Disclosed herein are methods and systems relating to proximity compensation for remote microphone techniques.
Vehicles often include active noise cancelation (ANC) technologies to reduce ambient noise within the vehicle cabin. Such ANC technologies may require various microphones to be placed within the vehicle cabin. These microphones may aid the ANC system in generating an error signal. However, often times it is not practical to have a physical microphone present at certain locations within the vehicle cabin in these cases, remote microphone technology may be used.
A remote microphone system for a vehicle may include at least one physical microphone arranged within a vehicle cabin configured to generate an error signal at a virtual microphone location within the vehicle, a database configured to maintain a look up table of premeasured seat positions and associated transfer functions, and a processor. The processor may be configured to receive a seat position indicative of a seat location within the vehicle, and apply a transfer function associated with the premeasured position to a primary noise signal of the at least one physical microphone to generate the error signal.
A remote microphone system for estimating an error signal for noise cancelation within a vehicle may include at least one physical microphone arranged within a vehicle cabin configured to generate an error signal at a virtual microphone location within the vehicle at a vehicle seat, a database configured to maintain a look up table of premeasured seat positions and associated transfer functions, and a processor. The processor may be configured to receive a seat position of the vehicle seat, and apply a transfer function associated with the seat position to a primary noise signal of the at least one physical microphone to generate the error signal.
A method for estimating an error signal for a virtual microphone for noise cancelation within a vehicle may include receiving a seat position of a vehicle seat, determining whether the seat position corresponds to a premeasured seat position, and applying a transfer function associated with the seat position to a primary noise signal of at least one physical microphone to generate an error signal.
The embodiments of the present disclosure are pointed out with particularity in the appended claims. However, other features of the various embodiments will become more apparent and will be best understood by referring to the following detailed description in conjunction with the accompanying drawings in which:
As required, detailed embodiments of the present embodiments are disclosed herein; however, it is to be understood that the disclosed embodiments are merely exemplary of the embodiments that may be embodied in various and alternative forms. The figures are not necessarily to scale; some features may be exaggerated or minimized to show details of particular components. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present invention.
Traditionally, remote microphone techniques take the physical microphones within the vehicle and applicate an error signal at a location where there is no physical microphone. This remote or virtual location is often in an area targeted to be the occupant's ear. This remote microphone technique involves a preliminary stage where measurements are made with microphones at the physical and virtual locations whereby the relationship between these two locations is identified. A transfer function between these two locations is created, either from a primary noise measurement or via an acoustic transfer function method using an omnidirectional source. This transfer function can exist either from a single physical microphone to a single virtual microphone, or with multiple physical microphones to a single virtual microphone. The latter example may be used as often a single physical microphone cannot always approximate the signal at the virtual location.
However, existing remote microphone technologies assume a fixed location between the physical and virtual microphone. This may not be the case when an occupant moves or adjusts his or her seat. Upon such movement of the seat, so does the occupant's ear location, and thus rendering the virtual location of the virtual microphone inaccurate. This may affect the cancellation performance and stability of the ANC system.
Described herein is system that determines a transfer function of a virtual microphone based on an occupant's seat position. Certain seat positions may be premeasured and associated with transfer functions. Thus, the transfer function may be determined and selected based on a current seat position. This may be done by comparing the seat location to a set of premeasured positions. If the seat location corresponds to one of the premeasured positions, then the transfer function associated with the premeasured position is selected. If the seat location does not correspond to one of the premeasured positions, then the transfer function will be interpolated between the premeasured positions. That is, if the seat position is between a first premeasured position and a second premeasured position, then the transfer function will be selected based on an interpolation of the transfer functions associated with each of the first and second premeasured positions.
The memory 108 may store a look up table of transfer functions to be applied and associated with various seat locations and positions. These premeasured transfer functions may be associated with a premeasured position. If the seat position corresponds to one of the premeasured positions, then the transfer function Ĥ(z) associated with the premeasured position is selected. If the seat position does not correspond to one of the premeasured positions, then a transfer unction Ĥ(z) may be interpolated between the premeasured positions. That is, if the seat position is between a first premeasured position and a second premeasured position, then the transfer function Ĥ(z) will be selected based on an interpolation of the transfer functions Ĥ(z) associated with each of the first and second premeasured positions.
The processor 105 may be in communication with at least one physical microphone 110. In the example in
The vehicle 102 may include various vehicle seats 140. These seats 140 may be areas where passengers and occupants typically sit during use of the vehicle. As explained above, RMT technology may include virtual microphone locations.
Each seat 140 may include at least one sensor 142 configured to detect the seat position. The seat location may be the relative position of the seat 140 within the vehicle 102. Vehicle seats 140 may be adjusted vertically, laterally, axially, horizontally, etc. The seat location may include one or more of a vertical, lateral, axial, positions. The one or more sensors 142 may provide the processor 105 with the seat location. The look up table within the memory 108 may then in turn be used to associate a transfer function Ĥ(z) with a premeasured seat position.
The controller 105 may output a control signal y(n) to a secondary path Sp(z). The secondary path Sp(z) may produce an anti-noise signal yp(n) to the physical microphone 110. The controller 105 may provide the control signal y(n) to an estimated secondary (electroacoustic) path Ŝp(z) to the virtual microphone 130. The estimated secondary path may provide an estimated anti-noise signal ŷp(n) at the virtual microphone 130.
The physical microphone 110 may receive a primary noise source signal dm(n) and the secondary anti-noise signal ym(n) and output an error signal em(n) assessed at the physical microphone location. The estimated anti-noise signal ŷe(n) may be removed or subtracted from the error signal em(n) at 170 to provide an estimated primary noise signal {circumflex over (d)}e(n) at the physical location at 110.
An estimated transfer function Ĥ(z) may be applied to the estimated primary noise signal {circumflex over (d)}e(n) at the physical location 110 and produce an estimated primary noise signal {circumflex over (d)}v(n) at the virtual microphone 130. This transfer function Ĥ(z) may be generated and determined based on a preliminary identification stage or interpolation between the stored transfer functions Ĥ(z) between the physical and virtual microphones so that cancellation performance is maintained and stability is not an issue if the occupant moves their seat 140. This is described in more detail below. Because the transfer function is based on the seat location, the transfer function is especially relevant to the location of the virtual microphone 130.
The controller 105 also provides the control signal y(n) to an estimated secondary (electroacoustic) path to the virtual microphone 130. The estimated secondary path to the virtual microphone 130 may provide an estimated anti-noise signal at the virtual location to the virtual microphone 130. The virtual microphone 130 may receive the estimated primary noise signal at the virtual location, add it to the estimated anti-noise signal at the virtual location, and provide an estimated error at the virtual microphone location.
Additionally or alternatively, the transfer function may be approximated as a ratio of cross spectral density (physical to virtual signals) and the auto spectral density (physical signal) of the primary noise signals, represented by:
The above example transfer function may be dependent on the linearity of the primary noise signals and is application dependent.
Referring to
Thus, the transfer function Ĥ(z) may be determined and selected based on the seat position. This may be done by comparing the seat location to the premeasured positions. If the seat location corresponds to the premeasured positions, then the transfer function Ĥ(z) associated with the premeasured position is selected. If the seat location does not correspond to one of the premeasured positions, then the transfer function Ĥ(z) will be interpolated between the premeasured positions. That is, if the seat position is between a first premeasured position and a second premeasured position, then the transfer function Ĥ(z) will be selected based on an interpolation of the transfer functions Ĥ(z) associated with each of the first and second premeasured positions.
Current head tracking methods are more cumbersome and many vehicles are not equipped with such capabilities. This mechanism avoids the needs for a specific head tracking device, camera, ultrasonic sensors, etc., and uses existing elements.
An estimated transfer function Ĥ(z) may be applied to the estimated primary noise signal {circumflex over (d)}e(n) at the physical location 110 and produce an estimated primary noise signal {circumflex over (d)}v(n) at the virtual microphone 130.
At block 610, the controller 105 may determine whether the current seat position corresponds to a premeasured seat position. If so, the process 600 proceeds to block 615. If not, the process 600 proceeds to block 620.
At block 615, the controller 105 selects the transfer function Ĥ(z) associated with the corresponding premeasured seat position.
At block 620, the controller 105 selects the transfer function Ĥ(z) based on an interpolation of at least two known premeasured positions. That is, the transfer function may be determined by selecting a transfer function between the transfer functions corresponding to two known premeasured functions.
The process 600 then ends.
The embodiments of the present disclosure generally provide for a plurality of circuits or other electrical devices. All references to the circuits and other electrical devices and the functionality provided by each are not intended to be limited to encompassing only what is illustrated and described herein. While particular labels may be assigned to the various circuits or other electrical devices disclosed, such labels are not intended to limit the scope of operation for the circuits and the other electrical devices. Such circuits and other electrical devices may be combined with each other and/or separated in any manner based on the particular type of electrical implementation that is desired. It is recognized that any circuit or other electrical device disclosed herein may include any number of microcontrollers, a graphics processor unit (GPU), integrated circuits, memory devices (e.g., FLASH, random access memory (RAM), read only memory (ROM), electrically programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), or other suitable variants thereof) and software which co-act with one another to perform operation(s) disclosed herein. In addition, any one or more of the electrical devices may be configured to execute a computer-program that is embodied in a non-transitory computer readable medium programmed to perform any number of the functions as disclosed.
While exemplary embodiments are described above, it is not intended that these embodiments describe all possible forms of the invention. Rather, the words used in the specification are words of description rather than limitation, and it is understood that various changes may be made without departing from the spirit and scope of the invention. Additionally, the features of various implementing embodiments may be combined to form further embodiments of the invention.
This application is the U.S. national phase of PCT Application No. PCT/US2019/034945 filed on May 31, 2019, which claims the benefit of U.S. Provisional Application No. 62/679,275 filed Jun. 1, 2018, the disclosures of which are hereby incorporated in their entirety by reference herein.
Filing Document | Filing Date | Country | Kind |
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PCT/US2019/034945 | 5/31/2019 | WO | 00 |
Publishing Document | Publishing Date | Country | Kind |
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WO2019/232400 | 12/5/2019 | WO | A |
Number | Name | Date | Kind |
---|---|---|---|
9305541 | Caillet | Apr 2016 | B2 |
20170032806 | Konjeti | Feb 2017 | A1 |
20170061951 | Starobin | Mar 2017 | A1 |
20180047383 | Hera et al. | Feb 2018 | A1 |
Number | Date | Country |
---|---|---|
102014201228 | Aug 2014 | DE |
102015119494 | May 2016 | DE |
Number | Date | Country | |
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20210217401 A1 | Jul 2021 | US |
Number | Date | Country | |
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62679275 | Jun 2018 | US |