Active noise cancellation system secondary path adjustment

Abstract

An active noise cancellation (ANC) system is equipped with at least one loudspeaker to project anti-noise sound into a room in response to receiving an anti-noise signal. A first controller is programmed to adjust a transfer function indicative of a secondary path between the at least one loudspeaker and at least one microphone in the room based on a resonant frequency of the at least one loudspeaker, and generate the anti-noise signal based on the adjusted transfer function.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to active noise cancellation systems, and more specifically, to adjusting secondary path parameters to limit noise enhancement and / or system instability. BACKGROUND

[0002] Active noise cancellation (ANC) systems use feedforward and / or feedback structures to attenuate unwanted noise to adaptively cancel unwanted noise within a listening environment (e.g., within a vehicle cabin). ANC systems typically cancel or reduce unwanted noise by producing a canceling sound wave to destructively interfere with the unwanted audible noise. Destructive interference occurs when the noise and the “anti-noise” (which is largely the same in amplitude but opposite in phase compared to the noise) reduce the sound pressure level (SPL) at a location. In a vehicle cabin listening environment, potential sources of unwanted noise come from the engine, the exhaust system, the interaction between the vehicle tires and the road surface on which the vehicle is traveling, and / or sound radiated by vibrations of other components of the vehicle. Thus, the unwanted noise varies with the speed of the vehicle, the road conditions, and the operating state of the vehicle.

[0003] Road noise cancellation (RNC) systems are a specific type of ANC system implemented on a vehicle in order to minimize unwanted road noise within the vehicle cabin. RNC systems use a vibration sensor to sense road-induced vibrations produced by the tires and the road interface that result in unwanted audible road noise. This unwanted road noise within the cabin is then canceled or reduced in level by producing sound waves using a speaker that are ideally the same in amplitude and opposite in phase to the noise to be reduced at the ear(s) of one or more listeners. Cancellation of this road noise makes the ride more pleasant for the vehicle occupants, and it enables vehicle manufacturers to use lightweight materials, thereby reducing energy consumption and emissions.

[0004] Engine order cancellation (EOC) systems are a specific type of ANC system implemented on a vehicle in order to minimize unwanted engine noise within the vehicle cabin. EOC systems use a non-acoustic sensor (e.g., an engine speed sensor) to generate a signal representative of the engine crankshaft speed (in revolutions per minute (RPM)) as a reference. This reference signal is used to generate sound waves that are opposite in phase to the engine noise that is audible inside the vehicle. Because EOC systems use a signal from an RPM sensor, they do not require a vibration sensor.

[0005] RNC systems are typically designed to cancel broadband signals, while EOC systems are designed and optimized to cancel narrowband signals, such as individual engine orders. ANC systems within a vehicle can provide both RNC and EOC technology. Such vehicle-based ANC systems are typically least mean square (LMS) adaptive feedforward systems that continuously adapt a W-filter based on noise inputs (e.g., acceleration inputs from vibration sensors in the RNC system) and signals from physical microphones located at various locations within the vehicle cabin. A feature of LMS-based feedforward ANC systems and corresponding algorithms (e.g., Filter-X LMS (FxLMS)) is the storage of the impulse response or secondary path between each physical microphone and each anti-noise loudspeaker in the system. The secondary path is the transfer function between the anti-noise generating loudspeaker and the physical microphone, essentially characterizing how the anti-noise signal changes from the loudspeaker, travels through the vehicle cabin to the physical microphone, and changes into the microphone output signal.

[0006] Remote or virtual microphone technology is a technology in which an ANC system estimates an error signal produced by an imaginary or remote microphone at a location where no real physical microphone is located based on error signals received from one or more real physical microphones. Such remote microphone technology can improve noise cancellation at the listener’s ear even without a physical microphone actually located there.

[0007] ANC systems employ modeled transfer characteristics that estimate 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, it can result in degraded noise cancellation performance, noise gain, or actual instability. The actual secondary paths can deviate from the stored secondary path models, which are typically measured by a trained engineer on a “golden system,” when the vehicle becomes substantially different from the reference vehicle or system in geometry, number of passengers, luggage load, etc. Other differences can include differences between speaker or microphone units, aging or failure, microphone or speaker obstruction, different speaker replacement, or wiring errors. Another source of secondary path mismatch is due to tolerances in speaker resonance frequencies resulting from typical manufacturing processes and material property variations of suspension materials, for example, up to about 15%. This range of speaker resonance frequencies results in a small safety margin for undesirable noise enhancement and divergence in EOC and RNC systems. Furthermore, the speaker resonance frequency is temperature dependent, which can cause the resonant frequency of the speaker to change over time. SUMMARY

[0008] In one embodiment, an active noise cancellation (ANC) system is equipped with at least one loudspeaker to project anti-noise sound into a room in response to receiving an anti-noise signal. A first controller is programmed to adjust a transfer function indicative of a secondary path between the at least one loudspeaker and at least one microphone in the room based on a resonant frequency of the at least one loudspeaker, and generate the anti-noise signal based on the adjusted transfer function.

[0009] In another embodiment, a method is provided for controlling stability in an active noise cancellation (ANC) system. A transfer function indicative of a secondary path between a loudspeaker and a microphone in a passenger cabin is adjusted based on a resonant frequency of the loudspeaker. An anti-noise signal to be radiated as anti-noise sound from the loudspeaker in the passenger cabin is generated based on the adjusted transfer function.

[0010] In yet another embodiment, an active noise cancellation (ANC) system is equipped with at least one loudspeaker to project anti-noise sound into a passenger cabin of a vehicle in response to receiving an anti-noise signal. A microphone provides an error signal indicative of noise and anti-noise sound in the passenger cabin. A sensor measures a voltage and a current supplied to the loudspeaker. At least one controller is programmed to: determine a resonant frequency of the loudspeaker based on the voltage and the current supplied to the loudspeaker; adjust a transfer function indicative of a secondary path between the loudspeaker and the microphone based on the resonant frequency based on the resonant frequency; and generate the anti-noise signal based on the adjusted transfer function.

[0011] Thus, the ANC system directly measures the resonant frequency of the loudspeaker in real-time and updates the stored secondary path in real-time to improve noise cancellation system performance and prevent undesirable noise enhancement and divergence in both EOC and RNC systems. BRIEF DESCRIPTION OF DRAWINGS

[0012] Figure 1 is a schematic diagram of a vehicle having an active noise cancellation (ANC) system including a road noise cancellation (RNC) and remote microphones in accordance with one or more embodiments.

[0013] Figure 2 is an example schematic diagram showing relevant portions of an RNC system scaled to include R accelerometer signals and L loudspeaker signals.

[0014] Figure 3 is an example schematic block diagram of an ANC system including an engine order cancellation (EOC) system and an RNC system.

[0015] Figure 4 is a schematic block diagram representing an ANC system including additional signal processing blocks to adjust secondary path parameters in accordance with one or more embodiments of the present disclosure.

[0016] Figure 5 is a flowchart depicting a method for adjusting secondary path parameters in an ANC system according to one or more embodiments.

[0017] Figure 6 is a plot showing the electrical impedance magnitude of a loudspeaker with resonance frequencies of 48 Hz, 60 Hz, and 72 Hz.

[0018] Figure 7 is a plot showing the frequency-dependent magnitude and phase of the current and impedance generated by Figure 4 an ANC system according to Figure 5 the method of

[0019] Figure 8 is a plot further showing the frequency-dependent phase of the anti-noise output produced from three loudspeakers with frequency-dependent impedance curves having different resonance frequencies than Figure 6

[0020] Figure 9 is a schematic block diagram representing a remote microphone ANC system according to one or more embodiments. DETAILED DESCRIPTION

[0021] Detailed embodiments of the present disclosure are disclosed herein as required by the Priorty; however, it is to be understood that the disclosed embodiments are merely exemplary of the present disclosure which can be embodied in various and alternative forms. The Figures are not necessarily to scale take some features can be exaggerated to show details which would be illusory in a more general context; therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a basis for the representative embodiments.

[0022] Referring to Figure 1 , a road noise cancellation (RNC) system according to one or more embodiments and generally designated by the reference numeral 100 is shown. The RNC system 100 is depicted as being within a vehicle 102 having one or more vibration sensors 104. The vibration sensors 104 are disposed throughout the vehicle 102 to monitor the vibrational behavior of the vehicle suspension, subframe, and other axle and chassis components. The RNC system 100 can be integrated with a broadband adaptive feed-forward active noise cancellation (ANC) system 106 that produces anti-noise by adaptively filtering signals from the vibration sensors 104 using one or more physical microphones 108. The anti-noise signal can then be played through one or more loudspeakers 110 to become sound within a room, such as the passenger cabin of the vehicle 102. S(z) represents the transfer function between a single loudspeaker 110 and a single microphone 108. The ANC system 106 evaluates the measured signals to determine the resonance frequency of each loudspeaker 110 and adaptively adjusts the secondary path parameters based on the resonance frequency to limit or cancel noise enhancement in the affected frequency range.​

[0023] While Figure 1 A single vibration sensor 104, microphone 108, and loudspeaker 110 are shown for simplicity purposes only, but it should be noted that a typical RNC system uses multiple vibration sensors 104 (e.g., ten or more), microphones 108 (e.g., four to six), and loudspeakers 110 (e.g., four to eight). According to one or more embodiments, the ANC system 106 can also include one or more remote microphones 112, 114 that are used to adapt an anti-noise signal optimized for an occupant in the vehicle 102.

[0024] The vibration sensor 104 can include, but is not limited to, an accelerometer, a load cell, a geophone, a linear variable differential transformer, a strain gauge, and a pressure cell. For example, an accelerometer is a device whose output signal magnitude is proportional to acceleration. Various accelerometers can be used in the RNC system. These accelerometers include accelerometers that are sensitive to vibrations in one, two, and three typically 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 the vibration sensor 104 to detect the magnitude and phase of acceleration and can also be used to sense orientation, motion, and vibration.

[0025] Noise and vibrations originating from the wheels 116 moving on the road surface 118 can be sensed by one or more vibration sensors 104 that are mechanically coupled to the suspension apparatus 119 or chassis components of the vehicle 102. The vibration sensor 104 can output a noise signal X(n) that is a vibration signal representative of the detected road-induced vibrations. It should be noted that multiple vibration sensors are possible and their signals can be used individually or can be combined. In certain embodiments, a microphone can be used in place of a vibration sensor to output a noise signal X(n) indicative of the noise produced by the interaction of the wheels 116 and the road surface 118. The noise signal X(n) can be filtered by a secondary path filter 120 with a modeled transfer characteristic that estimates the secondary path (i.e., the transfer function between the anti-noise loudspeaker 110 and the physical microphone 108).

[0026] ​Road noise originating from the interaction of the wheels 116 and the road surface 118 is also mechanically and / or acoustically transmitted into the passenger cabin and received by one or more microphones 108 within the vehicle 102. The one or more microphones 108 can be located, for example, in the headliner of the vehicle 102 or in some other suitable location to sense the acoustic noise field heard by an occupant within the vehicle 102, such as an occupant seated in the back row of seats 125. The road noise originating from the interaction of the road surface 118 and the wheels 116 is transmitted to the microphone 108 according to a transfer characteristic P(z) representing the primary path (i.e., the transfer function between the actual noise source and the physical microphone).

[0027] The microphone 108 can output an error signal e(n) representing the sound detected by the microphone 108 that is present in the passenger compartment of the vehicle 102, including noise and anti-noise. In the RNC system 100, the adaptive transfer characteristic W(z) of the controllable filter 126 can be controlled by an adaptive filter controller 128 that can operate according to a least mean square (LMS) algorithm based on the error signal e(n) and the noise signal X(n) filtered by the secondary path filter 120 with a modeled transfer characteristic. The controllable filter 126 is often referred to as a W filter. The anti-noise signal Y(n) can be produced by the combination of one or more controllable filters 126 and the vibration signal or vibration signal X(n). The anti-noise signal Y(n) ideally has a waveform such that when played through the loudspeaker 110, anti-noise is produced near the ears of the passengers and the microphone 108 that is substantially opposite in phase and identical in amplitude to the anti-noise of the road noise audible to the passengers of the vehicle cabin. The anti-noise from the loudspeaker 110 can combine with the road noise near the microphone 108 in the vehicle cabin, resulting in a reduction of the sound pressure level (SPL) caused by the road noise at this location. In certain embodiments, the RNC system 100 can receive a sensor signal to produce the error signal e(n) from other acoustic sensors in the passenger cabin, such as a sound energy sensor, a sound intensity sensor, or a particle acoustic velocity or acceleration sensor.

[0028] When the vehicle 102 is in operation, at least one controller 130 (hereinafter referred to as “controller 130”) can collect and process data from the vibration sensors 104 and microphones 108. The controller 130 includes a processor 132 and a storage device 134. The processor 132 collects and processes data to build a database or map containing data and / or parameters to be used by the vehicle 102. The collected data can be stored locally in the storage device 134 or in the cloud for future use by the vehicle 102. Examples of data types relevant to the RNC system 100 can be useful to store locally in the storage device 134, including but not limited to accelerometer or microphone frequency or time dependent signals, secondary path corresponding to different driver resonance frequencies, and amplitude and phase characteristics of driver resonances with different quality factors.

[0029] While the controller 130 is shown as a single controller, it can contain multiple controllers, or it can be implemented as software code within one or more other controllers (e.g., adaptive filter controller 128). The controller 130 generally includes any number of microprocessors, ASICs, ICs, memory (e.g., FLASH, ROM, RAM, EPROM, and / or EEPROM), and software code to cooperate with one another to perform a series of operations. Such hardware and / or software can be grouped together in modules to perform certain functions. Any one or more 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 technologies. Generally, a processor (e.g., processor 132) receives instructions, for example from a memory (e.g., storage device 134), computer-readable medium, etc., and executes these instructions. A processing unit is a non-transitory computer-readable storage medium capable of executing instructions of a software program. The computer-readable storage medium can be, but is not limited to, an electronic storage, a magnetic storage, an optical storage, an electromagnetic storage, a semiconductor storage, or any suitable combination thereof. According to one or more embodiments, the controller 130 also includes predetermined data or “look-up tables” stored within the memory.

[0030] As previously mentioned, a typical RNC system can use several vibration sensors, microphones, and loudspeakers to sense vibrational behavior on the structure of the vehicle and produce anti-noise. The vibration sensors can be multi-axis accelerometers with multiple output channels. For example, a three-axis accelerometer typically has separate electrical outputs for vibrations sensed in its X, Y, and Z directions. A typical configuration of an RNC system can have, for example, six error microphones, six loudspeakers, and twelve acceleration signal channels from four three-axis accelerometers or six two-axis accelerometers. Thus, the RNC system will also include multiple S'(z) filters (e.g., secondary path filters 120) and multiple W(z) filters (e.g., controllable filters 126).

[0031] Figure 1 The simplified RNC system diagram illustrates a secondary path, denoted by S(z), between loudspeaker 110 and microphone 108. As previously mentioned, RNC systems typically have multiple loudspeakers, microphones, and vibration sensors. Therefore, a six-loudspeaker, six-microphone RNC system would have a total of thirty-six secondary paths (i.e., 6×6). Correspondingly, a six-loudspeaker, six-microphone RNC system could also have thirty-six... The filters (i.e., secondary path filters 120) estimate the transfer function of each secondary path. For example... Figure 1 As shown, the RNC system will also have a W(z) filter (i.e., a controllable filter 126) between each noise signal X(n) from the vibration sensor (e.g., accelerometer) 104 and each speaker 110. Therefore, a twelve-accelerometer noise signal, six-speaker RNC system can have seventy-two W(z) filters. The relationship between the number of accelerometer signals, speakers, and W(z) filters is shown in... Figure 2 As shown in the image.

[0032] Figure 2 This is an example schematic diagram showing a relevant portion of the RNC system 200, which is scaled to include R accelerometer signals [X1(n), X2(n), ... X] from accelerometer 204. R [(n)] and L speaker signals [Y1(n), Y2(n), ... Y] from speaker 210 L (n)]. Therefore, the RNC system 200 may include R*L controllable filters (or W filters) 226 between each accelerometer signal and each speaker. As an example, an RNC system with twelve accelerometer outputs (i.e., R = 12) may employ six biaxial accelerometers or four triaxial accelerometers. Thus, in the same example, a vehicle with six speakers (i.e., L = 6) for reproducing noise immunity may use a total of seventy-two W filters. At each of the L speakers, the outputs of the R W filters are summed to generate the speaker's noise immunity signal Y(n). 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 generate an electro-reactive noise signal y(n), which is fed to an amplifier to generate an amplified noise immunity signal Y(n) sent to the speaker.

[0033] Figure 1The illustrated ANC system 106 can also include an engine order cancellation (EOC) system. As noted above, EOC techniques generally use a non-acoustic signal, such as an engine speed signal representing the engine crankshaft rotational speed, as a reference in order to generate sound that is out of phase with the engine noise audible inside the vehicle. The EOC system can utilize a narrowband feedforward ANC framework to use the engine speed signal to produce an anti-noise that directs the production of an engine order signal of the same engine order frequency to be cancelled and adaptively filters it to produce an anti-noise signal. After transmission from the anti-noise source to the listening location or physical microphone via the secondary path, the anti-noise ideally has the same amplitude but opposite phase as the combined sound generated by the engine and exhaust pipe after filtering through the primary path that extends from the engine to the listening location and from the exhaust pipe outlet to the listening location or physical or remote microphone location. Thus, at the location where the physical microphone is located in the vehicle cabin (i.e., most likely at or near the listening location), the superposition of the engine order noise and the anti-noise ideally will become zero such that the acoustic error signal received by the physical microphone will only record sound other than the engine order(s) generated by the engine and exhaust (ideally cancelled).

[0034] Generally, a non-acoustic sensor such as an engine speed sensor is used as a reference. The engine speed sensor can be a Hall effect sensor placed adjacent to a rotating steel disc, for example. Other detection principles can be employed, such as optical sensors or inductive sensors. The signal from the engine speed sensor can be used as a guide signal for generating any number of reference engine order signals corresponding to each engine order. The reference engine orders form the basis of 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 306 including an RNC system 300 and an EOC system 340. Similar to the RNC system 100, the RNC system 300 can include a vibration sensor 304, a physical microphone 308, a speaker 310, a secondary path filter 320, a w filter 326, and an adaptive filter controller 328, which are respectively consistent with the operation of the vibration sensor 104, the physical microphone 108, the speaker 110, the secondary path filter 120, the w filter 126, and the adaptive filter controller 128 described above.

[0036] The EOC system 340 can include an engine speed sensor 342 to provide an engine speed signal 344 (e.g., a square wave signal) that indicates the rotation of the engine crankshaft or other rotating shaft (e.g., drive shaft, half shaft, or other shaft whose rotational rate is consistent with vibrations that couple to vehicle components that cause noise in the passenger cabin). In some embodiments, the engine speed signal 344 can be obtained from a vehicle network bus (not shown). Since the radiated engine orders are directly proportional to the crankshaft RPM, the engine speed signal 344 represents the frequencies produced by the engine and exhaust system. Thus, the signal from the engine speed sensor 342 can be used to generate a reference engine order signal that corresponds to each engine order of the vehicle. Accordingly, the engine speed signal 344 can be used in conjunction with a look-up table 346 of engine speed (RPM) versus engine order frequencies that provides a list of the engine orders radiated at each engine speed. A frequency generator 348 can take the engine speed (RPM) as input and can generate a sinusoidal wave for each order based on this look-up table 346.

[0037] The frequency of a given engine order at the sensed engine speed (RPM) as retrieved from the look-up table 346 can be supplied to the frequency generator 348 to generate a sinusoidal wave at the given frequency. This sinusoidal wave represents a noise signal X(n) that indicates 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 the adaptive controllable filter 326 or W filter that provides a corresponding anti-noise signal Y(n) to the loudspeaker 310. As shown, the various components of this narrowband EOC system 340 can be the same as the wideband RNC system 300, including the physical microphone 308, the adaptive filter controller 328, and the secondary path filter 320. The anti-noise signal Y(n) broadcast by the loudspeaker 310 generates anti-noise that is substantially out of phase with, but the same amplitude as, the actual engine order noise at the listener's ear position, which can be in close proximity to the physical microphone 308, thereby reducing the sound amplitude of the engine order. Since the engine order noise is narrowband, the error signal e(n) can be filtered by a bandpass filter 350 before entering the LMS-based adaptive filter controller 328. In embodiments, the correct operation of the LMS adaptive filter controller 328 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 can include multiple frequency generators 348 for generating a noise signal X(n) for each engine order based on the engine speed (RPM) signal 344. As an example,Figure 3 A two-stage EOC system is shown with two such frequency generators for generating unique noise signals (e.g., X1(n), X2(n), etc.) for each engine order based on engine speed. Since the two engine orders have different frequencies, the bandpass filters 350, 352 (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 vary based on the number of engine orders to be cancelled for a particular engine of a vehicle. When the two-stage EOC system 340 is combined with the RNC system 300 to form the ANC system 306, the anti-noise signal Y(n) output from the three controllable filters 326 is summed and sent to the loudspeaker 310 as the loudspeaker signal S(n). Similarly, the error signal e(n) from the physical microphone 308 can be sent to the three LMS adaptive filter controllers 328.

[0039] If the modeled transfer characteristic stored in the ANC system representing the estimate of the secondary path Does not match the actual secondary path S(z) of the system, it can result in degraded noise cancellation performance, noise gain, or actual instability. As previously described, the secondary path is the transfer function between the anti-noise generating loudspeaker and the physical microphone. Thus, it essentially characterizes how the anti-noise signal Y(n) becomes part of the microphone output or error signal e(n) in the ANC system as it becomes sound radiating from the loudspeaker, propagates through the vehicle cabin to the physical microphone, and becomes part of the microphone output or error signal e(n) in the ANC system. The actual secondary path S(z) can deviate from the stored secondary path model S(z) when the vehicle configuration or audio system components (e.g., loudspeaker, amplifier, or microphone) become substantially different in performance, geometry, number of passengers, luggage load, etc. from the reference vehicle configuration or audio system components.

[0040] Filter-X LMS (FxLMS) ANC systems typically include a set of predetermined secondary paths from a "golden sample vehicle" or "typical vehicle" that are stored in the amplifier of every vehicle manufactured and sold. The set of secondary paths are used to filter the reference or "X" signal, hence the name Filter-X LMS. The secondary paths characterize how anti-noise is transmitted from each loudspeaker to each error microphone in the system, so an 8-loudspeaker, 8-microphone system has 64 stored secondary paths. If any of the 64 stored "golden sample" secondary paths do not match the individual secondary path of a vehicle sufficiently, then the particular vehicle can experience undesirable noise amplification and system instability. The secondary paths depend on the accurate sensitivity and frequency-dependent characteristics of each loudspeaker and microphone, as well as the acoustic resonant frequencies of the vehicle cabin excited by the loudspeakers and sensed by the microphones. While the tolerances on the performance characteristics of the microphones can be very tight (+ / - 1% on sensitivity), the tolerances on the low frequency behavior of the loudspeakers are less controlled, with + / - 15% being a typical uncertainty on the loudspeaker resonant frequency due to typical manufacturing processes (e.g., inherent variations in the quality of glue applied during loudspeaker assembly) and typical variations in the material properties of the suspension components (e.g., spider) of the loudspeaker. Furthermore, the loudspeaker resonant frequency is dependent on temperature due to the temperature-dependent stiffness of the loudspeaker suspension material. This range of loudspeaker resonant frequencies creates undesirable frequency-dependent amplitude and phase differences between the stored "golden sample" secondary paths and the actual secondary paths, which directly leads to a smaller safety margin against undesirable noise amplification and divergence in EOC and RNC systems.

[0041] Figure 4 is a schematic block diagram of a vehicle-based ANC system 406 that illustrates many of the key ANC system parameters that can be used to adapt or adjust the w filter parameters as a function of the driver resonant frequency to improve noise cancellation or limit or eliminate noise amplification in the affected frequency range. For ease of illustration, Figure 4 The ANC system 406 shown is illustrated as having the components and features of the RNC system 400 and the EOC system 440. Thus, the ANC system 406 is a schematic representation of an RNC and / or EOC system, such as those described in connection with Figures 1 to 3 The ANC system 406 is described in connection with the RNC system 400 and the EOC system 440. Thus, the ANC system 406 is a schematic representation of an RNC and / or EOC system, such as those described in connection with

[0042] For example, ANC system 406 can include an accelerometer or vibration sensor 404, a physical microphone 408, a speaker 410, a secondary path filter 420, a w filter 426, and an adaptive filter controller 428, which are consistent with the operation of vibration sensor 104, physical microphone 108, speaker 110, secondary path filter 120, w filter 126, and adaptive filter controller 128, respectively, described above, similar to ANC system 106. Figure 4 The primary path P(z), the secondary path S(z), a Fast Fourier Transform (FFT) block for converting signals to the frequency domain, and an Inverse FFT (IFFT) block for converting signals to the time domain are also shown in block form for illustrative purposes. Secondary path filter 420 includes a transfer characteristic of secondary path S(z) based on predetermined data. ANC system 406 adjusts the transfer characteristic of secondary path S(z) based on the resonant frequency of speaker 410.

[0043] ANC system 406 determines the resonant frequency (f res ) of speaker 410 in signal processing block 460. ANC system 406 includes an amplifier 462 with a controller 464 that monitors the characteristics of the electrical signal provided to speaker 410. Controller 464 can be mounted within a housing 466 of speaker 410, or outside of housing 466, or any other location. Controller 464 provides a voltage signal (V) and a current signal (I) based on the characteristics of the monitored electrical signal provided to speaker 410. In one embodiment, in addition to the real-time voltage signal, controller 464 includes a current sense resistor (not shown) for generating a real-time signal representative of the current. According to one or more embodiments, controller 464 includes a processor, a memory, and a transceiver (not shown). In one or more embodiments, controller 464 includes a digital-to-analog converter (DAC) for providing time-dependent V and I signals to signal processing block 460.

[0044] At block 468, ANC system 406 determines the electrical impedance (Z) (Z = V / I) based on the ratio of V and I. At block 470, ANC system 406 determines the resonant frequency (f res ) of speaker 410 based on the electrical impedance (Z). In one embodiment, ANC system 406 determines f res based on Z using a simple peak finding technique, where the frequency of the maximum impedance over the entire frequency band, or over a frequency band of interest (20 Hz to 200 Hz) for a mid to large woofer, represents the resonant frequency.

[0045] In another embodiment, ANC system 406 determines f resThe frequency at which the minimum current is applied to a medium to large woofer across the entire frequency band, or within the band of interest (20Hz to 200Hz), represents the resonant frequency. The ANC system 406 can average the V and I signals over time (e.g., 0.5 to approximately 2 seconds) to produce a high-quality estimate of the driver's resonant frequency, since not all frequencies in the band of interest are present at every moment. Additionally, the V and I signals include noise immunity sent to the speaker, plus any other signals such as a music signal. In other embodiments, the ANC system 406 determines f based on a signal input from a smart amplifier (not shown) external to the ANC system 406. res In other embodiments, the ANC system 406 may use the lumped element Thiele-Small loudspeaker theory to determine the resonant frequency based on signals representing loudspeaker position, velocity, acceleration, and / or enclosure pressure. In one embodiment, loudspeaker 410 is measured, and data representing the resonant frequency of loudspeaker 410 is acquired when a music playback and noise cancellation system is installed in vehicle 102, and these resonant frequencies or data are stored as predetermined data in a lookup table for later use by the ANC system 406.

[0046] At frame 472, the ANC system 406 is based on the resonant frequency of the speaker 410. fres Determine the secondary path The actual transmission characteristics. Then the ANC system 406 adjusts the secondary path parameters of the secondary path filter 420 to use the secondary path. The actual transmission characteristics replace the secondary path The estimated transfer characteristics are then determined. The adaptive filter controller 428 then controls the filter 426 adaptively based on the adjusted secondary path parameters.

[0047] Figure 5 This is a flowchart depicting a method 500 for adjusting secondary path parameters based on the resonant frequency of a loudspeaker, according to one or more embodiments of this disclosure. The various steps of the disclosed method may be performed individually by the adaptive filter controller 428 or in combination with other components of the ANC system 406 or the processor 132.

[0048] In step 502, the ANC system 406 receives voltage signals (V) and current signals (I) representing the voltage and current supplied to the speaker 410. In one or more embodiments, the controller 464 of the amplifier 462 measures the voltage and current and provides the corresponding time-dependent signals V and I to the signal processing block 460.

[0049] At step 504, the ANC system 406 determines the electrical impedance of the loudspeaker 410 based on the V signal and the I signal. At step 506, the ANC system 406 determines the resonant frequency of the loudspeaker 410 based on the electrical impedance. In other embodiments, the ANC system 406 determines the resonant frequency of the loudspeaker 410 based on the current, e.g., the frequency at which a minimum in current exists. In other embodiments, the ANC system 406 uses predetermined data from a lookup table to determine the resonant frequency of the loudspeaker 410.

[0050] At step 508, the ANC system 406 determines the actual transfer characteristics of the secondary path between the loudspeaker 410 and the physical microphone 408 based on the resonant frequency of the loudspeaker 410 fres At step 508, the ANC system 406 determines the actual transfer characteristics of the secondary path between the loudspeaker 410 and the physical microphone 408 based on the resonant frequency of the loudspeaker 410 The ANC system 406 then adjusts the secondary path parameters of the secondary path filter 420 to replace the estimated transfer characteristics of the secondary path with the actual transfer characteristics of the secondary path At step 508, the ANC system 406 determines the actual transfer characteristics of the secondary path between the loudspeaker 410 and the physical microphone 408 based on the resonant frequency of the loudspeaker 410

[0051] As described above, the secondary path characterizes the entire signal path from the voltage provided to the loudspeaker 410 through the air to the physical microphone 408 and to the electrical signal e(n) output from the microphone. The secondary path depends on the electromechanical characteristics of the loudspeaker, which in many applications are designed to meet a + / - 15% resonant frequency tolerance. This means that the secondary path measured with a conforming loudspeaker having a resonant frequency 15% below the nominal value will be different than the secondary path measured with a conforming loudspeaker having a resonant frequency 15% above the nominal value. For example, a loudspeaker having a nominal resonant frequency value of 60 Hz + / - 15% can have a resonant frequency between 51 Hz and 69 Hz, while a loudspeaker having a nominal resonant frequency value of 60 Hz + / - 20% can have a resonant frequency between 48 Hz and 72 Hz.

[0052] Figures 6 to 8 is a graph showing the resonant frequencies of three loudspeakers having resonant frequencies of 48 Hz, 60 Hz, and 72 Hz. Also shown are several methods for detecting the resonant frequency, and the amount of phase change imparted to the secondary path by implementing the method 500 when the ANC system 406 adjusts the secondary path parameters compared to existing ANC systems that do not adjust the secondary path parameters.

[0053] Figure 6is a plot 600 including three curves 602, 604, and 606 that show the magnitude of the electrical impedance of a loudspeaker that meets a 60 Hz + / - 20% resonant frequency. The first curve 602 shows the electrical impedance magnitude of a first loudspeaker that has a 48 Hz resonant frequency that is 60 Hz - 20%. The second curve 604 shows the electrical impedance magnitude of a second loudspeaker that has a 60 Hz resonant frequency. The third curve 606 shows the electrical impedance magnitude of a third loudspeaker that has a 72 Hz resonant frequency that is 60 Hz + 20%.

[0054] Figure 7 is a plot 700 including two graphs and shows three different methods of determining the resonant frequency of a loudspeaker. The upper graph includes two curves 702 and 704 that show the magnitude and phase, respectively, of the current sent to a loudspeaker with white noise as the input signal. The resonant frequency can be identified as the frequency at which the current magnitude has its minimum value, typically referenced by numeral 706, or for a mid or large woofer, the frequency at which the magnitude has its local minimum in the frequency range of interest - between 20 Hz and 200 Hz. The lower graph includes two curves 708 and 710 that show the magnitude and phase, respectively, of the electrical impedance, which is the ratio of voltage to current (Z = V / I). The resonant frequency can be found using a variety of methods. For example, the resonant frequency is the frequency at which the phase of the impedance is equal to zero degrees, as referenced by numeral 712. The resonant frequency can also be identified as the frequency at which the magnitude of the impedance has its peak value, as referenced by numeral 714. Reference numerals 706, 712, 714 show three different methods of determining that the resonant frequency of the loudspeaker is approximately 60 Hz.

[0055] Figure 8 is a plot 800 including three curves 802, 804, and 806 that show the phase of the anti-noise generated by an ANC system for a loudspeaker at resonant frequencies of 72 Hz, 60 Hz, and 48 Hz, respectively. Curves 802 and 804 show that the phase range of the sound output at 40 Hz (a typical SUV cabin resonance mode that is cancelled by the ANC system) is approximately 25 degrees. The secondary path filter The 25-degree phase shift between the stored secondary path and the actual secondary path S(z) 420 will have a large impact on the convergence of the FxLMS system in terms of how the W-filter 426 is adapted. The FxLMS system can require a longer initial adaptation time and can also have stability issues if adjustments are made at a high step size when the phase of the stored secondary path and the actual secondary path do not match. When the FxLMS system employs a W-filter, stability issues can arise due to this mismatch such that the W-filter does not converge to minimize the mean square error of the error signal, instead the W-filter diverges, which will result in noise gain, rather than noise cancellation. Specifically, if a phase deviation of more than 60 degrees occurs between the ideal W-filter and the current W-filter, not only will the noise cancellation disappear, but noise enhancement will occur. In the worst case, this noise enhancement amplitude will increase over time, resulting in a diverging and out-of-control ANC system that howls, often referred to as feedback. Once this divergence occurs, the system cannot recover and must be reset by its internal supervisory mechanisms. Thus, if the secondary path of an individual vehicle differs significantly from the stored secondary path, this type of noise enhancement and divergence occurs.

[0056] Figure 9 is a schematic block diagram of a vehicle-based remote microphone (RM) ANC system 906, which illustrates an adaptive filter controller 928 that contains many key ANC system parameters that can be used to adjust the secondary path parameters to optimize ANC system performance. For ease of illustration, Figure 9 The illustrated RM ANC system 906 is shown with components and features of the RNC system 900 and the EOC system 940. Thus, the RM ANC system 906 is a schematic representation of an RNC and / or EOC system, such as those described in connection with Figures 1 to 4 The RM ANC system 906 is shown with components and features of the RNC system 900 and the EOC system 940. Thus, the RM ANC system 906 is a schematic representation of an RNC and / or EOC system, such as those described in connection with

[0057] For example, similar to the ANC system 406, the RM ANC system 906 can include a vibration sensor 904, a physical microphone 908, a loudspeaker 910, a secondary path filter 920, a w-filter 926, an adaptive filter controller 928, and an additional signal processing block 960, which operate in accordance with the operations of the vibration sensor 404, the physical microphone 408, the loudspeaker 410, the secondary path filter 420, the w-filter 426, the adaptive filter controller 428, and the additional signaling processing block 460, respectively, described above. Figure 9 The primary path P(z) and the secondary path S(z) are also shown in block form for illustrative purposes, as with respect to Figure 4As described above. In the case of the EOC system 940, the vibration sensor 904 is replaced by the RPM sensor 342, the lookup table 346, and the frequency generator 348, as referenced above. Figure 3 As stated above.

[0058] Remote microphone 912 refers to a microphone located at a remote microphone position, which will similarly sense all sounds at its remote location, except for interference signals d to be eliminated. v Noise signals other than (n) include road noise, engine and exhaust noise, and external sounds. The pressure at the remote microphone location is estimated based on the pressure at the physical microphone location to form an estimated error signal. .

[0059] At box 948, the RM ANC system 906 measurement needs to be eliminated at the physical microphone location. Interference noise. The RM ANC system 906 detects physical error signals e p Subtract the physical microphone position from (n) The noise immunity estimate received from the physical secondary path filter 920 is used to estimate the physical microphone position. Interference noise at the location. RM ANC system 906 then By positioning the physical microphone at box 950 Estimated interference noise at the location and physical and remote microphone positions The transfer function 950 is convolved between the two to estimate the interference noise to be eliminated at the remote microphone location. At box 954, the RM ANC system 906 estimates the interference noise to be eliminated at the remote microphone location through the transfer function 950. The estimated interference noise to be eliminated is added at this location. The noise immunity estimate received from the remote secondary path filter 921 is used to estimate the remote microphone error signal that will appear at the remote microphone location. .if If the value is 1, then this remote microphone system 906 becomes a virtual microphone system, effectively bypassing the convolution of block 950.

[0060] The ANC system 906 determines the resonant frequency (f) of the loudspeaker 910 in the signal processing block 960. res The ANC system 906 includes an amplifier 962 with a controller 964 that monitors the characteristics of the electrical signals supplied to the speaker 910. The controller 964 may be mounted inside a housing 966 of the speaker 910, inside the amplifier 962, or outside both the housing 966 and the amplifier 962. The controller 964 provides a voltage signal (V) and a current signal (I) based on the electrical signals sent to the speaker 910.

[0061] At block 968, the ANC system 906 determines an electrical impedance (Z) based on the ratio of V and I (Z = V / I). At block 970, the ANC system 406 determines a resonance frequency (f res ) of the loudspeaker 910 based on the electrical impedance (Z), e.g., based on the frequency at which the phase of the impedance is equal to 0 degrees, or the frequency at which the magnitude of the impedance has its peak. In another embodiment, the ANC system 406 determines the resonance frequency based on the frequency at which the current magnitude has its minimum. In yet another embodiment, the ANC system 406 determines the resonance frequency based on signals representative of the loudspeaker position, velocity, acceleration, and / or the pressure inside the enclosure using the lumped element Thiele-Small loudspeaker theory.

[0062] At block 972, the ANC system 906 determines the actual transfer characteristics of the physical secondary path 920 fres and the remote secondary path 921 of the loudspeaker 910 based on the operating frequency (f ) of the loudspeaker 910. The ANC system 906 then adjusts the secondary path parameters of the secondary path filters 920, 921 to replace the estimated transfer characteristics of the physical secondary path and the remote secondary path with the actual transfer characteristics of the secondary path and the remote secondary path , respectively. The adaptive filter controller 928 then controls the adaptation of the w filter 926 based on the adjusted secondary path parameters. According to one or more embodiments, the secondary path filter 920 or 921 can be implemented in the time domain or in the frequency domain.

[0063] Although the ANC system is described with reference to a vehicle, the techniques described herein can be applicable to non-vehicle applications. For example, a room can have fixed seats that define the listening positions at which a reference sensor, an error sensor, a loudspeaker, and an FxLMS adaptive system are used to mute the interfering sound. Note that the interfering noise to be cancelled can be of different types, e.g., HVAC noise or noise from an adjacent room or space. Moreover, the room can have occupants whose positions vary over time and then have to rely on seat sensors or the head tracking techniques described herein to determine the position of one or more listeners so that the three-dimensional position of the remote microphone can be selected.

[0064] As noted above, there is a need to account for the offset from the "golden sample" nominal secondary path value in the production of a noise cancellation system, and there are several methods or embodiments to accomplish this. In one embodiment, the ANC system calls the secondary path for each speaker's specific resonant frequency, i.e., if the amplifier controller measures a woofer to have a resonant frequency of 70 Hz, then the secondary path using the 70 Hz woofer measurement is called from memory. There is a secondary path from each speaker 910 to each physical microphone 908 or remote microphone 912 location. Thus, in a system with multiple microphones, the ANC system will call the set of secondary paths for the 70 Hz woofer to each microphone in the system. This would require the tuning engineer to measure the secondary path with a set of speakers covering the range of resonant frequencies that are on spec, which would add memory to the algorithm. An alternative is to use a computational modeling (e.g., a simple lumped element model of the speaker in its enclosure) to calculate the magnitude and phase difference of the speaker response as a function of the speaker's resonant frequency. This set of magnitudes and phase differences (e.g., the data in Figure 6 and Figure 8 ) can then be stored in memory and used to post-process the "nominal golden" secondary path set to various and for use in the ANC system.

[0065] In another embodiment, the ANC system measures the difference between the secondary path measured with the "nominal golden" speaker measurement and with a set of other speakers having resonant frequencies that are on spec, and stores these differences for runtime calls.

[0066] In yet another embodiment, a simple lumped element model of the speaker or the speaker and its enclosure can be stored in the amplifier controller and can be used to process one stored "nominal golden" secondary path stored in the amplifier. Similarly, a nominal secondary path with the speaker model can be stored for each speaker in the system. The appropriate secondary path can then be calculated dynamically at runtime for the vehicle. This can be done without pops and clicks because the stored secondary path is only used to update the path, not to create the anti-noise in the FxLMS system, so changing the secondary path can be done without generating audible artifacts (pops or clicks). A combination of these techniques is also possible.

[0067] Although Figure 1 , Figure 3 , Figure 4 and Figure 9LMS-based adaptive filter controllers 128, 328, 428, and 928 are shown, respectively, but other methods and apparatuses can be used to adapt or create the optimal controllable W filters 126, 326, 426, and 926. For example, in one or more embodiments, a neural network can be employed in place of an LMS adaptive filter controller to create and optimize the W filter. In other embodiments, machine learning or artificial intelligence can be used in place of an LMS adaptive filter controller to create the optimal W filter.

[0068] Any one or more controllers or apparatuses described herein include computer executable instructions that can be compiled or interpreted from a computer program created using various programming languages and / or techniques. Generally, a processor, such as a microprocessor, receives instructions, for example, from memory, computer-readable media, and the like, and executes those instructions. A processing unit includes a non-transitory computer-readable storage medium capable of executing instructions of a 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.

[0069] For example, the steps recited in any method or process claim can be executed in any order and are not limited to the specific order presented in the claims. Equations can be implemented with filters to minimize the impact of signal noise. Additionally, the components and / or elements recited in any device claim can be assembled or otherwise operatively configured in various permutations and therefore are not limited to only the specific configuration recited in the claims.

[0070] Further, functionally equivalent processing steps can be performed in the time domain or the frequency domain. Thus, while each signal processing block is not explicitly illustrated in the figures, signal processing can occur in the time domain, the frequency domain, or a combination thereof. Further, while various processing steps are explained in terms of typical digital signal processing terminology, equivalent steps can be performed using analog signal processing without departing from the scope of the present disclosure.

[0071] Benefits, advantages, and solutions to problems have been described above with regard to specific embodiments. However, no element, component, or method step described herein is to be construed as being essential, required, or critical unless explicitly so described. As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items.

[0072] The terms "comprises", "comprising", "includes", "including", "has", "having" or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, composition or apparatus that comprises, includes or has a list of elements does not include only those elements but can 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 components used in the practice of the present subject matter, in addition to those not specifically described above or those described in the accompanying drawings, can be utilized in accordance with the generic principles of the present subject matter and its specific embodiment without departing from the spirit and scope of the present subject matter. Thus, other embodiments of the present subject matter are possible and are within the scope of the present subject matter.

[0073] While the example embodiments have been described above, these embodiments are not intended to describe all possible forms of the disclosure. Rather, the words used in the specification are words of description rather than limitation, and it is understood that various changes can be made without departing from the spirit and scope of the disclosure. Additionally, features of various embodiments can be combined to form further embodiments.

Claims

1. An active noise cancellation (ANC) system, comprising: at least one loudspeaker to project anti-noise sound into a room in response to receiving an anti-noise signal; a first controller programmed to: adjust a transfer function indicative of a secondary path between the at least one loudspeaker and at least one microphone in the room based on a resonant frequency of the at least one loudspeaker, and generate the anti-noise signal based on the adjusted transfer function; and a second controller in communication with the first controller and programmed to measure a characteristic of an electrical signal provided to the at least one loudspeaker; and wherein the characteristic of the electrical signal is indicative of at least one of a voltage and a current provided to the at least one loudspeaker; wherein the first controller is further programmed to determine the resonant frequency of the at least one loudspeaker based on an impedance of the at least one loudspeaker.

2. The active noise cancellation system of claim 1, wherein the first controller is further programmed to determine the resonant frequency of the at least one loudspeaker based on a frequency at which a phase of the impedance is equal to 0 degrees.

3. The active noise cancellation system of claim 2, wherein the first controller is further programmed to determine the resonant frequency of the at least one loudspeaker based on a peak of a magnitude of the impedance.

4. The active noise cancellation system of claim 1, wherein the first controller is further programmed to determine the resonant frequency of the at least one loudspeaker based on a minimum of a magnitude of a current provided to the at least one loudspeaker.

5. The active noise cancellation system of claim 1, further comprising the at least one microphone, wherein the at least one microphone is configured to provide an error signal indicative of noise in the room and the anti-noise sound.

6. The active noise cancellation system of claim 5, wherein the first controller is further programmed to: filter the error signal using the adjusted transfer function to obtain an estimated error signal; and generate the anti-noise signal based on the estimated error signal.

7. The active noise cancellation system of claim 1, wherein the first controller is further programmed to: adjust a first transfer function indicative of a first secondary path between the at least one loudspeaker and a first microphone in the room based on the resonant frequency; and adjust a second transfer function indicative of a second secondary path between the at least one loudspeaker and a remote microphone location in the room, wherein the first microphone and the remote microphone location are located at different locations in the room.

8. The active noise cancellation system of claim 7, wherein the first controller is further programmed to generate a first anti-noise signal based on a first adjusted transfer function and a second anti-noise signal based on a second adjusted transfer function.

9. The active noise cancellation system of claim 1, wherein the room comprises a passenger cabin, the active noise cancellation system further comprising: the at least one microphone, wherein the at least one microphone is configured to provide an error signal indicative of noise within the cabin and the anti-noise sound; a sensor to measure a voltage and a current provided to the loudspeaker; and wherein the first controller is further programmed to determine the resonant frequency of the loudspeaker based on the voltage and the current provided to the loudspeaker.

10. The active noise cancellation system of claim 9, wherein the at least one controller is further programmed to: determine an impedance of the loudspeaker based on the voltage and the current provided to the loudspeaker; and determine the resonant frequency of the loudspeaker based on at least one of a peak in a magnitude of the impedance of the loudspeaker and a frequency at which a phase of the impedance is equal to 0 degrees.

11. The active noise cancellation system of claim 9, wherein the at least one controller is further programmed to determine the resonant frequency of the loudspeaker based on a minimum in a magnitude of the current provided to the loudspeaker.

12. The active noise cancellation system of claim 9, wherein the at least one controller is further programmed to: adjust a first transfer function indicative of a first secondary path between the loudspeaker and a first microphone within the cabin based on the resonant frequency; and adjust a second transfer function indicative of a second secondary path between the loudspeaker and a remote microphone location within the cabin based on the resonant frequency, wherein the first microphone and the remote microphone location are at different locations within the cabin.

13. The active noise cancellation system of claim 12, wherein the at least one controller is further programmed to generate a first anti-noise signal based on the first adjusted transfer function and a second anti-noise signal based on the second adjusted transfer function.

14. A method for controlling stability in an active noise cancellation (ANC) system, the method comprising: adjusting a transfer function indicative of a secondary path between a loudspeaker and a microphone within a cabin based on a resonant frequency of the loudspeaker, wherein the resonant frequency of the loudspeaker is determined based on at least one of a peak in a magnitude of an impedance of the loudspeaker and a frequency at which a phase of the impedance is equal to 0 degrees; and generating an anti-noise signal to be radiated as an anti-noise sound from the loudspeaker within the cabin based on the adjusted transfer function.

15. The method of claim 14, further comprising determining the resonant frequency of the loudspeaker based on a minimum in a magnitude of a current provided to the loudspeaker.

16. The method of claim 14, further comprising: adjusting a first transfer function indicative of a first secondary path between the loudspeaker and a first microphone within the cabin based on the resonant frequency; and adjusting a second transfer function indicative of a second secondary path between the loudspeaker and a remote microphone location within the cabin based on the resonant frequency, wherein the first microphone and the remote microphone location are at different locations within the cabin.

17. The method of claim 16, further comprising generating a first anti-noise signal based on the first adjusted transfer function and generating a second anti-noise signal based on the second adjusted transfer function.

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