

[0029] While the vehicle 102 is operating, the processor 128 can collect and optionally process data from the vibration sensors 108 and microphones 112 to construct a database or map containing data and / or parameters to be used by the vehicle 102. The collected data can be stored locally at the storage device 130 or in the cloud for future use by the vehicle 102. Examples of data types related to the RNC system 100 that can be stored locally at the storage device 130 include, but are not limited to, optimal W filters, backup secondary path filters S'(z), various noise rise thresholds, accelerometer or microphone spectra or time-correlated signals, and engine SPL versus torque and RPM. In one or more embodiments, the processor 128 and storage device 130 can be integrated with one or more RNC system controllers, such as the adaptive filter controller 120.

[0030] As previously described, a typical RNC system may use several vibration sensors, microphones, and speakers to sense the structure-borne vibration behavior of the vehicle and generate anti-noise. The vibration sensor may be a multi-axis accelerometer with multiple output channels. For example, a three-axis accelerometer typically has separate electrical outputs for vibration sensed in its X, Y, and Z directions. A typical configuration of an RNC system may have, for example, six error microphones, six speakers, and 12 acceleration signal channels from four three-axis accelerometers or six two-axis accelerometers. Therefore, the RNC system will also include multiple S'(z) filters (i.e., secondary path filter 122) and multiple W(z) filters (i.e., controllable filter 118).

[0031] Figure 1 The simplified RNC system schematically depicted in FIG shows one secondary path (denoted by S(z)) between each speaker 124 and each microphone 112. As previously mentioned, an RNC system typically has multiple speakers, microphones, and vibration sensors. Thus, a 6-speaker, 6-microphone RNC system would have a total of 36 secondary paths (i.e., 6×6). Accordingly, a 6-speaker, 6-microphone RNC system may also have 36 S'(z) filters (i.e., secondary path filters 122) that estimate the transfer function of each secondary path. As shown in FIG Figure 1 As shown, the RNC system will also have one W(z) filter (i.e., controllable filter 118) between each noise signal X(n) from the vibration sensor (i.e., accelerometer) 108 and each speaker 224. Therefore, an RNC system with 12 accelerometer signals and 6 speakers may have 72 W(z) filters. The relationship between the number of accelerometer signals, speakers, and W(z) filters is shown in Figure 2 Shown in.

[0032] Figure 2 is shown expanded to include R accelerometer signals [X1(n), X2(n), ... X R (n)] and L speaker signals [Y1(n), Y2(n), ...Y L(n)]. Thus, the RNC system 200 may include R×L controllable filters (or W filters) 218 between each of the accelerometer signals and each of the speakers. As an example, an RNC system with 12 accelerometer outputs (i.e., R=12) may employ 6 dual-axis accelerometers or 4 tri-axis accelerometers. In the same example, a vehicle with 6 speakers (i.e., L=6) for reproducing anti-noise may use a total of 72 W filters. At each of the L speakers, the outputs of the R W filters are summed to produce an anti-noise signal Y(n) for the speaker. Each of the L speakers may include an amplifier (not shown). In one or more embodiments, the R accelerometer signals filtered by the R W filters are summed to produce an anti-noise signal y(n), which is fed to an amplifier to generate an amplified anti-noise signal Y(n), which is sent to the speaker.

[0033] Figure 1 The illustrated ANC system 104 may also include an engine order cancellation (EOC) system. As mentioned above, EOC technology uses a non-acoustic signal (such as an RPM signal representing engine speed) as a reference to generate a sound that is opposite in phase to the engine noise audible inside the vehicle. Common EOC systems utilize a narrowband feed-forward ANC framework to generate anti-noise using the RPM signal to guide the generation of an engine order signal at the same frequency as the engine order to be cancelled and adaptively filter it to produce the anti-noise signal. After being transmitted from the anti-noise source to the listening position or error microphone via a secondary path, the anti-noise ideally has the same amplitude but opposite phase as the combined sound generated by the engine and exhaust pipe and filtered by the primary path, which extends from the engine to the listening position and from the exhaust pipe outlet to the listening position. Therefore, at the location in the vehicle cabin where the error microphone is located (i.e., most likely at or near the listening position), the superposition of the engine order noise and the anti-noise will ideally become zero, so that the acoustic error signal received by the error microphone will only record sounds other than one or more engine orders generated by the engine and exhaust (ideally cancelled).

[0034] Typically, a non-acoustic sensor (e.g., an RPM sensor) is used as a reference. The RPM sensor can be, for example, a Hall effect sensor placed adjacent to a rotating steel disk. Other detection principles can be employed, such as optical or inductive sensors. The signal from the RPM sensor can be used as a pilot signal for generating any number of reference engine order signals corresponding to each of the engine orders. The reference engine orders form the basis for the noise cancellation signals generated by one or more narrowband adaptive feedforward LMS blocks forming the EOC system.

[0035] Figure 3 is a schematic block diagram illustrating an example of an ANC system 304 including both an RNC system 300 and an EOC system 340. Similar to RNC system 100, RNC system 300 may include elements 308, 312, 318, 320, 322, and 324, respectively, operating in accordance with elements 108, 112, 118, 120, 122, and 124 discussed above. EOC system 340 may include an RPM sensor 342 that provides an RPM signal 344 (e.g., a square wave signal) indicating the rotation of an engine drive shaft or other rotating shaft (indicative of engine speed). In some embodiments, RPM signal 344 may be obtained from a vehicle network bus (not shown). Because radiated engine orders are proportional to drive shaft RPM, RPM signal 344 represents frequencies generated by the engine and exhaust system. Therefore, the signal from RPM sensor 342 may be used to generate a reference engine order signal corresponding to each of the vehicle's engine orders. Thus, the RPM signal 344 may be used in conjunction with a lookup table 346 of RPM versus engine order frequency, which provides a list of engine orders radiated at each engine RPM.

[0036] Figure 4 An example EOC cancellation tuning table 400 is shown that can be used to generate the lookup table 346. The example table 400 lists the frequency of each engine order for a given RPM. In the example shown, four engine orders are shown. The LMS algorithm uses RPM as input and generates a sine wave for each order based on this lookup table 400. As previously described, the RPM associated with the table 400 can be the drive shaft RPM.

[0037] Return Reference Figure 3The frequency of a given engine order at the sensed RPM, as retrieved from the lookup table 346, can be supplied to a frequency generator 348, thereby generating a sine wave at the given frequency. This sine wave represents a noise signal X(n) indicative of the engine order noise of the given engine order. Similar to the RNC system 300, this noise signal X(n) from the frequency generator 348 can be sent to an adaptively controllable filter 318, or W filter, which provides a corresponding anti-noise signal Y(n) to a speaker 324. As shown, various components of this narrowband EOC system 340 can be the same as those of the wideband RNC system 300, including the error microphone 312, the adaptive filter controller 320, and the secondary path filter 322. The anti-noise signal Y(n) broadcast by the speaker 324 generates anti-noise that is substantially out of phase but of the same magnitude as the actual engine order noise at the listener's ear (which may be very close to the error microphone 312), thereby reducing the acoustic amplitude of the engine order. Because the engine order noise is narrowband, the error microphone signal e(n) may be filtered by a bandpass filter 350 before being passed to the LMS-based adaptive filter controller 320. In one embodiment, proper operation of the LMS-based adaptive filter controller 320 is achieved when the noise signal x(n) output by the frequency generator 348 is bandpass filtered using the same bandpass filter parameters.

[0038] To reduce the amplitude of multiple engine orders simultaneously, the EOC system 340 may include multiple frequency generators 348 for generating a noise signal X(n) for each engine order based on the RPM signal 344. As an example, Figure 3 A second-order EOC system is shown, having two such frequency generators for generating unique noise signals for each engine order (e.g., X1(n), X2(n), etc.) based on engine speed. Because the frequencies of the two engine orders are different, the bandpass filters 350 (labeled BPF and BPF2) have different high-pass and low-pass filter corner frequencies. The number of frequency generators and corresponding noise cancellation components will ultimately vary based on the number of engine orders for the vehicle's particular engine. When the second-order EOC system 340 is combined with the RNC system 300 to form the ANC system 304, the anti-noise signals Y(n) output from the three controllable filters 318 are summed and sent to the speaker 324 as the speaker signal S(n). Similarly, the error signal e(n) from the error microphone 312 can be sent to the three LMS adaptive filter controllers 320.

[0039] A major factor that can lead to instability or reduced noise cancellation performance in an ANC system occurs when the modeled transfer characteristic S'(z) stored in the ANC system, representing an estimate of the secondary path, does not match the system's actual secondary path. As previously discussed, the secondary path is the transfer function between the speaker generating the anti-noise and the error microphone. Therefore, it essentially characterizes how the reactive noise signal Y(n) transforms into sound radiated from the speaker, travels through the vehicle cabin to the error microphone, and becomes part of the microphone output, or error signal, e(n), in the ANC system. According to one or more embodiments of the present disclosure, music or anti-noise played from the speaker and captured by the error microphone can be used to verify in real time that the stored estimate of the secondary path (i.e., S'(z)) is an accurate representation of the actual secondary path (i.e., S(z)).

[0040] Figure 5 5 is a schematic block diagram of a vehicle-based ANC system 500 illustrating a number of key ANC system parameters that may be used to validate stored estimates of secondary paths and optimize ANC system performance. For ease of explanation, Figure 5 The illustrated ANC system 500 is shown as having components and features of an RNC system such as RNC system 100. However, the ANC system 500 may include components such as a combination of Figure 3 Thus, the ANC system 500 is an RNC and / or EOC system (such as a combination of Figures 1 to 3 Similar components may be numbered using similar conventions. For example, similar to RNC system 100, ANC system 500 may include elements 508, 510, 512, 518, 520, 522, and 524 that operate consistent with elements 108, 110, 112, 118, 120, 122, and 124 discussed above, respectively. For illustrative purposes, Figure 5 The primary path P(z) and the secondary path S(z) are also shown in box form, as shown in FIG. Figure 1 described.

[0041] Similar to Figure 1A noise signal X(n) from a noise input (such as a vibration sensor 508) can be filtered by a secondary path filter 522 using a modeled transfer characteristic S'(z) (using a stored estimate of the secondary path as previously described) to obtain a filtered noise signal X'(n). Furthermore, the transfer characteristic W(z) of a controllable filter 518 (e.g., a W filter) can be controlled by an LMS adaptive filter controller (or simply, LMS controller) 520 to provide an adaptive filter. The noise signal filtered by the secondary path filter 522 and the error signal e(n) from the microphone 512 are inputs to the LMS adaptive filter controller 520. An anti-noise signal Y(n) can be generated by the controllable filter 518 adapted by the LMS controller 520 based on the noise signal X(n).

[0042] The speaker 524 that generates anti-noise based on the anti-noise signal Y(n) can be the same speaker used for music playback. Figure 5 The figure shows that a music signal M(n) from a music playback device 560 can be combined with an anti-noise signal Y(n) to form a speaker signal S(n) for reproduction as sound by a speaker 524. As shown, the ANC system 500 can also include a signal analysis controller 562. The signal analysis controller 562 can include a processor and memory (not shown), such as the processor 128 and the memory device 130, programmed to verify whether a stored estimate of the secondary path S'(z) matches the actual secondary path S(z) in the vehicle. This secondary path verification can be performed using an estimate of the music and / or anti-noise radiated by the speaker 524 toward the location of the microphone 512. Therefore, the ANC system can include an additional secondary path filter 564 to generate these estimates of the music or anti-noise. In particular, the anti-noise signal Y(n) can be filtered by the secondary path filter 564 to obtain an estimated anti-noise signal Y'(n), which provides an estimate of the anti-noise at the location of the microphone 512. Similarly, the music signal M(n) can be filtered by the secondary path filter 564 to obtain an estimated music signal M'(n), which provides an estimate of the music at the location of the microphone 512. The stored transfer characteristic modeled by the secondary path filter 564 can typically be the same as the stored transfer characteristic modeled in the secondary path filter 522. For example, the values of the secondary path filter 522 can be copied into the secondary path filter 564 to calculate the estimated anti-noise signal Y'(n) and / or the estimated music signal M'(n).

[0043] At block 566, the actual error signal e(n) from the microphone 512 may be modified by one or both of the estimated anti-noise signal Y'(n) and the estimated music signal M'(n) to obtain an adjusted error signal e'(n). For example, when music is present in the error signal e(n) because it is radiated by the speaker 524, the estimate of the music at the microphone 512 (i.e., the estimated music signal M'(n)) may be subtracted from the error signal e(n) to obtain the adjusted error signal e'(n). Similarly, when anti-noise is present (e.g., because the ANC system is active), the estimate of the anti-noise at the microphone 512 (i.e., the estimated anti-noise signal Y'(n)) may be subtracted from the error signal e(n) to obtain the adjusted error signal e'(n).

[0044] According to another embodiment, when the ANC system is inactive, the estimate of the secondary path can be verified by adding the estimated anti-noise signal Y'(n) to the error signal e(n) to obtain an adjusted error signal e'(n). In this case, it should be noted that with ANC turned off, the anti-noise signal Y(n) will not be delivered to the speaker 524 and introduced as actual anti-noise in the passenger compartment. For example, a switch 572 can be introduced between the controllable filter 518 and the summing block 574 to prevent the anti-noise signal Y(n) from reaching the summing block and being added to the music signal M(n) for output by the speaker 524.

[0045] The signal analysis controller 562 can then compare the error signal e(n) with the adjusted error signal e'(n) to determine whether noise rise or instability has occurred, as will be described in more detail below. The presence of noise rise, as detected by the signal analysis controller 562, can indicate that the modeled transfer characteristic S'(z) of the secondary path applied by the secondary path filter 522 is inaccurate. Once noise rise or instability is identified, the ANC system can take corrective action by, for example, disabling the ANC system 500, effectively disabling any anti-noise adaptation using the inaccurate secondary path filter 522 by blocking the associated anti-noise signal Y(n) from reaching the speaker 524, or replacing the stored transfer characteristics of the secondary path filters 522 and 564 with different modeled transfer characteristics of the secondary path between the speaker 524 and the microphone 512. Various techniques for mitigating the presence of noise rise based on secondary path verification are described in more detail below.

[0046] In another embodiment, the signal analysis controller 562 can verify the accuracy of the secondary path filter 522 using known good W filter values stored by the ANC system 500. This technique can be employed after a noise increase has been detected using anti-noise as a detection signal to determine whether the increase is due to an inaccurate controllable W filter 518 or an inaccurately modeled transfer characteristic S'(z) stored in the secondary path filter 522. In this case, in block 568, the noise signal X(n) can be convolved with the stored W filter to obtain a simulated anti-noise signal Y sim (n). At block 570, the simulated anti-noise signal Y sim (n) can optionally be combined with the music signal M(n) to obtain a simulated loudspeaker signal S sim (n). Simulated loudspeaker signal S sim (n) The stored estimate of the secondary path S'(z) may then be filtered or convolved using the secondary path filter 564 to provide an analog error signal e sim (n). The signal analysis controller 562 can then compare the error signal e(n) with the simulated error signal e sim The comparison is performed with the stored estimate of the secondary path S'(z) to provide an alternative check as to whether the stored estimate of the secondary path S'(z) is an accurate representation of the actual secondary path S(z) or whether the noise rise is simply due to a misadaptation of the controllable filter 518 (i.e., the W filter). That is, if a noise rise is still detected using the known good W filter stored in block 568, then it can be determined that a misadapted controllable filter 518 may be the cause.

[0047] Figure 6 Flowchart depicts a method 600 for verifying that a stored estimate of the secondary path S'(z) is an accurate representation of the actual secondary path between a loudspeaker and an error microphone in an ANC system. This can be accomplished by acquiring an error microphone signal e(n) indicative of all sounds at a particular location in the passenger compartment and adding or subtracting anti-noise or music from the signal to produce a second error signal (e.g., an adjusted error signal e'(n)) to compare with the actual error signal e(n). The various steps of the disclosed method can be performed by the signal analysis controller 562 alone or in conjunction with other components of the ANC system 500.

[0048] There are four potential scenarios to consider in which this secondary path verification process may be employed: (1) ANC off, music playback off; (2) ANC off, music playback on; (3) ANC on, music playback off; and (4) ANC on, music playback on. In scenarios where the error signal e(n) includes an anti-noise trace because the ANC system is active, the accuracy of the stored secondary path S'(z) can be verified by removing the anti-noise component at the microphone 512 from the error signal e(n). In these scenarios, if the stored secondary path S'(z) is indicative of the actual secondary path S(z), then subtracting (removing) the anti-noise from the error signal e(n) to produce an adjusted error signal e'(n) should result in an adjusted error signal e'(n) having a higher amplitude at one or more frequencies (e.g., frequencies contained within the estimated anti-noise signal Y'(n)) than the error signal e(n). If any frequency range has a lower signal amplitude, this is because the stored secondary path S'(z) does not represent the actual secondary path S(z) and results in increased noise.

[0049] In the event that the error signal e(n) includes a music track due to the activation of the music playback device 560, the accuracy of the stored secondary path S'(z) can be verified by removing the music component at the microphone 512 from the error signal e(n). For example, if the stored secondary path S'(z) indicates the actual secondary path S(z), then subtracting (removing) the music from the error signal e(n) to generate the adjusted error signal e'(n) should result in an adjusted error signal e'(n) having a lower amplitude at one or more frequencies (e.g., frequencies included in the estimated music signal M'(n)) than the actual error signal e(n). If any frequency range has a higher signal amplitude, this is because the stored secondary path S'(z) is inaccurate and is causing increased noise.

[0050] With ANC turned off, the error signal e(n) does not contain anti-noise. Therefore, adding the anti-noise signal (i.e., the estimated anti-noise signal Y'(n)) to the error signal e(n) to form the adjusted error signal e'(n) should also result in e'(n) having a lower signal amplitude at one or more frequencies (e.g., the frequencies included in the estimated anti-noise signal Y'(n)) than the original error signal. If any frequency range has a higher signal amplitude, it may be because the stored secondary path S'(z) does not represent the actual secondary path S(z).

[0051] When both music playback and ANC are activated, the error signal e(n) from the microphone may contain traces of either of these sounds. Therefore, the estimate of the music or anti-noise at the microphone can be removed from the error signal e(n) to obtain an adjusted error signal e'(n). The appropriate comparison process described above can then be performed depending on which sound component is removed.

[0052] Method 600 for verifying the accuracy of a stored estimate of secondary path S'(z) may begin at step 605, where signal analysis controller 562 may receive error signal e(n) from microphone 512. At step 610, the system may determine whether error signal e(n) contains music (i.e., whether music playback device 560 is activated and contributing to the sound sensed by microphone 512). If error signal e(n) contains music, the method may proceed to step 615, where the music component of error signal e(n) is removed to obtain an adjusted error signal e'(n). As previously described, this may be achieved by convolving the music with stored secondary path S'(z) (i.e., filtering music signal M(n) using secondary path filter 564) to generate an estimated music signal M'(n), which represents an estimate of the music at the location of microphone 512. The estimated music signal M'(n) may then be subtracted from error signal e(n) to obtain the adjusted error signal e'(n).

[0053] Then, at step 620, the error signal e(n) can be compared to the adjusted error signal e'(n). If the stored secondary path S'(z) sufficiently matches the vehicle's actual secondary path S(z), the energy in the newly created adjusted error signal e'(n) should be lower than the energy in the error signal e(n) from the error microphone 512. In one embodiment, the signal analysis controller 562 can calculate frequency domain representations of both the error signal e(n) and the adjusted error signal e'(n) to make this comparison. If the level of any frequency bin in the adjusted error signal e'(n) is higher than that of the error signal e(n), then the stored secondary path S'(z) and the actual secondary path S(z) are not sufficiently matched at that frequency, and any anti-noise generated at that frequency results (or may result) in noise gain rather than noise cancellation.

[0054] As part of the comparison at step 620, the signal analysis controller 562 can calculate the difference between the error signal e(n) and the adjusted error signal e'(n) by subtracting the adjusted error signal e'(n) from the error signal e(n). This can also be performed in the frequency domain by calculating the difference between the signal amplitudes in each frequency bin. The difference between the error signal e(n) and the adjusted error signal e'(n) can then be compared to a predetermined threshold, as provided at step 625. Thus, when the energy in the error signal e(n) does not exceed the energy in the adjusted error signal e'(n) by the predetermined threshold, a noise rise can be detected. In other words, when the result of subtracting the adjusted error signal e'(n) from the error signal e(n) is less than the predetermined threshold, a noise rise can be detected.

[0055] If it is determined that noise rise is occurring, one or more techniques may be employed to reduce or reverse the noise rise and / or stabilize the ANC system, as provided at step 630. These mitigation techniques are described in greater detail below. Returning to step 625, if the difference calculated at step 620 exceeds a predetermined threshold, it may be determined that the stored secondary path S'(z) sufficiently matches the actual secondary path S(z) such that the adaptive filter controller 520 will appropriately update the controllable filter 518 and noise rise will not occur in the ANC system. Therefore, the method may return to step 605 to continue verifying the accuracy of the secondary path filter.

[0056] If, at step 610, it is determined that the error signal does not contain a music playback component, or if secondary path verification using anti-noise is preferred, the method may proceed to step 635. At step 635, the signal analysis controller may determine whether the error signal e(n) contains anti-noise. For example, if ANC is not active, the error signal e(n) will not pick up any anti-noise at the microphone 512. However, if ANC is active, the signal analysis controller 562 may determine that the error signal e(n) does contain anti-noise radiated by the speaker 524. If the error signal e(n) contains anti-noise, the method may proceed to step 640, where the anti-noise component of the error signal e(n) is removed to obtain an adjusted error signal e'(n). As previously described, this may be accomplished by convolving the anti-noise signal Y(n) with the stored secondary path S'(z) (i.e., filtering the anti-noise signal Y(n) using the secondary path filter 564) to generate an estimated anti-noise signal Y'(n) that represents an estimate of the anti-noise at the location of the microphone 512. The estimated anti-noise signal Y'(n) may then be subtracted from the error signal e(n) to obtain an adjusted error signal e'(n).

[0057] Then, at step 645, the error signal e(n) can be compared to the adjusted error signal e'(n). If the stored secondary path S'(z) sufficiently matches the actual secondary path S(z) of the vehicle, then the energy in the newly created adjusted error signal e'(n) should be higher than the energy in the error signal e(n) from the error microphone 512. In one embodiment, the signal analysis controller 562 can calculate frequency domain representations of both the error signal e(n) and the adjusted error signal e'(n) to perform this comparison. If the level of any frequency bin in the adjusted error signal e'(n) is lower than that of the error signal e(n), then the stored secondary path S'(z) and the actual secondary path S(z) are not sufficiently matched at that frequency, and any anti-noise generated at that frequency results (or may result) in noise gain rather than noise cancellation.

[0058] As part of the comparison at step 645, the signal analysis controller 562 can calculate the difference between the error signal e(n) and the adjusted error signal e'(n) by subtracting the error signal e(n) from the adjusted error signal e'(n). This can also be performed in the frequency domain by calculating the difference between the signal amplitudes in each frequency bin. The difference between the error signal e(n) and the adjusted error signal e'(n) can then be compared to a predetermined threshold, as provided at step 625. In this case, noise rise can be detected when the energy in the adjusted error signal e'(n) does not exceed the energy in the error signal e(n) by the predetermined threshold. In other words, noise rise can be detected when the result of subtracting the error signal e(n) from the adjusted error signal e'(n) is less than the predetermined threshold. Similarly, if noise rise is detected, the method can proceed to step 630 to apply noise rise mitigation.

[0059] If, at step 635, the error signal e(n) does not contain anti-noise (e.g., ANC is effectively off), the method may proceed to step 650, where an estimate of the anti-noise may be added to the error signal e(n) to obtain an adjusted error signal e'(n). As previously described, this may be achieved by filtering the anti-noise signal Y(n) using the secondary path filter 564 to generate an estimated anti-noise signal Y'(n), which represents an estimate of the anti-noise at the location of the microphone 512. In this case, it should be noted that, with ANC off, the anti-noise signal Y(n) will not be delivered to the speaker 524 and will be introduced as the actual anti-noise in the passenger compartment. As previously described, a switch 572 may be introduced between the controllable filter 518 and the summing block 574 to prevent the anti-noise signal Y(n) from reaching the summing block and being added to the music signal M(n) for output by the speaker 524. The estimated anti-noise signal Y'(n) may then be added to the error signal e(n) to obtain an adjusted error signal e'(n). At step 620, the error signal e(n) can then be compared to the adjusted error signal e'(n), as previously described. That is, if the stored secondary path S'(z) adequately matches the vehicle's actual secondary path S(z), the energy in the newly created adjusted error signal e'(n) should be lower than the energy in the error signal e(n) from the error microphone 512. In one embodiment, the signal analysis controller 562 can calculate frequency domain representations of both the error signal e(n) and the adjusted error signal e'(n) to perform this comparison. If the level of any frequency bin in the adjusted error signal e'(n) is higher than that of the error signal e(n), then the stored secondary path S'(z) and the actual secondary path S(z) are not adequately matched at that frequency, and any anti-noise generated at that frequency results (or may result) in noise gain rather than noise cancellation.

[0060] Similarly, as part of the comparison at step 620, the signal analysis controller 562 can calculate the difference between the error signal e(n) and the adjusted error signal e'(n) by subtracting the adjusted error signal e'(n) from the error signal e(n). This can also be performed in the frequency domain by calculating the difference between the signal amplitudes in each frequency bin. The difference between the error signal e(n) and the adjusted error signal e'(n) can then be compared to a predetermined threshold, as provided at step 625. Thus, when the energy in the error signal e(n) does not exceed the energy in the adjusted error signal e'(n) by the predetermined threshold, a noise rise can be detected. In other words, when the result of subtracting the adjusted error signal e'(n) from the error signal e(n) is less than the predetermined threshold, a noise rise can be detected.

[0061] As previously explained, the ANC system 500 can be expanded to include multiple noise signals X(n) (both RNC and EOC), speakers 524, and error microphones 512. Furthermore, there is a secondary path S(z) between each error microphone 512 and each speaker 524. Thus, for example, a four-microphone, six-speaker ANC system would have 24 secondary path filters (4×6=24). In a multi-speaker system, each microphone 512 detects the output from each speaker 524. Thus, in the above example, the microphone's error signal e(n) can be composed of the contribution of the primary path noise P(z) plus the contributions of six different anti-noise Y(n) signals traveling to the microphone on six different secondary path S(z) paths. In one embodiment, the accuracy of the individual secondary path filters can be verified by stepping through the above steps. For example, in this example, each of the six anti-noise signals Y(n) may be individually subtracted from the error signal e(n) of the microphone 512, and the energy differencing step may be repeated for each iteration in an attempt to detect noise rise. This will identify any and all secondary path filter estimates S'(z) that result in noise rise or instability and therefore do not match the actual secondary path accurately enough.

[0062] If a noise rise is determined to be occurring, one or more techniques may be employed to reduce or reverse the noise rise and / or stabilize the ANC system, as provided at step 630. For example, the ANC system 500 may be completely disabled, effectively disabling any anti-noise adapted using the inaccurate secondary path filter 522 by preventing the associated anti-noise signal Y(n) from reaching the speaker 524. Techniques for preventing the associated anti-noise signal Y(n) from reaching the speaker 524 may include replacing the stored transfer characteristic of the secondary path filter 522 with zero, replacing the stored W(z) filter in block 568 with zero, reducing the gain of the amplifier channel associated with the speaker 524, and the like. Lowering the value of any of these filters or amplifiers by even 10 dB may be sufficient to render the anti-noise generated by the speaker 524 negligible to the soundscape at the microphone 512, thereby reducing any rise or instability to inaudible levels. Alternatively, individual secondary path filters contributing to noise rise or instability may be disabled or zeroed. In one embodiment, all secondary path filters associated with a particular speaker may be disabled. In another embodiment, the secondary path filter that contributes to elevated noise may be replaced or updated with an estimate of the secondary path S′(z) stored in the secondary path filter that does not contribute to elevated noise levels in the passenger compartment, as determined at step 625 .

[0063] As described, implementations of the above method are possible using the music signal M(n), the anti-noise signal Y(n), or a combination of both signals. When the speaker signal S(n) sent to the speaker 524 consists solely of music, the above process can subtract only the music from the error signal e(n), allowing the signal analysis controller 562 to predict the presence of a noise rise. When the speaker signal S(n) sent to the speaker 524 consists solely of anti-noise, the above process can subtract only the anti-noise from the error signal e(n), allowing the signal analysis controller 562 to detect the presence of a noise rise. Because the secondary path S(z) can be correlated with the signal amplitude S(z), multiple estimates of the secondary path S'(z) can be stored and used as a set to achieve the most accurate prediction of the presence of a noise rise. For example, the anti-noise signal Y(n) typically has a lower amplitude than the music signal M(n) because the level of typical road noise is lower than the level at which an occupant typically listens to music. In one embodiment, a set of secondary path estimates S'(z) at various levels is stored and used as a set, where lower playback amplitudes S'(z) are used in secondary path filter 522 and higher playback amplitudes S'(z) are used in secondary path filter 564 to generate the estimated music signal M'(z). If a rise is detected in step 625, a new set of stored secondary path estimates S'(z) is replaced in secondary path filters 522 and 564. It should also be noted that typical music or anti-noise does not contain energy at every frequency in every analysis frame. Therefore, in one embodiment, when comparing the error signal e(n) to the adjusted error signal e'(n), some averaging of the FFT frames may be required to provide reliable analysis of the entire noise cancellation frequency range by the signal analysis controller 562.

[0064] In one embodiment, additional thresholding can enhance the detection of noise rises because S'(z) is mismatched relative to S(z). It should be noted that when using a music signal to determine rises, the level of the music can typically be set so that it is 20 dB louder than the level of all other background noise sources (e.g., speech, road noise, engine noise) combined, thereby achieving a 20 dB signal-to-noise ratio (SNR). In this case, when the estimated music signal M'(n) is subtracted from the error signal e(n), a significant reduction (e.g., as much as 10 dB or more) in the level of the adjusted error signal e'(n) relative to the error signal e(n) can be calculated. This significant reduction is possible because the estimated music signal M'(n) is the dominant contribution to the error signal e(n) because it is 20 dB louder than the sum of all other contributions to the error signal e(n). The total reduction level can be even smaller if the music playback is set to be 20 dB quieter than the sum of all other sounds in the vehicle, thereby achieving a -20 dB SNR. In this case, subtracting the estimated music signal M'(n) from the error signal e(n) will only produce an adjusted error signal e'(n) that may be only 1 dB lower in level than the error signal e(n). In one embodiment, the relative levels of the error signal e(n), the estimated music signal M'(n), and the estimated anti-noise signal Y'(n) can be used to dynamically calculate the SNR that increases or decreases the threshold used to determine whether an elevation is detected. In one embodiment, more than one SNR threshold is stored for either or both of the estimated music signal M'(n) and the estimated anti-noise Y'(n).

[0065] although Figure 1 、 Figure 3 and Figure 5 LMS-based adaptive filter controllers 120, 320, and 520 are shown, respectively, but other methods and apparatuses for adapting or generating optimal controllable W filters 118, 318, and 518 are possible. For example, in one or more embodiments, a neural network can be used instead of an LMS adaptive filter controller to generate and optimize the W filter. In other embodiments, machine learning or artificial intelligence can be used instead of an LMS adaptive filter controller to generate the optimal W filter.

[0066] In the foregoing description, the present subject matter has been described with reference to specific exemplary embodiments. However, various modifications and changes may be made without departing from the scope of the present subject matter as set forth in the claims. The present description and drawings are illustrative rather than restrictive, and modifications are intended to be included within the scope of the present subject matter. Therefore, the scope of the present subject matter should be determined by the claims and their legal equivalents, rather than by merely the described examples.

[0067] For example, the steps recited in any method or process claim may be performed in any order and are not limited to the specific order presented in the claim. Equations may be implemented using filters to minimize the effects of signal noise. Additionally, the components and / or elements recited in any apparatus claim may be assembled or otherwise operatively configured in a variety of arrangements and are therefore not limited to the specific configuration recited in the claim.

[0068] Those skilled in the art will appreciate that functionally equivalent processing steps can be performed in the time domain or the frequency domain. Thus, while not explicitly stated for each signal processing block in the accompanying drawings, signal processing can occur in the time domain, the frequency domain, or a combination thereof. Furthermore, while various processing steps are explained in terms of typical digital signal processing, equivalent steps can be performed using analog signal processing without departing from the scope of this disclosure.

[0069] The benefits, advantages, and solutions to problems have been described above with respect to specific embodiments. However, any benefit, advantage, solution to a problem, or any element that makes any particular benefit, advantage, or solution to a problem appear or become more apparent, should not be construed as a critical, required, or essential feature or component of any or all of the claims.

[0070] The terms "comprise," "comprises," "comprising," "having," "including," "includes," or any variations thereof, are intended to refer to a non-exclusive inclusion, such that a process, method, article, composition, or apparatus that comprises a list of elements includes not only those elements that are enumerated, but may also include other elements not expressly listed or inherent to such process, method, article, composition, or apparatus. Other combinations and / or modifications of the above-described structures, arrangements, applications, proportions, elements, materials, or parts for practicing the present subject matter, in addition to those not specifically enumerated, may be varied or otherwise specially adapted to a particular environment, manufacturing specifications, design parameters, or other operating requirements without departing from the general principles of the present subject matter.

Claims

1. A method for controlling stability in an active noise cancellation (ANC) system, the method comprising: receiving an error signal from a microphone; generating a speaker signal to be radiated from a speaker, the speaker signal comprising at least a music signal; filtering the music signal using a secondary path filter defined by a stored transfer characteristic estimating a secondary path between the loudspeaker and the microphone to obtain an estimated music signal; modifying the error signal using the estimated music signal to obtain an adjusted error signal, wherein modifying the error signal using the estimated music signal to obtain the adjusted error signal comprises subtracting the estimated music signal from the error signal to obtain the adjusted error signal when the error signal includes music; as well as The occurrence of a noise rise is detected based on a comparison of the error signal and the adjusted error signal.

2. The method according to claim 1, Wherein detecting the occurrence of a noise rise based on a comparison of the error signal and the adjusted error signal comprises detecting the occurrence of a noise rise when energy in the adjusted error signal exceeds energy in the error signal.

3. The method of claim 1 , wherein modifying the error signal using the estimated music signal to obtain an adjusted error signal comprises subtracting the estimated music signal from the error signal to obtain the adjusted error signal when the error signal contains music; and Wherein detecting the occurrence of noise rise based on the comparison of the error signal and the adjusted error signal includes detecting the occurrence of noise rise when energy in the error signal does not exceed energy in the adjusted error signal by a predetermined threshold. The method of claim 1 , wherein the speaker signal further comprises an anti-noise signal.

5. The method of claim 1, further comprising: The speaker signal is deactivated in response to detecting an occurrence of elevated noise.

6. The method of claim 1 , wherein the secondary path filter is further configured to filter a noise signal from a sensor to obtain a filtered noise signal, wherein an adaptive filter controller is configured to control an adaptive transfer characteristic based on the filtered noise signal and the error signal, and wherein the controllable filter is configured to generate an anti-noise signal based on the adaptive transfer characteristic and the noise signal, the method further comprising: The anti-noise signal is deactivated in response to detecting an occurrence of a noise increase.

7. The method of claim 1 , wherein the secondary path filter is further configured to filter a noise signal from a sensor to obtain a filtered noise signal, the method further comprising: The stored transfer characteristic in the secondary path filter is modified in response to detecting an occurrence of a noise rise.

8. The method of claim 7, wherein modifying the stored transfer characteristic comprises replacing the stored transfer characteristic with another transfer characteristic that provides a different estimate of the secondary path between the loudspeaker and the microphone.

9. An active noise cancellation (ANC) system, comprising: a first secondary path filter configured to filter a noise signal received from the sensor to obtain a filtered noise signal, the first secondary path filter being defined by a stored transfer characteristic of a secondary path between the estimated speaker and the microphone; an adaptive filter controller comprising a processor and a memory, the adaptive filter controller being programmed to control an adaptive transfer characteristic based on the filtered noise signal and an error signal received from a microphone located in a cabin of the vehicle; a controllable filter configured to generate an anti-noise signal based on the adaptive transfer characteristic and the noise signal; A signal analysis controller, comprising a processor and a memory, wherein the signal analysis controller is programmed to: receiving an adjusted error signal based on the error signal; detecting an occurrence of a noise rise based on a comparison of the adjusted error signal with one of the error signal and a simulated error signal; as well as modifying the stored transfer characteristic in the first secondary path filter in response to detecting an occurrence of a noise increase; The adjusted error signal is obtained by filtering the anti-noise signal using a second secondary path filter when the error signal includes anti-noise to obtain an estimated anti-noise signal and then subtracting the estimated anti-noise signal from the error signal.

10. The ANC system of claim 9, wherein the signal analysis controller is programmed to detect a rise in noise when the energy in the error signal exceeds the energy in the adjusted error signal or when the energy in the adjusted error signal does not exceed the energy in the error signal by a predetermined threshold.

11. The ANC system of claim 10, wherein the second secondary path filter is a copy of the first secondary path filter.

12. The ANC system of claim 9, wherein the signal analysis controller is programmed to detect a rise in noise when the energy in the adjusted error signal exceeds the energy in the error signal or when the energy in the error signal does not exceed the energy in the adjusted error signal by a predetermined threshold.

13. The ANC system of claim 12 , wherein the adjusted error signal is obtained by filtering the anti-noise signal using a second secondary path filter to obtain an estimated anti-noise signal when the error signal lacks anti-noise, and then adding the estimated anti-noise signal to the error signal, the second secondary path filter being a copy of the first secondary path filter.

14. The ANC system of claim 12 , wherein the adjusted error signal is obtained by filtering a music signal using a second secondary path filter to obtain an estimated music signal when the error signal contains music, and then subtracting the estimated music signal from the error signal, the second secondary path filter being a copy of the first secondary path filter.

15. The ANC system of claim 9, wherein the simulated error signal is obtained by filtering a simulated loudspeaker signal using a second secondary path filter, the second secondary path filter being a replica of the first secondary path filter.

16. The ANC system of claim 15, wherein the simulated loudspeaker signal comprises at least one of a music signal and a simulated anti-noise signal obtained by filtering the noise signal using a stored adaptive transfer characteristic.

17. A computer program product embodied in a non-transitory computer readable medium, the computer program product being programmed for active noise cancellation (ANC), the computer program product comprising instructions for: receiving an error signal from a microphone; receiving a noise signal from a sensor; filtering the noise signal using a first secondary path filter defined by a stored transfer characteristic of a secondary path between an estimated loudspeaker and the microphone to obtain a filtered noise signal; controlling filter coefficients of a controllable filter based on the filtered noise signal and the error signal; generating an anti-noise signal to be radiated from the speaker based on the noise signal and the filter coefficients; filtering the music signal using a second secondary path filter to obtain an estimated music signal, the second secondary path filter being a copy of the first secondary path filter; subtracting the estimated music signal from the error signal to obtain an adjusted error signal when the error signal includes anti-noise; as well as The occurrence of a noise rise is detected based on a comparison of the error signal and the adjusted error signal.

18. The computer program product of claim 17, further comprising instructions for: Radiating the anti-noise signal by the speaker is disabled in response to detecting an occurrence of a noise increase.

19. The computer program product of claim 17, further comprising instructions for: The stored transfer characteristic in the first secondary path filter is modified in response to detecting an occurrence of a noise rise.

20. The computer program product of claim 17, further comprising instructions for: filtering the anti-noise signal using the second secondary path filter to obtain an estimated anti-noise signal; and The estimated anti-noise signal is subtracted from the error signal to obtain the adjusted error signal.

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