Patent Application
20240029701
The present application is based upon and claims the benefit of priority from DE 10 2022 118 015.8 filed on Jul. 19, 2022, the entire contents of which is incorporated herein by reference.
The present disclosure relates to a noise reduction system and more particularly to a noise reduction system for actively compensating background noise generated by a noise source in a noise reduction area in a passenger transport area of a vehicle The present disclosure also relates to the use of the system.
Furthermore, the present disclosure relates to a method of operating a noise reduction system for actively compensating background noise generated by a noise source in a noise reduction area in a passenger transport area of a vehicle.
Noise reduction systems are known in various configurations. Noise reduction systems are also referred to as noise suppression systems, background noise suppression systems, background noise reduction systems and noise-canceling systems. A distinction is made between active and passive systems. In case of a passive system, sound-absorption materials are applied in order to reduce the undesired background noise in for example a passenger area of a vehicle. In active noise reduction systems, which are also referred to as active noise-canceling systems or active noise control systems (often abbreviated as “ANC”), active noise compensation by means of anti-noise (also referred to as “counter noise”) is applied. The anti-noise is superimposed on the undesired background noise in that the background noise is reduced or almost completely eliminated in a quiet zone by means of destructive interference.
In the context of this disclosure, only active noise reduction systems are explained, even if these are not explicitly referred to as active noise reduction systems but rather merely as noise reduction systems.
In noise reduction systems, efficient suppression of the background noise can only be achieved within a small spatial region. This spatial region is typically referred to as a quiet zone and lies inside a noise reduction area of the system. In the quiet zone, the anti-noise is superimposed on the background noise in more or less exact phase opposition. Therefore, efficient suppression of the background noise occurs. This spatial limitation leads to the effect that active noise reduction systems are rather sensitive to movements of the head of a user. When the entrance of the auditory channel at the ear of the user is no longer located in the quiet zone, efficient background noise reduction cannot be guaranteed and the noise reduction system loses effectiveness.
This is why a relocation or readjustment of the noise reduction area is performed in many cases. Generally, noise reduction systems are driven by minimizing an error signal, which indicates the residual noise not canceled by the noise reduction system. To provide efficient noise-canceling, the residual noise near or at the auditory channel of the ear of the user should be minimized. To estimate said noise at a position in which no physical microphone can be placed or is not desired to be placed, the concept of “virtual microphones” has been established. This concept is basically described for example in U.S. Pat. No. 5,381,485.
When referring back to the movement of the user's head, the adaption of the noise reduction system to said movement is performed by relocating a position of the virtual microphone, which is configured to pick up the sum of the background noise and the anti-noise.
In many cases, a microphone array is applied for picking up a signal used for subsequent estimation of the signal at the position of the virtual microphone. There are various approaches applying different filters that are used to estimate a residual signal representing the sum of the background noise and the anti-noise at a position of the virtual microphone.
Furthermore, an active noise reduction system comprises a microphone for detecting the background noise of a noise source, the noise of which should be eliminated in the noise reduction area. This microphone is often referred to as a reference microphone. An anti-noise filter driving a sound generator that emits the anti-noise uses the signal of the reference microphone. The output of the anti-noise filter is not only used for driving the sound generator but is also input to a further filter. This is configured to estimate a muting signal representing the anti-noise at the position of the before mentioned virtual microphone. By subtracting the estimated muting signal from the estimated signal, which is the background noise and the anti-noise, an error signal can be derived. This error signal represents a cost function of the noise reduction system. By minimizing the value of the error function, the noise-canceling system is dynamically adapted to the noise generated by the noise source and by that, efficient noise reduction at the position of the virtual microphone can be achieved.
The position of the virtual microphone does however not match in all situations with the location of the auditory channel of the user's ear. In an attempt to provide a flexible and dynamic noise reduction in a noise reduction area, a plurality of virtual microphones can be established. A virtual microphone can be selected for active noise reduction, wherein a selection of the virtual microphone being located next to the detected location of the user's ear will provide the most efficient noise cancelation. Systems using a plurality of virtual microphone positions are for example known from EP 3 435 372 A1 or from WO 2020/047286 A1.
Irrespective of the particular implementation of the noise reduction system, it was observed that the systems sometimes suffer from instabilities under varying operating conditions.
It is an object to provide a noise reduction system for actively compensating background noise, a method of operating such a system and use of said system, wherein efficient and stable noise reduction in a noise reduction area should be provided.
Such object can be solved by a noise reduction system for actively compensating background noise generated by a noise source in a noise reduction area in a passenger transport area of a vehicle, the system comprising a controller comprising hardware, a reference sensor for detecting the background noise of the noise source, a sound generator for generating anti-noise for superimposing the anti-noise with the background noise in the noise reduction area for active reduction of the background noise, and a monitor-microphone array having a plurality of monitor microphones, the monitor-microphone array being disposed adjacent to the noise reduction area and being configured to pick up background noise emitted by the noise source and anti-noise emitted by the sound generator, wherein a virtual sensing algorithm is implemented in the controller, which is thereby configured to estimate an error signal at a position of a virtual microphone, wherein the virtual microphone is located in the noise reduction area and the error signal is indicative of a difference between the background noise and the anti-noise at the position of the virtual microphone, the controller further comprising an anti-noise unit for generating an anti-noise signal for driving the sound generator in that it generates the anti-noise, the system is further enhanced by a nonlinearity filter unit having a model of a non-linear transfer function of the sound generator, wherein the filter unit is configured to receive the anti-noise signal and to generate a corrected anti-noise signal by applying a nonlinear filter function on the anti-noise signal, which is based on the model of the non-linear transfer function in that the non-linear response of the sound generator is at least partially corrected when driven by the corrected anti-noise signal, wherein the nonlinearity filter unit is further configured to output the corrected anti-noise signal to the sound generator.
The noise reduction system can provide enhanced stability. Nonlinear harmonics of the sound generator, which can be for example a loudspeaker or another electromagnetic actuator, result in undesired disturbances in the generated anti-noise signal and by that also in the estimated error signal. Typically applied linear filters are not capable of taking into account the nonlinear behavior of the sound generator. As a result of this, the noise-canceling algorithm attempts to compensate for frequencies that are generated due to the nonlinear effects in the sound generator. This, however, sometimes fails when applying prior art approaches and therefore, the traditional noise-canceling can become unstable. By combining the compensation for the nonlinear behavior of the sound generator with the concept of virtual microphones, the noise-canceling can be both, very efficient and very stable.
Compensation of the nonlinear effects in sound generators, such as for loudspeakers, is generally known from, for example DE 43 34 040 A1 or DE 41 11 884 A1. Nonlinearities in electromechanical and electro acoustical transducers basically occur when large output signals are desired and the transducer is urged to operate at large amplitudes. While most transducers, for example loudspeakers, operate with linear response at small amplitudes, for higher amplitudes, nonlinear effects come into play. The nonlinearity filter unit can compensate for this effect. The parameters for the nonlinearity filter unit can be derived for example from a test measurement of the sound generator or from simulations.
It was found that the combination of the concept of virtual microphones together with the compensation of nonlinear effects of the sound generator can be very advantageous. It could be found that the nonlinearities of the sound generator sometimes mislead the noise-canceling algorithm. This can result in instabilities of the noise-canceling algorithm, which cannot be overcome by optimizing of the noise-canceling algorithm itself. It was therefore necessary to take a completely different approach, namely the compensation of the non-linear behavior of the sound generator, to stabilize the noise-canceling algorithm. This unconventional and counterintuitive approach surprisingly resulted in the desired effect.
According to an embodiment, the noise reduction system can be further enhanced in that the sound generator is an electromechanical device and the model of the non-linear transfer function is an adaptive model being configured to adapt on a change in at least one mechanical parameter of the sound generator.
The sound generator can be for example a loudspeaker or another electromagnetic actuator. The noise-canceling system and thereby the sound generator are exposed to varying environmental conditions, when installed in a vehicle. Varying environmental conditions are for example varying humidity and/or temperature. These influence the response behavior of the sound generator, because the mechanical parts thereof change their physical properties with varying temperature, for example. By compensating for these effects, the noise-canceling system can be reliably operated even under different and harsh environmental conditions.
According to an embodiment, the controller can further comprise an averaging unit, which can be configured to calculate an average error signal, which is indicative of a difference between the background noise and the anti-noise at more than one position in the noise reduction area and a dynamic adjustment unit, which is configured to update parameters of the anti-noise unit based on the average error signal and so as to minimize the average error signal.
By averaging the error signals, wherein an average of two or more virtual microphones is taken into account, the quiet zone can be significantly increased. At the same time, the computational load can be reduced to a level, which is similar to systems using only a single virtual microphone. This can represent a significant advantage for practical implementation of the system.
According to an embodiment, the virtual sensing algorithm in the controller can be implemented according to the remote microphone technique. This can be advantageous in practical experiments because it provides the best performance under the desired circumstances.
According to further embodiments, the virtual sensing algorithm can be implemented by other means. For example, the controller can comprise a virtual sensing algorithm which is a virtual microphone arrangement, a forward difference prediction technique, an adaptive LMS virtual microphone technique, a Kalman filtering virtual sensing algorithm or a stochastically optimal tonal diffuse field virtual sensing technique. One of these algorithms can be implemented in the control unit according to further embodiments. Without prejudice, in the following description, further reference will be made to the embodiment in which the remote microphone technique is implemented.
The virtual microphones in the noise reduction area can be arranged in a grid or the position of the virtual microphones can be freely selected and defined. It is also possible to dynamically rearrange the virtual microphones, which means that their positions can be changed or optimized during operation of the system. There is multiplicity of predetermined positions, at which the virtual microphones can be placed.
A plurality of positions can be located in the noise reduction area and the controller can be configured to estimate at least a first error signal for a virtual microphone located at a first position and a second error signal for a virtual microphone located at a second position and the averaging unit can be configured to calculate the average error signal from at least the first and the second error signal.
Averaging of the error signal can be for example performed in that the averaging unit can be further configured to calculate the average error signal, which is an arithmetic average of the at least first and second error signal.
According to another embodiment, the noise reduction system can comprise the feature according to which the averaging unit can be further configured to calculate an average error signal, which can be a weighted average of the at least first and second error signal. Calculating a weighted average of the error signals can allow focus on one or more positions in the noise reduction area. This can be performed by overemphasizing the respective virtual microphone. The emphasis can be put on a single virtual microphone or one more than one microphone, depending on whether particular emphasis should be put on one or on more than a single position. This can result in a shift of the quiet zone to a certain area or to certain areas, while the overall area of the quit zone can be increased. The emphasis can be put on said virtual microphone by overweighting the signal of this microphone in the calculation of the weighted average. For example, the signal can be multiplied by a factor greater than one, which defines the overweight, while the remaining signals are considered without a factor, when calculating the weighted average.
The noise reduction system, according to a further embodiment, can comprise a camera arrangement and a position detection unit for detecting a position and/or orientation of a head of a user in the passenger transport area, wherein the controller can be further configured to select a main virtual microphone position of the plurality of positions for the virtual microphones adjacent to an estimated position of an ear of the user, wherein the averaging unit can be configured to overweight the error signal at the main virtual microphone position when calculating the average error signal.
The position detection unit can be configured as a head tracking system. Using this system, the quiet zone can follow the movement of the passenger's head. This can be performed by shifting the position of the virtual microphone, which can be overemphasized in the calculation of the weighted average. If the virtual microphones are arranged in a fixed pattern or grid, the virtual microphone being located nearest to the auditory channel of a user's ear, can be selected as the microphone on which particular emphasis is put. When calculating the weighted average, this particular virtual microphone can be overemphasized.
According to yet another embodiment, the noise reduction system can be further enhanced in that the controller can comprise: a first filter unit configured to receive the anti-noise signal and to estimate a shifted anti-noise signal, which can be indicative of the anti-noise at a physical position of one of the monitor microphones of the monitor-microphone array, a first arithmetic unit configured to receive the shifted anti-noise signal and a monitor signal of the monitor microphone being located at said physical position, wherein the first arithmetic unit can be configured to calculate a residual signal, which can be a difference between the monitor signal and the shifted anti-noise signal at the physical position of the monitor microphone, a second filter unit, which can be configured to receive the residual signal and to estimate a shifted residual signal, which can be the residual signal shifted to the position of the virtual microphone, a third filter unit configured to receive the anti-noise signal and to estimate a shifted anti-noise signal, which can be indicative of the anti-noise at the position of the virtual microphone, a second arithmetic unit configured to receive the shifted residual signal and the shifted anti-noise signal and to estimate the error signal for the position of the virtual microphone by addition of the shifted residual signal and the shifted anti-noise signal.
In particular, the first filter unit, the first arithmetic unit, the second filter unit, the third filter unit and the second arithmetic unit can be configured to calculate and estimate the respective signals for at least the first and the second position, such as for all positions in the noise reduction area.
By taking into account all virtual microphones, which can be located in the noise reduction area, the quiet zone can be maximized. Furthermore, a maximum flexibility with respect to head tracking and weighting during calculation of the average error signal can be provided.
In another embodiment, the averaging unit can be configured to calculate an average error signal, which can be indicative of a difference between the background noise and the anti-noise in a predetermined area of the noise reduction area comprising more than one position.
The averaging unit can be configured to receive a plurality of monitor signals of monitor microphones being located at different physical positions and to estimate an area monitor signal, which can be indicative of a monitor signal captured by the monitor microphones for a predetermined area of the monitor microphones, wherein the controller can comprise: a first filter unit configured to receive the anti-noise signal and to estimate a shifted area anti-noise signal, which can be indicative of the anti-noise in the predetermined area, a first arithmetic unit configured to receive the shifted area anti-noise signal and the area monitor signal, wherein the first arithmetic unit can be configured to calculate an area residual signal, which is a difference between the area monitor signal and the shifted area anti-noise signal, a second filter unit, which can be configured to receive the area residual signal and to estimate a shifted area residual signal, which is the area residual signal shifted to a predetermined virtual area comprising more than one position of a virtual microphone, a third filter unit configured to receive the anti-noise signal and to estimate a shifted area anti-noise signal, which can be indicative of the anti-noise in the predetermined virtual area, and the averaging unit further comprises a second arithmetic unit configured to receive the shifted area residual signal and the shifted area anti-noise signal and to estimate the error signal for the predetermined virtual area as the average error signal, by addition of the shifted area residual signal and the shifted area anti-noise signal.
The area based calculation can reduce the computational load while, at the same time, the quiet zone can be enlarged.
On the other hand, the averaging over the plurality of error values for different positions in the quiet zone can allow a dynamic and flexible adaption of the system, wherein emphasis can be put on various points in the noise reduction area. While the area based calculation can be a more static solution, the average based solution using a plurality of error values can be dynamically adapted on the individual use situation for example in combination with head tracking.
The noise reduction system according to another embodiment can be further enhanced in that the monitor-microphone array can further comprise a direct monitor microphone and the averaging unit can be configured to calculate the average error signal, by further taking into account a direct residual signal of the direct monitor microphone.
The direct signal of the reference microphone can act as a physical support vector for the calculation, which can be based on the estimated signals of the virtual microphones. Although this measure is counterintuitive, it could be found that this measure enhances the robustness of the algorithm. It could further be found that the direct signal of the reference microphone compensates for estimation errors in the signals of the virtual microphones. The algorithm using weighted control can become more robust when compared to traditional solutions.
The first filter unit can be further configured to estimate a shifted direct anti-noise signal, which can be indicative of the anti-noise at a physical position of the direct monitor-microphone, the first arithmetic unit can be further configured to receive the shifted direct anti-noise signal and a direct monitor signal of the direct monitor microphone, wherein the first arithmetic unit can be configured to further calculate a direct residual signal, which can be a difference between the direct monitor signal and the shifted direct anti-noise signal at the position of the direct monitor microphone, the second filter unit and the second arithmetic unit can be configured to bypass the direct residual signal and the averaging unit can be further configured to calculate the average error signal, which can be an average of the at least one error signal for a position in the noise reduction area and the direct residual signal.
Furthermore, the averaging unit can be configured to bypass a direct monitor signal of the direct monitor microphone, the first arithmetic unit can be further configured to receive the shifted direct anti-noise signal and a direct monitor signal of the direct monitor microphone, wherein the first arithmetic unit can be configured to further calculate a direct residual signal, which can be a difference between the direct monitor signal and the shifted direct anti-noise signal at the position of the direct monitor microphone, the first arithmetic unit can be further configured to receive the shifted direct anti-noise signal and a direct monitor signal of the direct monitor microphone, wherein the first arithmetic unit can be configured to further calculate a direct residual signal, which can be a difference between the direct monitor signal and the shifted direct anti-noise signal at the position of the direct monitor microphone, the second filter unit and the second arithmetic unit can be configured to bypass the direct residual signal and the averaging unit can be further configured to calculate the average error signal, which can be an average of the error signal for the predetermined virtual area and the direct residual signal.
Furthermore, the noise reduction system can be enhanced in that the controller can further comprise at least one band pass unit, which can be configured to apply a band pass filter on the average error signal and/or on a noise signal picked up by the reference sensor for detecting the background noise of the noise source.
The band pass filter can be a band pass for the frequency range between 50 Hz and 600 Hz. Furthermore, it can be a low-pass filter, wherein a cutoff frequency of the low-pass filter can be between 400 Hz and 1000 Hz, such as between 500 Hz and 800 Hz, or such as at least approximately 600 Hz. The upper cutoff frequency can be chosen in that a prefix of the anti-noise signal does not change within the noise reduction area. This prerequisite can provide for the stability of the noise-canceling algorithm. When calculating a spatial distance from a frequency in one of the mentioned ranges, applying the well-known formula by further taking into account the speed of sound, this results in a spatial distance of about 0.2 m. This limit should be a maximum distance for the points at which the virtual microphones are arranged. The same applies for a distance between the point at which the virtual microphone can be arranged, i.e. one of the aforementioned points, and the physical position of the direct microphone.
Such object can be further solved by a method of operating a noise reduction system for actively compensating background noise generated by a noise source in a noise reduction area in a passenger transport area of a vehicle, the system comprising a controller, a reference sensor for detecting the background noise of the noise source, a sound generator for generating anti-noise for superimposing the anti-noise with the background noise in the noise reduction area for active reduction of the background noise, and a monitor-microphone array having a plurality of monitor microphones, the monitor-microphone array being disposed adjacent to the noise reduction area and being configured to pick up background noise emitted by the noise source and anti-noise emitted by the sound generator, wherein a virtual sensing algorithm is implemented in the controller, which thereby estimates an error signal at a position of a virtual microphone, wherein the virtual microphone is located in the noise reduction area and the error signal is indicative of a difference between the background noise and the anti-noise at the position of the virtual microphone, the controller can further comprise an anti-noise unit for generating an anti-noise signal for driving the sound generator in that it generates the anti-noise, wherein the method can be further enhance by a nonlinearity filter unit having a model of a non-linear transfer function of the sound generator, wherein the filter unit receives the anti-noise signal and generates a corrected anti-noise signal by applying a non-linear filter function on the anti-noise signal, which is based on the model of the non-linear transfer function in that the non-linear response of the sound generator is at least partially corrected when driven by the corrected anti-noise signal, wherein the nonlinearity filter unit outputs the corrected anti-noise signal to the sound generator.
In an embodiment, the sound generator can be an electromechanical device and the model of the non-linear transfer function can be an adaptive model which adapts on a change in at least one mechanical parameter of the sound generator.
According to another embodiment, the controller can further comprise an averaging unit, which can calculate an average error signal, which can be indicative of a difference between the background noise and the anti-noise at more than one position in the noise reduction area and a dynamic adjustment unit, which updates parameters of the anti-noise unit based on the average error signal and so as to minimize the average error signal.
Furthermore, the method can be enhanced in that a plurality of positions can be located in the noise reduction area and the controller can estimate at least a first error signal for a virtual microphone located at a first position and a second error signal for a virtual microphone located at a second position and the averaging unit can calculate the average error signal from at least the first and the second error signal.
The averaging unit can further calculate the average error signal, which can be an arithmetic average of the at least first and second error signal.
According to an embodiment, the averaging unit can calculate the average error signal, which can be a weighted average of the at least first and second error signal, wherein the noise reduction system can further comprise a position detection unit which detects a position and/or orientation of a head and estimates a position of an ear of a user in the passenger transport area, wherein the controller can further select a main position of the plurality of positions, which is adjacent to the estimated position of the ear of the user, wherein the averaging unit gives an overweight to the error signal at the main position when calculating the average error signal.
In another embodiment, the controller can comprise: a first filter unit, which receives the anti-noise signal and estimates a shifted anti-noise signal, which can be indicative of the anti-noise at a physical position of one of the monitor microphones of the microphone array, a first arithmetic unit, which can receive the shifted anti-noise signal and a monitor signal of the monitor microphone being located at said physical position, wherein the first arithmetic unit can calculate a residual signal, which can be a difference between the monitor signal and the shifted anti-noise signal at the physical position of the monitor microphone, a second filter unit can receive the residual signal and estimates a shifted residual signal, which can be the residual signal shifted to the position (P) of the virtual microphone, a third filter unit, which can receive the anti-noise signal and estimate a shifted anti-noise signal, which can be indicative of the anti-noise at the position of the virtual microphone, a second arithmetic unit, which can receive the shifted residual signal and the shifted anti-noise signal and estimate the error signal for the position of the virtual microphone by adding the shifted residual signal and the shifted anti-noise signal.
The first filter unit, the first arithmetic unit, the second filter unit, the third filter unit and the second arithmetic unit can calculate and estimate the respective signals for at least the first and the second position, such as for all positions in the noise reduction area.
According to an embodiment, the averaging unit can calculate an average error signal, which can be indicative of a difference between the background noise and the anti-noise in a predetermined area of the noise reduction area comprising more than one position.
The averaging unit can receive a plurality of monitor signals of monitor microphones being located at different physical positions and estimate an area monitor signal, which can be indicative of an error signal captured by the monitor microphones for a predetermined area of the monitor microphones, wherein the controller can comprise: a first filter unit, which can receive the anti-noise signal and estimate a shifted area anti-noise signal, which can be indicative of the anti-noise in the predetermined area, a first arithmetic unit, which can receive the shifted area anti-noise signal and the area monitor signal, wherein the first arithmetic unit calculates an area residual signal, which can be a difference between the area monitor signal and the shifted area anti-noise signal, a second filter unit, which can receive the area residual signal and estimate a shifted area residual signal, which can be the area residual signal shifted to a predetermined virtual area comprising more than one position of a virtual microphone, a third filter unit, which can receive the anti-noise signal and estimate a shifted area anti-noise signal, which can be indicative of the anti-noise in the predetermined virtual area, and the averaging unit can further comprise a second arithmetic unit, which can receive the shifted area residual signal and the shifted area anti-noise signal and estimate the error signal for the predetermined virtual area as the average error signal by adding the shifted area residual signal and the shifted area anti-noise signal.
According to an embodiment, the monitor-microphone array can further comprise a direct monitor microphone and the averaging unit can calculate the average error signal, by further taking into account a direct residual signal of the direct monitor microphone.
The first filter unit can further estimate a shifted direct anti-noise signal, which can be indicative of the anti-noise at a physical position of the direct monitor microphone, the first arithmetic unit can further receive the shifted direct anti-noise signal and a direct monitor signal of the direct monitor microphone, wherein the first arithmetic unit can further calculate a direct residual signal, which can be a difference between the direct monitor signal and the shifted direct anti-noise signal at the position of the direct monitor microphone, the second filter unit and the second arithmetic unit can bypass the direct residual signal and the averaging unit can calculate the average error signal, which can be an average of the at least one error signal for a position in the noise reduction area and the direct residual signal.
Furthermore, the averaging unit can bypass a direct monitor signal of the direct monitor microphone, the first arithmetic unit can further receive the shifted direct anti-noise signal and a direct monitor signal of the direct monitor microphone, wherein the first arithmetic unit can further calculate a direct residual signal, which can be a difference between the direct monitor signal and the shifted direct anti-noise signal at the position of the direct monitor microphone, the first arithmetic unit can further receive the shifted direct anti-noise signal and a direct monitor signal of the direct monitor microphone, wherein the first arithmetic unit can further calculate a direct residual signal, which can be a difference between the direct monitor signal and the shifted direct anti-noise signal at the position of the direct monitor microphone, the second filter unit and the second arithmetic unit can bypass the direct residual signal and the averaging unit can further calculate the average error signal, which can be an average of the error signal for the predetermined virtual area and the direct residual signal.
According to still another embodiment, the controller can further comprise at least one band pass unit, which can apply a band pass filter on the average error signal and/or on a noise signal picked up by the reference sensor for detecting the background noise of the noise source.
Furthermore, the method can be enhanced by actively compensating background noise generated by a noise source in a noise reduction area in a passenger transport area of a vehicle, such as in a commercial vehicle, or in a construction vehicle.
Same or similar advantages and advantageous embodiments which have been mentioned with respect to the noise reduction system apply to the method of operating the noise reduction system in a same or similar way and are therefore not repeated.
Such object can also be solved by use of the noise reduction system according to any of the previously mentioned embodiments. The used noise reduction system is for actively compensating background noise generated by a noise source in a noise reduction area in a passenger transport area of a vehicle. Such vehicle can be a commercial vehicle, or a construction vehicle.
Further features of the embodiments will become apparent from the description of the embodiments together with the claims and the attached drawings. Embodiments can fulfill individual features or a combination of several features.
The embodiments are described below, without restricting the general idea of the invention, using exemplary embodiments with reference to the drawings, express reference being made to the drawings with regard to all details that are not explained in greater detail in the text. In the drawings:
In the drawings, the same or similar elements and/or parts are provided with the same reference numbers in order to prevent the item from needing to be reintroduced.
The noise reduction system of the vehicle 2 comprises a control unit 10 (such as a processor/controller comprising hardware), which can be a separate electronic device. The control unit 10, however, can also be implemented as software in a main controller of the vehicle 2, which, in this case, provides the control unit 10. The noise reduction system further comprises a sound generator 12 for generating anti-noise. The sound generator 12 can be a loudspeaker. The anti-noise and the background noise are superimposed in a noise reduction area 14 for active reduction of the background noise. Furthermore, the noise reduction system comprises a monitor-microphone array 16, which is disposed adjacent to the noise reduction area 14. The monitor-microphone array 16 is configured to pick up background noise emitted by the noise source 6 and anti-noise emitted by the sound generator 12.
There is the control unit 10, a plurality of monitor microphones 15 forming the monitor-microphone array 16 and the sound generator 12. Furthermore, a sensor 8, for example a microphone, can be arranged in the headrest 24 for detecting the background noise of the noise source 6 (schematically represented by a loudspeaker). The senor 8 can also be arranged remote from the remaining parts of the system 20 as it is for example illustrated in
The noise reduction system 20 can be used with or without the sensor 8. The presence of the sensor 8 depends on whether the noise reduction system 20 is a feed forward system (with the reference sensor 8) or a feedback system (without the reference sensor 8). If the system 20 dispenses with the sensor 8, the background noise is directly detected using the monitor microphone array 16. Furthermore, the noise reduction system 20 comprises a sound generator 12, which is for example a loudspeaker. The sound generator 12 is also located in the headrest 24 by way of an example only.
The noise reduction system 20 further comprises a head tracking system 26, which comprises for example a pair of stereo cameras 28. The head tracking system 26 is applied for detecting a position and/or orientation of the head 30 of a passenger, who is situated in the passenger transport area 4. The head tracking system 26 is suitable for detecting the position of an ear of the user, such as the location of the entrance of the auditory channel. The head tracking system 26 can also be integrated in the headrest 24 so as to provide an integrated system. The position of the user's head 30 is detected or computed by the position detection unit 46 of the head tracking system 26.
The head tracking is suitable for establishing the noise reduction area 14 in that it is directly adjacent to the passenger's head 30, i.e. near to the passenger's ears. When making reference to a noise reduction area 14, it should be noted that there is a right noise reduction area 14b and a left noise reduction area 14a, which are established so as to provide a suitable noise reduction for both ears of the user. By way of an example and without limitation, for the purpose of simplification of explanations only, reference will be made to a noise reduction area 14 in the following. Notwithstanding the explanations are made for a single noise reduction area 14, the noise reduction system 20 is suitable for establishing two or even more noise reduction areas 14 for at least both ears of a passenger or even for a plurality of passengers.
In an attempt to establish the noise reduction area 14 at the most suitable position for efficient noise reduction, the noise reduction system 20 applies the concept of virtual microphones 32. The virtual microphone 32 is established in the noise reduction area 14. At a position of the virtual microphone 32, an error function is detected, which is the residual noise at the position of the virtual microphone 32 after noise cancelation. By minimizing the error function at the position of the virtual microphone 32, the noise reduction system 20 optimizes noise-canceling performance. This is why it is desirable to place the virtual microphone 32 as near to the entrance of the auditory channel of the passenger's head 30 as possible. This can be performed by for example relocating the position of the virtual microphone 32 based on data generated by the head tracking system 26.
The control unit 10 runs a virtual sensing algorithm which is commonly referred to as the “remote microphone technique”. Without prejudice, reference will be made to this type of algorithm in the following. According to further embodiments, alternative algorithms can be run on the control unit 10. These are for example algorithms referred to as: “virtual microphone arrangement”, “forward difference prediction technique”, “adaptive LMS virtual microphone technique”, “Kalman filtering virtual sensing” or “stochastically optimal tonal diffuse field virtual sensing technique”.
The noise reduction system 20 furthermore comprises the microphone array 16, which comprises a plurality of monitor microphones 15 each illustrated using a dot. The microphone array 16 is configured to pick up background noise and anti-noise for a plurality of virtual microphone positions P1, P2 . . . PN. The virtual microphone positions are referred to as P1, P2 . . . PN for an arbitrary number of N of virtual microphones 15. The virtual microphone positions are generally also referred to as P. They are located in the noise reduction area 14 and they can be arranged in a grid, by way of an example only.
A maximum distance between the positions P actually depends on the frequency range in which the noise-canceling algorithm operates. This frequency range can be between 50 Hz and 600 Hz. The upper limit or cutoff frequency is chosen in that a prefix of the anti-noise signal does not invert within the noise reduction area 14. This prerequisite can be advantageous for the stability of the noise-canceling algorithm. When calculating a spatial distance from this frequency, this results in a maximum spatial distance of about 0.2 m. This limit should be a maximum distance for the points P at which the virtual microphones are arranged. The same applies for a maximum distance between the point P at which the virtual microphone can be arranged, i.e. one of the aforementioned points P1 . . . PN and the physical position of the direct microphone 48, which will be explained in detail further below.
The frequency range can be set by integrating a band pass unit 50 in the signal line(s) of the either one or both of the noise signal S and the average error signal EA. The band pass unit 50 is illustrated in
In
The estimation of the average error signal EA reflects more than one position P in the noise reduction area 14. It can be either performed by calculating more than one error signal or by calculating an average error signal, which is indicative of a difference between the background noise and the anti-noise in a predetermined section PQ of the noise reduction area 14, wherein the section PQ comprises more than one position P. The first concept will be explained in the following by making reference to
Referring back to
Furthermore, the control unit 10 comprises a first arithmetic unit 39. The first arithmetic unit 39 receives the shifted anti-noise signals A(x) and a monitor signal, generally referred to as N(x), of the monitor microphones 15 being located at the physical position x. The first arithmetic unit 39 can receive the shifted anti-noise signals A(x1), A(x2), A(x3) and A(x4) and the monitor signal N(x1 . . . x4) of the monitor microphones 15 being located at positions x1 . . . x4. The first arithmetic unit 39 is configured to calculate a residual signal, which is generally denoted R(x) and which is a difference between the monitor signal N(x) and the shifted anti-noise signal A(x) at the physical position x of the monitor microphone 15. The first arithmetic unit 39 can calculate the residual signals R(x1), R(x2), R(x3) and R(x4), which is a respective difference between A(x1) and N(x1), A(x2) and N(x2), A(x3) and N(x3) and A(x4) and N(x4). The residual signal R(x) is the residual noise at the respective position x of the monitor microphone 15, which means the noise generated by the noise source 6 minus the anti-noise signal at a respective position x.
The residual signals R(x) are input to a second filter unit 40. The second filter unit 40 is configured to estimate a shifted residual signal R(P), which is the residual signal R(x) shifted to the position P of the virtual microphone. Residual signals R(P1) . . . R(N) for a respective one of the position P1 . . . PN, such as for all the positions P in the noise reduction area 14, are calculated.
The control unit 10 further comprises a third filter unit 41, which receives the anti-noise signal A. The third filter unit 41 is configured to estimate a shifted anti-noise signal, which is generally denoted A(P) and which is indicative of the anti-noise at the position P of the virtual microphone 32. For calculation of a respective one of the shifted anti-noise signals A(P1) . . . A(PN), the third filter unit 41 can comprise respective subunits.
Furthermore, the control unit 10 comprises a second arithmetic unit 42, which receives the residual signals R(P) and the shifted anti-noise signals A(P), respectively. The second arithmetic unit 42 can receive the shifted residual signals R(P1) . . . R(PN) and the shifted anti-noise signals A(P1) . . . A(PN) for a respective one of the positions P1 . . . PN in the noise reduction area 14. The second arithmetic unit 42, from a respective one of these pairs of values, calculates or estimates an error signal, which should be generally denoted E(P), for the position P of the virtual microphone. A first error signal E(P1) can be calculated for a point P1, a second error signal E(P2) is calculated for a point P2, wherein this is continued up to the maximum number N of points P in the noise reduction area 14, which means the error signal E(PN).
All the error signals E(P1) . . . E(PN) are input to the averaging unit 44. From the error signals E(P), the averaging unit 44 calculates the average error signal EA. The average error signal EA can be the arithmetic average of all the previously mentioned error signals E(P1), E(P2) . . . E(PN). This averaging is performed at least for the first and the second position P1, P2 of the virtual microphones. The averaging unit 44 can be configured to compute the average error signal EA, which is the average of every error signal E(P1), E(P2) . . . E(PN) for all positions P1, P2 . . . PN of the virtual microphones located in the noise reduction area 14. The average error signal EA is input to the dynamic adjustment unit 36 to update parameters of the anti-noise filter unit 34, which means the updated parameters are calculated based on information about the average error signal EA and so as to minimize the average error signal EA. This leads to the effect of minimization of background noise generated by the noise source 6 in the noise reduction area 14.
The averaging unit 44 can be configured to calculate the average error signal EA from an arithmetic average of the individual error signals E(P1), E(P2) . . . E(PN). According to another embodiment, the averaging unit 44 of the noise reduction system 20 is configured to calculate the average error signal EA as a weighted average. This can be performed by giving one or more of the error signals E(P1), E(P2) . . . E(PN) an individual weight or weighting factor. When calculating this weighted average, particular emphasis can be put on a certain point P, at which a main virtual microphone is located. For example, if the head 30 of the passenger is in the position illustrated in
The location of the point PX, which is located nearest to the user's ear, can be performed by for example the head tracking system 26. For this purpose, the head tracking system 26 (see
The system 20 further comprises a nonlinearity filter unit 60 having a model of the sound generator 12. There nonlinearity filter unit 60 receives the anti-noise signal A. It processes the anti-noise signal A by applying a nonlinear filter function thereon. This nonlinear filter function is based on a model of the nonlinear transfer function of the sound generator 12. By application of the nonlinear filter function on the anti-noise signal A, the nonlinear response of the sound generator number 12 can be compensated. The nonlinear filter function of the sound generator 12 can be determined for example in a practical experiment, which is performed in advance.
Compensation of nonlinear effects in sound generators 12, which can be for example one or more loudspeaker(s), is generally known from for example DE 43 34 040 A1 or DE 41 11 884 A1. Nonlinearities in electromechanical and electroacoustical transducers basically occur when large output signals are desired and the transducer is urged to operate at large amplitudes.
The nonlinearity filter unit 60 can also be placed directly behind the anti-noise unit 34 in that the filtered anti-noise signal CA is not only input to the sound generator 12 but also to the first filter unit 38 and/or third filter unit 41. By feeding the filtered anti-noise signal CA also to the third filter unit 41, the determination of the error signals E(P1), E(P2) . . . E(PN)) can also be performed based on the filtered anti-noise signal CA. This will further enhance the stability of the noise-canceling algorithm.
The embodiment in
In
There is a further embodiment of the noise reduction system 20, which is illustrated in
The first filter unit 38 can be configured to estimate a shifted direct anti-noise signal A(xd). This signal A(xd) is indicative of the anti-noise at the physical position xd of the direct monitor microphone 48. Furthermore, the first arithmetic unit 39 is configured to receive the shifted direct anti-noise signal A(xd) and direct monitor signal N(xd) of the direct monitor microphone 48. The unit calculates a direct residual signal R(xd) from the difference of the direct monitor signal N(xd) and the shifted direct anti-noise signal A(xd), for the position xd of the direct monitor microphone 48. The second filter unit 40 and the second arithmetic unit 42 bypass the direct residual signal R(xd). The averaging unit 44 calculates the average error signal EA from the average of the error signals R(P1) . . . R(PN) for the positions P1 . . . PN in the noise reduction area 14 by further taking into account the direct residual signal R(xd). By further taking into account the direct residual signal R(xd), the stability of the noise-canceling in the noise reduction area 14 is enhanced.
Also this system 20 comprises a nonlinearity filter unit 60 for compensating for the nonlinear response of the sound generator 12. Compensation of the nonlinear effects in sound generators 12, for example of a loudspeaker, is in principle known from DE 43 34 040 A1 or DE 41 11 884 A1. Such compensation can be implemented in the nonlinearity filter unit 60—this can apply to all embodiments.
The third filter unit 41 receives the anti-noise signal A and estimates a shifted area anti-noise signal A(PQ), which is indicative of the anti-noise in the predetermined virtual area PQ. The averaging unit 44 further comprises the second arithmetic unit 42, which is configured to receive the shifted area residual signal R(PQ) and the shifted area anti-noise signal A(PQ). The second arithmetic unit 42 further estimates the error signal E(PQ) for the predetermined virtual area PQ as the average error signal EA. The average error signal EA is again feedback to the dynamic adjustment unit 36 so as allow this unit to adapt or optimize the parameters of the anti-noise unit 34.
The concept of the area calculation of the monitor signal N, the residual signal R and the anti-noise signal A can also be supplemented by further taking into account the signal of a direct microphone 48. This will be explained by making reference to the embodiment in
Units of the embodiment shown in
The averaging unit 44 calculates from this signal the area monitor signal N(xq), wherein the signals of the monitor microphones 15 being located for example at positions x1 . . . x3 are taken into account. Furthermore, the averaging unit 44 forwards the direct monitor signal N(xd) to the first arithmetic unit 39. At the first arithmetic unit 39, as already explained with reference to the embodiment shown in
The systems shown in
The various units described as part of the control unit 10 in
| Number | Date | Country | Kind |
|---|---|---|---|
| 10 2022 118 015.8 | Jul 2022 | DE | national |
