Active noise reduction device

Abstract

To provide an active noise reduction device with which it is possible to estimate a head position of an occupant and effectively reduce noise at the estimated head position of the occupant, and which is simple and inexpensive.SOLUTION: An active noise reduction device 11 for reducing a noise in an internal space of a moving vehicle, comprises: a reference signal generation device 12 that generates a reference signal that corresponds to the noise; a negating sound generation device 13 that generates a negating sound to negate the noise; an error detection device 14 that detects an error between the noise and the negating sound and generates an error signal that corresponds to the error; and a control device 15 that controls the negating sound generation device 13 on the basis of the reference signal and the error signal. The control device 15 updates an estimation value of acoustic characteristic of the internal space on the basis of the reference signal and the error signal, estimates a head position of an occupant present in the internal space on the basis of the updated estimation value of the acoustic characteristic, and updates a control filter W for controlling the negating sound generation device 13, on the basis of the estimated head position of the occupant.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an active noise reduction device that reduces noise by interfering with the noise with a canceling sound that is in the opposite phase to the noise. [Background technology]

[0002] Conventionally, active noise reduction devices have been known that reduce noise by interfering with a canceling sound that is in the opposite phase to the noise. For example, Patent Document 1 discloses an active noise reduction device that is configured to estimate the head position of an occupant based on an image captured by a camera and reduce noise at the estimated head position of the occupant. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2019 / 106748 Summary of the Invention [Problem to be solved by the invention]

[0004] However, in Patent Document 1, a dedicated device called a camera is required to estimate the head position of the occupant, which may complicate the configuration of the active noise reduction device and increase the cost of the active noise reduction device.

[0005] In view of the above background, an object of the present invention is to provide a simple and inexpensive active noise reduction device that can estimate the head position of an occupant and effectively reduce noise at the estimated head position of the occupant. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems, one aspect of the present invention is an active noise reduction device (11) for reducing noise in an interior space (5) of a moving body (1), comprising: a reference signal generation device (12) for generating a reference signal corresponding to the noise; a cancellation generation device (13) for generating a cancellation sound to cancel out the noise; an error detection device (14) for detecting an error between the noise and the cancellation sound and generating an error signal corresponding to the error; and a control device (15) for controlling the cancellation generation device based on the reference signal and the error signal, wherein the control device updates an estimate of acoustic characteristics of the interior space based on the reference signal and the error signal, estimates a head position of an occupant present in the interior space based on the updated estimate of acoustic characteristics, and updates a control filter (W) for controlling the cancellation generation device based on the estimated head position of the occupant.

[0007] According to this aspect, the occupant's head position can be estimated based on estimated values ​​of acoustic characteristics. Therefore, when the occupant's head position changes, the characteristics of the control filter can be changed to follow the change in the occupant's head position. This makes it possible to effectively reduce noise at the occupant's head position. Furthermore, since a dedicated device (such as a camera) for estimating the occupant's head position is not required, a simple and inexpensive active noise reduction device can be provided.

[0008] In the above aspect, the control device may generate an estimated signal of the noise at the head position of the occupant and an estimated signal of the cancellation at the head position of the occupant based on the estimated head position of the occupant, and update the control filter so that an error between the estimated signal of the noise at the head position of the occupant and the estimated signal of the cancellation at the head position of the occupant is minimized.

[0009] According to this aspect, the control filter can be appropriately updated based on the estimated head position of the occupant, thereby more effectively reducing noise at the head position of the occupant.

[0010] In the above aspect, the control device updates an estimate of the transfer characteristic of the noise from the noise source to the error detection device and an estimate of the transfer characteristic of the cancellation from the cancellation generation device to the error detection device based on the reference signal and the error signal, generates an estimate signal of the noise at the position of the error detection device based on the updated estimate of the transfer characteristic of the noise from the noise source to the error detection device, and filters a predetermined noise correction filter (H^ me ) to generate an estimated signal of the noise at the position of the occupant's head by correcting the estimated signal of the noise at the position of the error detection device, and generating an estimated signal of the noise at the position of the error detection device based on the updated estimated value of the transfer characteristic of the noise cancellation from the noise cancellation generating device to the error detection device, and generating an estimated signal of the noise cancellation ... estimated value of the transfer characteristic of the noise cancellation from the noise cancellation generating device to the error detection device by using a predetermined noise cancellation correction filter (C^ me ) to correct the estimated signal of the cancellation at the position of the error detection device, thereby generating the estimated signal of the cancellation at the position of the occupant's head.

[0011] According to this aspect, the estimated signals of the noise and the negated sound at the position of the occupant's head can be appropriately generated based on the estimated signals of the noise and the negated sound at the position of the error detection device. That is, the noise and the negated sound at the position of the occupant's head can be appropriately estimated based on the estimated signals of the noise and the negated sound at the position of the error detection device. Therefore, the noise at the position of the occupant's head can be more effectively reduced.

[0012] In the above aspect, the noise cancellation correction filter is defined as a ratio between a transfer characteristic of the noise cancellation from the noise cancellation generating device to the head position of the occupant and a transfer characteristic of the noise cancellation from the noise cancellation generating device to the error detection device, and the noise correction filter may be defined as a ratio between a transfer characteristic of the noise from the noise source to the head position of the occupant and a transfer characteristic of the noise from the noise source to the error detection device.

[0013] According to this aspect, the influence of factors other than the transfer characteristics of the noise (for example, changes in the state of the internal space) on the noise cancellation correction filter can be minimized, so the estimated signal of the noise cancellation can be appropriately corrected by the noise cancellation correction filter.Similarly, the influence of factors other than the transfer characteristics of the noise (for example, changes in the state of the internal space) on the noise correction filter can be minimized, so the estimated signal of the noise can be appropriately corrected by the noise correction filter.

[0014] In the above aspect, the control device may store, in table form, a relationship between the head position of the occupant and the coefficient of the noise cancellation correction filter, and a relationship between the head position of the occupant and the coefficient of the noise correction filter.

[0015] According to this aspect, the coefficients of the noise cancelling correction filter and the noise correction filter can be easily determined based on the head position of the occupant.

[0016] In the above aspect, the control device may have a neural network that has learned the relationship between the estimated value of the acoustic characteristics and the head position of the occupant, and may estimate the head position of the occupant by inputting the estimated value of the acoustic characteristics into the neural network.

[0017] According to this aspect, the head position of the occupant can be accurately estimated based on the estimated value of the acoustic characteristics. [Effects of the Invention]

[0018] According to the above aspects, it is possible to provide a simple and inexpensive active noise reduction device that can estimate the head position of an occupant and effectively reduce noise at the estimated head position of the occupant. [Brief explanation of the drawings]

[0019] [Figure 1] FIG. 1 is a schematic diagram showing a vehicle to which an active noise reduction device according to a first embodiment is applied; [Figure 2]FIG. 1 is a functional block diagram showing an active noise reduction device according to a first embodiment; [Figure 3] FIG. 1 is an explanatory diagram showing a process in which a head position estimation unit according to the first embodiment estimates the head position of an occupant; [Figure 4] FIG. 10 is an explanatory diagram showing a cancellation correction table according to the first embodiment; [Figure 5] FIG. 1 is an explanatory diagram illustrating the definitions of a noise cancellation filter and a noise correction filter according to the first embodiment; [Figure 6] A functional block diagram showing a cancellation estimation signal correction unit according to the first embodiment. [Figure 7] Graph showing road noise reduction effect [Figure 8] FIG. 1 is an explanatory diagram showing a method for constructing a neural network according to a first embodiment; [Figure 9] FIG. 1 is an explanatory diagram showing a first example of a method for constructing a cancellation correction table according to the first embodiment; [Figure 10] FIG. 10 is an explanatory diagram showing a second example of a method for constructing a cancellation correction table according to the first embodiment; [Figure 11] FIG. 1 is a schematic diagram showing a vehicle to which an active noise reduction device according to a modified example of the first embodiment is applied; [Figure 12] FIG. 10 is a schematic diagram showing a vehicle to which an active noise reduction device according to a second embodiment is applied; [Figure 13] FIG. 10 is a functional block diagram showing an active noise reduction device according to a second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0020] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In this specification, the "^" (hat) next to various symbols indicates an identified value or an estimated value. While the "^" is placed above various symbols in figures and formulas, it is placed after the various symbols in the main text.

[0021] (First embodiment) First, a first embodiment of the present invention will be described with reference to FIGS.

[0022] <Active Noise Reduction Device 11> FIG. 1 is a schematic diagram showing a vehicle 1 (an example of a moving body) to which an active noise reduction device 11 (hereinafter abbreviated as "noise reduction device 11") according to a first embodiment is applied. When a wheel 2 vibrates due to a force received from a road surface S and the vibration of the wheel 2 is transmitted to a vehicle body 4 via a suspension 3, road noise d is generated in a vehicle cabin 5 (an example of an interior space of a moving body). The noise reduction device 11 according to the first embodiment is a feedback control type ANC device (Active Noise Control Device) for reducing such road noise d. More specifically, the noise reduction device 11 generates a canceling sound y that is in the opposite phase to the road noise d, and causes the generated canceling sound y to interfere with the road noise d, thereby reducing the road noise d.

[0023] 1 and 2, the noise reduction device 11 includes a vibration sensor 12 (an example of a reference signal generating device) that generates a reference signal x corresponding to road noise d, a plurality of speakers 13 (an example of a noise canceling generating device) that generate a cancellation sound y to cancel out the road noise d, a plurality of error microphones 14 (an example of an error detecting device) that detect an error (synthetic sound) between the road noise d and the cancellation sound y and generate an error signal e corresponding to the detected error, and a control device 15 that controls the plurality of speakers 13 based on the reference signal x and the error signal e.

[0024] In addition, the symbol H in Fig. 2 m indicates the transfer characteristic of the road noise d from the noise source (in this embodiment, the road surface S) to the error microphone 14 (transfer characteristic of the primary path: an example of the acoustic characteristic inside the vehicle compartment 5). m indicates the transfer characteristic of the canceling sound y from the speaker 13 to the error microphone 14 (transfer characteristic of the secondary path: an example of the acoustic characteristic inside the vehicle compartment 5).

[0025] <Vibration sensor 12> 1, a vibration sensor 12 of a noise reduction device 11 is installed, for example, on a suspension 3. The vibration sensor 12 detects the acceleration of the suspension 3 corresponding to road noise d, and generates a reference signal x corresponding to the acceleration of the suspension 3. Note that in other embodiments, the vibration sensor 12 may be installed at a location other than the suspension 3 of the vehicle 1.

[0026] <Speaker 13> Each speaker 13 of the noise reduction device 11 constitutes, for example, part of the audio system of the vehicle 1 and is installed in the door of the vehicle 1. Note that in other embodiments, the speaker 13 may be provided separately from the audio system of the vehicle 1, or may be installed in a location other than the door of the vehicle 1 (for example, in the headrest 6a of the passenger seat 6 or on the floor below the passenger seat 6).

[0027] <Error Mic 14> Each error microphone 14 of the noise reduction device 11 is installed, for example, on the headrest 6a of the passenger seat 6. Note that in other embodiments, the error microphone 14 may be installed in a location other than the passenger seat 6 of the vehicle 1 (for example, on the ceiling above the passenger seat 6).

[0028] <Control device 15> The control device 15 of the noise reduction device 11 is an electronic control unit (ECU) that includes an arithmetic processing unit (a processor such as a CPU or an MPU) and a storage device (a memory such as a ROM or a RAM). The control device 15 may be configured as a single piece of hardware, or may be configured as a unit consisting of multiple pieces of hardware.

[0029] Referring to FIG. 2, the control device 15 includes, as functional components, a first A / D conversion unit 21, a control signal output unit 22, a D / A conversion unit 23, a second A / D conversion unit 24, an acoustic characteristic update unit 25, a reference signal correction unit 26, a head position estimation unit 27, an estimated signal correction unit 28, and a control filter update unit 29.

[0030] <First A / D conversion unit 21> The first A / D conversion unit 21 of the control device 15 converts the reference signal x output from the vibration sensor 12 from an analog signal to a digital signal, and outputs the converted reference signal x to the control signal output unit 22, the acoustic characteristic update unit 25, and the reference signal correction unit 26. Hereinafter, when simply described as "reference signal x", it indicates the reference signal x that has passed through the first A / D conversion unit 21.

[0031] <Control signal output unit 22> The control signal output unit 22 of the control device 15 is constituted by a control filter W. An FIR filter (finite impulse response filter) may be used for the control filter W, or a SAN filter (adaptive notch filter) may be used. The control signal output unit 22 generates a control signal u by performing a filter process on the reference signal x, and outputs the generated control signal u to the D / A conversion unit 23 and the acoustic characteristic update unit 25.

[0032] <D / A conversion unit 23> The D / A conversion unit 23 of the control device 15 converts the control signal u output from the control signal output unit 22 from a digital signal to an analog signal, and outputs it to the speaker 13. Thereby, the speaker 13 generates a canceling sound y according to the control signal u.

[0033] <Second A / D conversion unit 24> The second A / D conversion unit 24 of the control device 15 converts the error signal e output from the error microphone 14 from an analog signal to a digital signal, and outputs the converted error signal e to the acoustic characteristic update unit 25. Hereinafter, when simply described as "error signal e", it indicates the error signal e that has passed through the second A / D conversion unit 24.

[0034] <Acoustic characteristic update unit 25> The acoustic characteristic update unit 25 of the control device 15 updates the estimated value of the acoustic characteristics in the passenger compartment 5 based on the reference signal x, the control signal u, and the error signal e. The acoustic characteristic update unit 25 includes a canceling sound estimation signal generation unit 31, a noise estimation signal generation unit 32, and an adder 33.

[0035] The cancellation estimation signal generator 31 includes a secondary path filter unit 35 and a secondary path update unit 36 ​​.

[0036] The secondary path filter unit 35 is configured by a secondary path filter C^. The secondary path filter C^ has a transfer characteristic C of the cancellation sound y from the speaker 13 to the error microphone 14. m The secondary path filter C^ is a filter corresponding to an estimated value of (an example of an estimated value of an acoustic characteristic). An FIR filter or a SAN filter may be used as the secondary path filter C^.

[0037] The secondary path filter unit 35 performs filtering on the control signal u using the secondary path filter C^, thereby generating the cancellation estimated signal y^. m1 Generate the cancellation estimated signal y^ m1 is an estimated signal of the canceling sound y at the position of the error microphone 14 (hereinafter referred to as the "microphone position"). The secondary path filter unit 35 generates the canceling sound estimated signal y^ m1 is output to the adder 33.

[0038] The secondary path update unit 36 ​​updates the coefficients of the secondary path filter C^ using an adaptive algorithm such as an LMS (Least Mean Square) algorithm. More specifically, the secondary path update unit 36 ​​updates the coefficients of the secondary path filter C^ so that the virtual error signal e1 (details of which will be described later) output from the adder 33 is minimized.

[0039] The noise estimation signal generator 32 includes a primary path filter unit 38 and a primary path update unit 39 .

[0040] The primary path filter unit 38 is configured by a primary path filter H^. The primary path filter H^ has a transfer characteristic H m The primary path filter H^ is a filter corresponding to an estimated value of (an example of an estimated value of an acoustic characteristic). An FIR filter or a SAN filter may be used as the primary path filter H^.

[0041] The primary path filter unit 38 performs filtering on the reference signal x using the primary path filter H^, thereby generating a noise estimation signal d^. m Generate the noise estimation signal d^ m is an estimated signal of noise at the microphone position. The primary path filter unit 38 generates the estimated noise signal d̂ m is output to the adder 33 and the estimated signal correction unit 28.

[0042] The primary path update unit 39 updates the coefficients of the primary path filter H^ using an adaptive algorithm such as an LMS algorithm. More specifically, the primary path update unit 39 updates the coefficients of the primary path filter H^ so that the virtual error signal e1 (details of which will be described later) output from the adder 33 is minimized.

[0043] The adder 33 outputs the error signal e and the cancellation estimation signal y^. m1 and the noise estimation signal d^ m The adder 33 outputs the generated virtual error signal e1 to the cancellation estimation signal generator 31 and the noise estimation signal generator 32.

[0044] <Reference signal correction unit 26> The reference signal corrector 26 of the control device 15 is configured with a secondary path filter C^, similar to the canceling noise estimation signal generator 31. When the coefficient of the secondary path filter C^ is updated in the canceling noise estimation signal generator 31, the updated coefficient of the secondary path filter C^ is output to the reference signal corrector 26, and the coefficient of the secondary path filter C^ is updated in the reference signal corrector 26. In other words, the coefficient of the secondary path filter C^ set in the reference signal corrector 26 is not a fixed value but a value that is successively updated based on the signal from the canceling noise estimation signal generator 31.

[0045] The reference signal correction unit 26 performs a filter process on the reference signal x to obtain the cancellation estimated signal y^ m2 Generate the cancellation estimated signal y^ m2 is the cancellation estimated signal y^ m1Similarly, the estimated signal of the cancellation sound y at the microphone position is the cancellation sound estimated signal y^. m2 contains information about the secondary path filter C^. The reference signal corrector 26 corrects the generated cancellation estimation signal y^ m2 to the head position estimation unit 27 and the estimated signal correction unit 28.

[0046] <Head position estimation unit 27> The head position estimation unit 27 of the control device 15 estimates the head position of the occupant present in the vehicle compartment 5 based on the secondary path filter C^. More specifically, the head position estimation unit 27 estimates the head position of the occupant in the vehicle compartment 5 based on the coefficients of the secondary path filter C^ copied from the reference signal correction unit 26. The head position estimation unit 27 outputs the estimated head position of the occupant to the estimated signal correction unit 28.

[0047] 3, head position estimation unit 27 has a neural network that has learned the relationship between secondary path filter C^ and the head position of an occupant. The neural network is composed of n layers. Each layer of the neural network has coefficients (w1, w2, ..., wn). A method for constructing the neural network will be described later.

[0048] When an FIR filter is used as the secondary path filter C^, the head position estimation unit 27 calculates a sequence of coefficients (C1, C2, ..., C^) of the secondary path filter C^ corresponding to the impulse response. L ) from the reference signal correction unit 26. The sequence of coefficients of the secondary path filter C^ corresponding to the impulse response may be copied in a graph format. The head position estimation unit 27 inputs the copied sequence of coefficients of the secondary path filter C^ to a neural network, and acquires the occupant's head position (position 1, position 2, position 3, ...) output from the neural network in response to this input.

[0049] When a SAN filter is used as the secondary path filter C^, the head position estimation unit 27 copies the coefficients C^0 and C^1 of the secondary path filter C^ and the corresponding frequency f from the reference signal correction unit 26. The head position estimation unit 27 inputs the copied coefficients C^0 and C^1 of the secondary path filter C^ and the corresponding frequency f to a neural network, and acquires the occupant's head position (position 1, position 2, position 3, ...) output from the neural network in response to this input.

[0050] <Estimated signal correction unit 28> Referring to FIG. 2, the estimated signal corrector 28 of the control device 15 corrects the noise cancellation estimated signal y^ based on the head position of the occupant estimated by the head position estimator 27. m2 and noise estimation signal d^ m The estimated signal correcting unit 28 includes a database unit 41, a cancellation correcting unit 42, and a noise correcting unit 43.

[0051] 4(a) and 4(b), the database unit 41 stores a cancellation correction table Tc. The method for constructing the cancellation correction table Tc will be described later.

[0052] Referring to FIG. 4(a), when an FIR filter is used as the secondary path filter C^, the noise cancellation correction table Tc contains the noise cancellation correction filter C^ for each occupant's head position. me The database unit 41 stores a series of coefficients of the noise cancellation correction filter C^ (details will be described later) by referring to the noise cancellation correction table Tc based on the head position of the occupant estimated by the head position estimation unit 27. me The database unit 41 reads out the coefficient string of the cancellation correction filter C^ me The coefficient string is output to the cancellation correction unit 42.

[0053] Referring to FIG. 4(b), when a SAN filter is used as the secondary path filter C^, the noise cancellation correction table Tc contains the noise cancellation correction filter C^ for each occupant's head position. meThe coefficient table TN is stored. me The coefficient table TN contains the cancellation correction filter C^ for each frequency f. me The database unit 41 determines the coefficient table TN to be used by referring to the noise cancellation correction table Tc based on the head position of the occupant estimated by the head position estimation unit 27. Furthermore, the database unit 41 determines the noise cancellation correction filter C^ corresponding to the current control target frequency by referring to the coefficient table TN to be used based on the current control target frequency. me The database unit 41 reads out the coefficients C^0 and C^1 of the cancellation correction filter C^ me The coefficients C^0 and C^1 are output to the cancellation correction unit 42.

[0054] Although not shown in the figure, the database unit 41 stores a noise correction table similar to the cancellation correction table Tc. The database unit 41 stores the noise correction filter H^ in the same manner as above. me (Details will be explained later) or the noise compensation filter H^ corresponding to the current control target frequency me The database unit 41 reads out the coefficients H^0 and H^1 of the noise correction filter H^ me or the noise compensation filter H^ corresponding to the current controlled frequency me The coefficients H^0 and H^1 are output to the noise correction unit 43.

[0055] As described above, the database unit 41 stores the head position of the occupant and the noise cancellation correction filter C^ me The relationship between the coefficients of the occupant's head position and the noise correction filter H^ me The relationship between the coefficients of and are stored in table format.

[0056] Referring to FIG. 2, the cancellation correction unit 42 uses a cancellation correction filter C^ me It is composed of the cancellation correction filter C^ me An FIR filter or a SAN filter may be used for the cancellation correction filter C^.me The coefficients of the cancellation correction filter C^ output from the database unit 41 me It is updated at any time by the coefficient of

[0057] Referring to Figure 5, the cancellation correction filter C^ me is defined by the following formula (1). However, C in the following formula (1) e indicates the transfer characteristic of the sound cancellation y from the speaker 13 to the head position of the occupant (particularly, the ear position of the occupant), and is expressed by C in the following equation (1): m indicates the transfer characteristic of the cancellation sound y from the speaker 13 to the error microphone 14.

number

[0058] Referring to FIG. 2, the cancellation correction unit 42 uses a cancellation correction filter C^ me Using the cancellation estimation signal y^ m2 By correcting e Generate the cancellation estimated signal y^ e is an estimated signal of the cancellation sound y at the position of the occupant's head (particularly, the position of the occupant's ear).

[0059] 6, the head position of the occupant estimated by the head position estimation unit 27 may be between position N (N: integer) and position N+1. In such a case, the noise cancellation correction unit 42 uses the noise cancellation correction filter C^ at position N. me (N) and the cancellation correction filter C^ at position N+1 me (N+1) and the cancellation estimated signal y^ m2 By performing linear interpolation on e may be generated.

[0060] Referring to FIG. 2, the noise correction unit 43 uses a noise correction filter H^ me The noise correction filter H^ me The noise correction filter H^ may be an FIR filter or an SAN filter. me The coefficients of the noise correction filter H^ output from the database unit 41 me It is updated at any time by the coefficient of

[0061] Referring to Figure 5, the noise compensation filter H^ me is defined by the following equation (2). e indicates the transmission characteristics of road noise d from the noise source to the head position of the occupant (especially the ear position of the occupant), and is expressed by H in the following equation (2). m indicates the transfer characteristic of the road noise d from the noise source to the error microphone 14.

number

[0062] Referring to FIG. 2, the noise correction unit 43 uses a noise correction filter H^ me Using the noise estimation signal d^ m By correcting the noise estimation signal d^ e Generate the noise estimation signal d^ e is an estimated signal of the road noise d at the position of the occupant's head (particularly, the position of the occupant's ear). m By performing linear interpolation on the noise estimation signal d^ e may be generated.

[0063] <Control filter update unit 29> The control filter update unit 29 is configured with a control filter W, similar to the control signal output unit 22. The control filter update unit 29 updates the control filter W based on the head position of the occupant estimated by the head position estimation unit 27. The control filter update unit 29 has a control filter unit 45, an adder 46, and a control update unit 47.

[0064] The control filter unit 45 uses the control filter W to generate the cancellation estimation signal y^ e Filter processing is performed on the cancellation estimated signal y^. e " refers to the cancellation estimation signal y^ that has passed through the control filter unit 45. e Shows.

[0065] The adder 46 outputs the cancellation estimation signal y^ e and noise estimation signal d^ e By adding and, the virtual error signal e e The adder 46 generates the generated virtual error signal e e is output to the control update unit 47.

[0066] The control update unit 47 uses an adaptive algorithm such as an LMS algorithm to update the coefficients of the control filter W. More specifically, the control update unit 47 updates the coefficients of the virtual error signal e output from the adder 46. e The coefficients of the control filter W are updated so that is minimized.

[0067] When the coefficients of the control filter W are updated in this manner in the control filter update unit 29, the updated coefficients of the control filter W are output to the control signal output unit 22, and the coefficients of the control filter W are updated in the control signal output unit 22. In other words, the coefficients of the control filter W set in the control signal output unit 22 are not fixed values, but are values ​​that are successively updated based on the signal from the control filter update unit 29.

[0068] <Principles of road noise reduction> Next, the principle by which the noise reduction device 11 reduces the road noise d will be described.

[0069] Cancellation estimated signal y^ e The noise reduction device 11 has a configuration and a noise canceling correction filter C^ me Based on the definition of , it can be expressed as the following equation (3). Similarly, the noise estimation signal d^ e The configuration of the noise reduction device 11 and the noise correction filter H^ me Based on the definition, it can be expressed as the following equation (4).

number

number

[0070] As is clear from the above equations (3) and (4), the virtual error signal e e (=d^ e +y^ e ) corresponds to the sound pressure after control (after sound reduction) at the head position of the occupant. Therefore, as described above, the virtual error signal e e By updating the coefficients of the control filter W so that d is minimized, the road noise d at the head position of the occupant can be effectively suppressed.

[0071] <Effects of the first embodiment> The control device 15 according to the first embodiment updates the primary path filter H^ and the secondary path filter C^ based on the reference signal x and the error signal e. In other words, the control device 15 updates the estimated value of the acoustic characteristics of the interior space based on the reference signal x and the error signal e. Therefore, even if the acoustic characteristics of the interior space change in response to the displacement of the error microphone 14, the characteristics of the control filter W can also be changed in response to this change in the acoustic characteristics. As a result, the error microphone 14 can be disposed on a movable part such as the headrest 6a, and the error microphone 14 can be brought closer to the position of the occupant's head.

[0072] On the other hand, the area where the control effect (noise reduction effect) of the noise reduction device 11 is high is limited to a part of the area (see circle A in FIG. 1 ) around the error microphone 14. Therefore, if the occupant's head moves away from the error microphone 14 depending on the driving posture of the occupant, the control effect of the noise reduction device 11 that the occupant can feel may decrease.

[0073] Therefore, the control device 15 estimates the head position of the occupant in the vehicle compartment 5 based on the updated secondary path filter C^, and updates the control filter W for controlling the speaker 13 based on the estimated head position of the occupant. Therefore, when the head position of the occupant changes, the characteristics of the control filter W can be changed to follow the change in the head position of the occupant. This makes it possible to effectively reduce the road noise d at the head position of the occupant. Furthermore, since a dedicated device (such as a camera) for estimating the head position of the occupant is not required, a simple and inexpensive noise reduction device 11 can be provided.

[0074] Fig. 7 is a graph showing the effect of reducing road noise d at the position of the occupant's head (particularly the position of the occupant's ears). As shown in Fig. 7, when the noise reduction device 11 of this embodiment (i.e., the noise reduction device 11 that updates the control filter W based on the occupant's head position) is turned on, the road noise d can be reduced over a wide frequency band compared to when a conventional noise reduction device (i.e., a noise reduction device that updates the control filter W without considering the occupant's head position) is turned on or when the noise reduction device 11 is turned off.

[0075] <How to build a neural network> Next, a method for constructing the neural network that constitutes head position estimation unit 27 will be described.

[0076] Referring to FIG. 8, when constructing a neural network, first, learning data is collected. More specifically, the coefficients of the secondary path filter C^ are measured for each occupant's head position. This measurement may be performed with a mannequin or the like placed in the occupant seat 6, or with an actual occupant sitting in the occupant seat 6. When an FIR filter is used as the secondary path filter C^, the measured coefficients of the secondary path filter C^ are output as an impulse response waveform. When a SAN filter is used as the secondary path filter C^, the measured coefficients of the secondary path filter C^ are output for each frequency.

[0077] The position of the occupant's head is determined by the relative positional relationship between the error microphone 14 and the occupant's head position. Therefore, regardless of whether the backrest of the occupant's seat 6 is reclined or not, if the relative positional relationship between the error microphone 14 and the occupant's head position is constant, the occupant's head position is considered to be the same (see "Position 1" in Figure 8).

[0078] Next, the coefficients of the secondary path filter C^ measured as described above are set as input values, and the occupant's head position is set as output values, and the neural network is made to learn the coefficients (w1, w2, ..., wn) of each layer. This learning is performed using a machine learning method such as deep learning.

[0079] Next, the neural network that has learned the coefficients w of each layer is stored as system parameters in the memory of the control device 15. This makes it possible to use the neural network to estimate the occupant's head position from the coefficients of the secondary path filter C^.

[0080] <How to build the cancellation correction table Tc> Next, a method for constructing the cancellation correction table Tc stored in the database unit 41 of the estimated signal correction unit 28 will be described with reference to Fig. 9 and Fig. 10. Fig. 9 is an explanatory diagram showing a first example of a method for constructing the cancellation correction table Tc, and Fig. 10 is an explanatory diagram showing a second example of a method for constructing the cancellation correction table Tc.

[0081] 9(a) and 9(b), in a first example of a method for constructing the cancellation correction table Tc, first, in a state where the identified sound yi is output from the speaker 13, the sound pressure signal S m The sound pressure signal S at the head position of the passenger was measured at a measurement microphone 14 m away. e is measured by the measurement microphone 14e, and the measured sound pressure signal S m , S e is recorded (step ST1: recording of signal).

[0082] Next, the recorded sound pressure signal S m , S e Using the cancellation correction filter C^ me Identify the coefficients of (Step ST2: C^ me More specifically, the sound pressure signal S e and the sound pressure signal S m For the cancellation correction filter C^ me The cancellation correction filter C^ is used to minimize the error signal between the signal filtered using me Update the coefficients of the cancellation correction filter C^ me The coefficients of are output as a sequence of coefficients of the FIR filter. Therefore, the cancellation correction filter C^ me When an FIR filter is used as the canceling correction filter C^ output from the identification system, me The coefficients of the above can be directly input into the cancellation correction table Tc, thereby constructing the cancellation correction table Tc.

[0083] On the other hand, the cancellation correction filter C^ me When the SAN filter is used as the filter, the calculated cancellation correction filter C^ output from the identification system is me An FFT (Fast Fourier Transform) is performed on the coefficients (sequence of FIR filter coefficients). This makes it possible to obtain the coefficients for each frequency of the SAN filter. By inputting the obtained coefficients for each frequency of the SAN filter into the noise cancellation correction table Tc, the noise cancellation correction table Tc can be constructed.

[0084] Referring to FIG. 10, in the second example of the method for constructing the cancellation correction table Tc, first, the sound pressure signal S e , S m Measure the sound pressure signal S e , S m Transfer characteristic C of cancellation y e , C m The coefficients of the cancelling sound y are extracted. e , C m The coefficients of are calculated as a sequence of coefficients of an FIR filter.

[0085] Next, the transfer characteristic C of the cancellation y e , C m By performing FFT on the coefficients (coefficient sequence of the FIR filter), the transfer characteristic C of the cancellation y is obtained. e , C m Next, calculate the frequency characteristics of the cancellation y. e The frequency characteristic of the sound cancellation y transfer characteristic from the speaker 13 to the head position of the passenger is expressed as the sound cancellation y transfer characteristic C m By dividing by the frequency characteristic of (transfer characteristic of the cancellation sound y from the speaker 13 to the error microphone 14), the cancellation correction filter C^ me Calculate the coefficient of the cancellation correction filter C^ me The coefficients of are calculated as the coefficients for each frequency of the SAN filter. Therefore, the cancellation correction filter C^ me When a SAN filter is used as the noise canceling filter, the noise canceling correction table Tc can be constructed by inputting the coefficients of the acquired SAN filter for each frequency into the noise canceling correction table Tc.

[0086] On the other hand, the cancellation correction filter C^ me If an FIR filter is used as the filter, the calculated cancellation correction filter C^ meIFFT (Inverse Fast Fourier Transform) is performed on the coefficients (coefficients for each frequency of the SAN filter). This makes it possible to obtain a sequence of coefficients for the FIR filter. By inputting the sequence of coefficients of the obtained FIR filter into the noise cancellation correction table Tc, the noise cancellation correction table Tc can be constructed.

[0087] The noise correction table (not shown) stored in the database unit 41 of the estimated signal correction unit 28 can also be constructed by a construction method similar to that of the noise cancellation correction table Tc. However, when constructing the noise correction table, the vehicle 1 is driven to generate actual road noise d while measuring the sound pressure signal S e , S m It is preferable to measure

[0088] <Modification of the first embodiment> In the first embodiment described above, the vibration sensor 12 installed on the suspension 3 is an example of the reference signal generating device. On the other hand, in other embodiments, as shown in Fig. 11, a reference microphone 16 placed near a noise source in the vehicle interior 5 may be an example of the reference signal generating device. In this case, the reference microphone 16 may detect a sound generated by the noise source and generate a reference signal x corresponding to the detected sound.

[0089] (Second embodiment) Next, a second embodiment of the present invention will be described with reference to Figures 12 and 13. Note that descriptions that overlap with the first embodiment of the present invention will be omitted as appropriate.

[0090] 12 is a schematic diagram showing a vehicle 1 to which an active noise reduction device 51 (hereinafter simply referred to as "noise reduction device 51") according to the second embodiment is applied. When the vehicle 1 runs, the internal combustion engine 7 (hereinafter simply referred to as "engine 7") vibrates, generating drivetrain noise d (for example, muffled noise from the engine 7 or propeller shaft) in the passenger compartment 5.

[0091] The noise reduction device 51 according to the second embodiment is a feedback control type ANC device for reducing drivetrain noise d caused by vibrations of the engine 7. In other embodiments, if an electric motor is used as the drive source of the vehicle 1 instead of the engine 7, the noise reduction device 51 may also reduce drivetrain noise d caused by vibrations of the electric motor. The configuration of the noise reduction device 51 according to the second embodiment, other than the reference signal generation device 52 and the control device 53, is the same as that of the noise reduction device 11 according to the first embodiment, and therefore description thereof will be omitted.

[0092] <Reference signal generation device 52> 13, the reference signal generating device 52 includes a frequency detecting circuit 56, a cosine wave generating circuit 57, and a sine wave generating circuit 58. The frequency detecting circuit 56 includes a cosine wave generating circuit 57 and a sine wave generating circuit 58. The cosine wave generating circuit 57 and the sine wave generating circuit 58 generate a reference signal.

[0093] The frequency detection circuit 56 detects the frequency of the drivetrain noise d (hereinafter referred to as "noise frequency f") based on vehicle information corresponding to the drivetrain noise d (for example, the rotation speed of the engine 7 and the vehicle speed). The frequency detection circuit 56 outputs the detected noise frequency f to the cosine wave generation circuit 57, the sine wave generation circuit 58, and the control device 53.

[0094] The cosine wave generating circuit 57 generates a reference cosine wave signal rc (an example of a reference signal) corresponding to the drive train noise d based on the noise frequency f output from the frequency detecting circuit 56. The cosine wave generating circuit 57 outputs the generated reference cosine wave signal rc to the control device 53.

[0095] The sine wave generating circuit 58 generates a reference sine wave signal rs (an example of a reference signal) corresponding to the drive train noise d based on the noise frequency f output from the frequency detecting circuit 56. The sine wave generating circuit 58 outputs the generated reference sine wave signal rs to the control device 53.

[0096] <Control device 53> The control device 53 includes, as functional components, a control signal output unit 62, a D / A conversion unit 63, an A / D conversion unit 64, an acoustic characteristic update unit 65, a reference signal correction unit 66, a head position estimation unit 67, an estimated signal correction unit 68, and a control filter update unit 69. Note that the configurations of the D / A conversion unit 63 and the A / D conversion unit 64 are similar to the configurations of the D / A conversion unit 23 and the second A / D conversion unit 24 of the control device 15 according to the first embodiment, and therefore description thereof will be omitted.

[0097] <Control signal output unit 62> The control signal output unit 62 of the control device 53 is configured by a control filter W. A SAN filter is used as the control filter W. The control signal output unit 62 includes a first control filter unit 71, a second control filter unit 72, a first adder 73, a third control filter unit 74, a fourth control filter unit 75, and a second adder 76.

[0098] The first control filter unit 71 has a control filter coefficient W0. The control filter coefficient W0 forms the real part of the coefficient of the control filter W. The first control filter unit 71 performs filtering on the reference cosine wave signal rc output from the reference signal generating device 52.

[0099] The second control filter unit 72 has a control filter coefficient W1. The control filter coefficient W1 forms the imaginary part of the coefficient of the control filter W. The second control filter unit 72 performs filtering on the reference sine wave signal rs output from the reference signal generating device 52.

[0100] The first adder 73 generates a control signal u0 by adding the reference cosine wave signal rc that has passed through the first control filter unit 71 and the reference sine wave signal rs that has passed through the second control filter unit 72. The first adder 73 outputs the generated control signal u0 to the D / A conversion unit 63 and the acoustic characteristic update unit 65.

[0101] The third control filter unit 74 has a coefficient obtained by inverting the polarity of the control filter coefficient W0. The third control filter unit 74 performs filtering on the reference sine wave signal rs output from the reference signal generating device 52.

[0102] The fourth control filter unit 75 has a control filter coefficient W1. The fourth control filter unit 75 performs filtering on the reference cosine wave signal rc output from the reference signal generator 52.

[0103] The second adder 76 generates a control signal u1 by adding the reference sine wave signal rs that has passed through the third control filter unit 74 and the reference cosine wave signal rc that has passed through the fourth control filter unit 75. The second adder 76 outputs the generated control signal u1 to the acoustic characteristic update unit 65.

[0104] <Acoustic characteristics update section 65> The acoustic characteristic update unit 65 of the control device 53 includes a cancellation estimation signal generator 81 , a noise estimation signal generator 82 , and a virtual error signal generator 83 .

[0105] The canceling noise estimation signal generation unit 81 is configured by a secondary path filter C^. A SAN filter is used as the secondary path filter C^. The canceling noise estimation signal generation unit 81 includes a first secondary path filter unit 91, a second secondary path filter unit 92, an adder 93, a first secondary path update unit 94, and a second secondary path update unit 95.

[0106] The first secondary path filter unit 91 has a secondary path filter coefficient C^0. The secondary path filter coefficient C^0 forms the real part of the coefficient of the secondary path filter C^. The first secondary path filter unit 91 performs filtering on the control signal u0 output from the control signal output unit 62.

[0107] The second secondary path filter unit 92 has a secondary path filter coefficient C^1. The secondary path filter coefficient C^1 forms the imaginary part of the coefficient of the secondary path filter C^. The second secondary path filter unit 92 performs filtering on the control signal u1 output from the control signal output unit 62.

[0108] The adder 93 adds the control signal u0 that has passed through the first secondary path filter unit 91 and the control signal u1 that has passed through the second secondary path filter unit 92 to generate the cancellation estimated signal y^ m1 The adder 93 generates the generated cancellation estimation signal y^. m1 is output to the virtual error signal generator 83.

[0109] The first secondary path update unit 94 updates the secondary path filter coefficient C^0 using an adaptive algorithm such as an LMS algorithm. More specifically, the first secondary path update unit 94 updates the secondary path filter coefficient C^0 so that the virtual error signal e1 (described in detail later) output from the virtual error signal generation unit 83 is minimized.

[0110] The second secondary path update unit 95 updates the secondary path filter coefficient C^1 using an adaptive algorithm such as an LMS algorithm. More specifically, the second secondary path update unit 95 updates the secondary path filter coefficient C^1 so that the virtual error signal e1 output from the virtual error signal generation unit 83 is minimized.

[0111] The noise estimation signal generation unit 82 is configured by a primary path filter H^. A SAN filter is used as the primary path filter H^. The noise estimation signal generation unit 82 includes a first primary path filter unit 101, a second primary path filter unit 102, a first adder 103, a first primary path update unit 104, a second primary path update unit 105, a third primary path filter unit 106, a fourth primary path filter unit 107, and a second adder 108.

[0112] The first primary path filter unit 101 has a primary path filter coefficient H^0. The primary path filter coefficient H^0 forms the real part of the coefficient of the primary path filter H^. The first primary path filter unit 101 performs filtering on the reference cosine wave signal rc output from the reference signal generating device 52.

[0113] The second primary path filter unit 102 has coefficients obtained by inverting the polarity of the primary path filter coefficients H^1. The primary path filter coefficients H^1 form the imaginary parts of the coefficients of the primary path filter H^. The second primary path filter unit 102 performs filtering on the reference sine wave signal rs output from the reference signal generating device 52.

[0114] The first adder 103 adds the reference cosine wave signal rc that has passed through the first primary path filter unit 101 and the reference sine wave signal rs that has passed through the second primary path filter unit 102 to obtain the noise estimation signal d̂ m1 The first adder 103 generates the generated noise estimation signal d̂ m1 to the virtual error signal generator 83 and the estimated signal corrector 68.

[0115] The first primary path update unit 104 updates the primary path filter coefficient H^0 using an adaptive algorithm such as an LMS algorithm. More specifically, the first primary path update unit 104 updates the primary path filter coefficient H^0 so that the virtual error signal e1 output from the virtual error signal generation unit 83 is minimized.

[0116] The second primary path update unit 105 updates the primary path filter coefficient H^1 using an adaptive algorithm such as an LMS algorithm. More specifically, the second primary path update unit 105 updates the primary path filter coefficient H^1 so that the virtual error signal e1 output from the virtual error signal generation unit 83 is minimized.

[0117] The third primary path filter unit 106 has a primary path filter coefficient H 0. The third primary path filter unit 106 performs filtering on the reference sine wave signal rs output from the reference signal generating device 52.

[0118] The fourth primary path filter unit 107 has a primary path filter coefficient H^1. The fourth primary path filter unit 107 performs filtering on the reference cosine wave signal rc output from the reference signal generator 52.

[0119] The second adder 108 adds the reference sine wave signal rs passed through the third primary path filter unit 106 and the reference cosine wave signal rc passed through the fourth primary path filter unit 107 to obtain the noise estimation signal d̂ m2 The second adder 108 generates the generated noise estimation signal d̂ m2 is output to the estimated signal correction unit 68.

[0120] The virtual error signal generating unit 83 includes a first polarity inverting circuit 111, a second polarity inverting circuit 112, and an adder 113.

[0121] The first polarity inversion circuit 111 converts the cancellation estimation signal y^ output from the cancellation estimation signal generation unit 81 into m1 The second polarity inversion circuit 112 inverts the polarity of the noise estimation signal d̂ output from the noise estimation signal generation unit 82. m1 Reverse the polarity of

[0122] The adder 113 outputs the error signal e and the cancellation estimation signal y^ that has passed through the first polarity inversion circuit 111. m1 and the noise estimation signal d^ passed through the second polarity inversion circuit 112. m1 The adder 113 outputs the generated virtual error signal e1 to the canceling estimated signal generator 81 and the noise estimated signal generator 82.

[0123] <Reference signal correction unit 66> The reference signal correction unit 66 of the control device 53 is configured with a secondary path filter C^, similar to the canceling sound estimation signal generation unit 81. When the coefficients C^0 and C^1 of the secondary path filter C^ are updated in the canceling sound estimation signal generation unit 81, the updated coefficients C^0 and C^1 of the secondary path filter C^ are output to the reference signal correction unit 66, and the coefficients C^0 and C^1 of the secondary path filter C^ are updated in the reference signal correction unit 66. The reference signal correction unit 66 outputs the updated coefficients C^0 and C^1 of the secondary path filter C^ to the head position estimation unit 67.

[0124] The reference signal correction unit 66 includes a third secondary path filter unit 121, a fourth secondary path filter unit 122, a first adder 123, a fifth secondary path filter unit 124, a sixth secondary path filter unit 125, and a second adder 126.

[0125] The third secondary path filter unit 121 has a secondary path filter coefficient C 0. The third secondary path filter unit 121 performs filtering on the reference cosine wave signal rc output from the reference signal generating device 52.

[0126] The fourth secondary path filter unit 122 has a coefficient obtained by inverting the polarity of the secondary path filter coefficient C^1. The fourth secondary path filter unit 122 performs filtering on the reference sine wave signal rs output from the reference signal generating device 52.

[0127] The first adder 123 adds the reference cosine wave signal rc that has passed through the third secondary path filter unit 121 and the reference sine wave signal rs that has passed through the fourth secondary path filter unit 122 to obtain the cancellation estimation signal y^ m2 The first adder 123 generates the generated cancellation estimation signal y^. m2 is output to the estimated signal correction unit 68.

[0128] The fifth secondary path filter unit 124 has a secondary path filter coefficient C ^ 0. The fifth secondary path filter unit 124 performs filtering on the reference sine wave signal rs output from the reference signal generating device 52.

[0129] The sixth secondary path filter unit 125 has a secondary path filter coefficient C^1. The sixth secondary path filter unit 125 performs filtering on the reference cosine wave signal rc output from the reference signal generator 52.

[0130] The second adder 126 adds the reference sine wave signal rs that has passed through the fifth secondary path filter unit 124 and the reference cosine wave signal rc that has passed through the sixth secondary path filter unit 125 to obtain the cancellation estimation signal y^ m3 The second adder 126 generates the generated cancellation estimation signal ŷm3 is output to the estimated signal correction unit 68.

[0131] <Head position estimation unit 67> The head position estimation unit 67 of the control device 53 estimates the head position of an occupant present in the vehicle compartment 5 based on the noise frequency f output from the reference signal generation unit 52 and the coefficients C^0 and C^1 of the secondary path filter C^ output from the reference signal correction unit 66. The method of estimating the head position of an occupant by the head position estimation unit 67 is the same as the method of estimating the head position of an occupant by the head position estimation unit 27 according to the first embodiment, and therefore a description thereof will be omitted.

[0132] <Estimated signal correction unit 68> The estimated signal correction unit 68 of the control device 53 includes a database unit 131, a cancellation correction unit 132, and a noise correction unit 133. The configuration of the database unit 131 is similar to the configuration of the database unit 41 according to the first embodiment, and therefore a description thereof will be omitted.

[0133] The cancellation correction unit 132 uses a cancellation correction filter C^ me It is composed of the cancellation correction filter C^ me The cancellation correction unit 132 includes a first cancellation correction filter unit 141, a second cancellation correction filter unit 142, a first adder 143, a third cancellation correction filter unit 144, a fourth cancellation correction filter unit 145, and a second adder 146.

[0134] The first cancellation correction filter unit 141 calculates the cancellation correction filter coefficient C^ me 0. Cancellation correction filter coefficient C^ me 0 is the cancellation correction filter C^ me The first cancellation correction filter unit 141 forms the real part of the coefficient of the cancellation estimation signal y^ output from the reference signal correction unit 66. m2 A filter process is performed on the

[0135] The second cancellation correction filter unit 142 calculates the cancellation correction filter coefficient C^ me 1. Cancellation correction filter coefficient C^me 1 is the cancellation correction filter C^ me The second cancellation correction filter unit 142 forms the imaginary part of the coefficient of the cancellation estimation signal y^ output from the reference signal correction unit 66. m3 A filter process is performed on the

[0136] The first adder 143 outputs the cancellation estimation signal y^ that has passed through the first cancellation correction filter unit 141. m2 and the cancellation estimation signal y^ passed through the second cancellation correction filter unit 142 m3 By adding and, the cancellation estimated signal y^ e1 The first adder 143 generates the generated cancellation estimation signal y^. e1 to the control filter update unit 69.

[0137] The third cancellation correction filter unit 144 calculates the cancellation correction filter coefficient C^ me 0. The third cancellation correction filter unit 144 is configured to convert the cancellation estimation signal y^ output from the reference signal correction unit 66 into m3 A filter process is performed on the

[0138] The fourth cancellation correction filter unit 145 calculates the cancellation correction filter coefficient C^ me The fourth cancellation correction filter unit 145 receives the cancellation estimation signal y^ output from the reference signal correction unit 66. m2 A filter process is performed on the

[0139] The second adder 146 outputs the cancellation estimation signal y^ that has passed through the third cancellation correction filter unit 144. m3 and the cancellation estimation signal y^ passed through the fourth cancellation correction filter unit 145 m2 By adding and, the cancellation estimated signal y^ e2 The second adder 146 generates the generated cancellation estimation signal ŷ e2 to the control filter update unit 69.

[0140] The noise correction unit 133 uses a noise correction filter H^ me The noise correction filter H^ meThe noise compensation unit 133 includes a first noise compensation filter unit 151, a second noise compensation filter unit 152, and an adder 153.

[0141] The first noise correction filter unit 151 calculates the noise correction filter coefficient H^ me 0. Noise correction filter coefficient H^ me 0 is the noise correction filter H^ me The first noise correction filter unit 151 converts the noise estimation signal d̂ output from the noise estimation signal generation unit 82 into the real part of the coefficient of m1 A filter process is performed on the

[0142] The second noise correction filter unit 152 calculates the noise correction filter coefficient H^ me 1. Noise correction filter coefficient H^ me 1 is the noise correction filter H^ me The second noise correction filter unit 152 converts the noise estimation signal d̂ output from the noise estimation signal generation unit 82 into the imaginary part of the coefficient of m2 A filter process is performed on the

[0143] The adder 153 outputs the noise estimation signal d^ that has passed through the first noise compensation filter unit 151. m1 and the noise estimation signal d^ passed through the second noise correction filter unit 152 m2 By adding and, the noise estimation signal d^ e The adder 153 generates the generated noise estimation signal d̂ e to the control filter update unit 69.

[0144] <Control filter update unit 69> The control filter update unit 69 of the control device 53 is configured by a control filter W, similar to the control signal output unit 62. The control filter update unit 69 includes a fifth control filter unit 161, a sixth control filter unit 162, a first adder 163, a second adder 164, a first control update unit 165, and a second control update unit 166.

[0145] The fifth control filter unit 161 has a control filter coefficient W0. The fifth control filter unit 161 converts the cancellation estimated signal y^ output from the estimated signal correction unit 68 into a e1 A filter process is performed on the

[0146] The sixth control filter 162 has a control filter coefficient W1. The sixth control filter 162 calculates the cancellation estimated signal ŷ output from the estimated signal correction unit 68. e2 A filter process is performed on the

[0147] The first adder 163 outputs the cancellation estimation signal y^ that has passed through the fifth control filter unit 161. e1 and the cancellation estimated signal y^ passed through the sixth control filter unit 162. e2 By adding and, the cancellation estimated signal y^ e The first adder 163 generates the generated cancellation estimation signal y^. e is output to the second adder 164.

[0148] The second adder 164 outputs the cancellation estimation signal ŷ e and noise estimation signal d^ e By adding and, the virtual error signal e e The second adder 164 generates the generated virtual error signal e e to the first control update unit 165 and the second control update unit 166.

[0149] The first control update unit 165 updates the control filter coefficient W0 using an adaptive algorithm such as an LMS algorithm. More specifically, the first control update unit 165 updates the virtual error signal e output from the second adder 164. e The control filter coefficient W0 is updated so that is minimized.

[0150] The second control update unit 166 updates the control filter coefficient W1 using an adaptive algorithm such as an LMS algorithm. More specifically, the second control update unit 166 updates the virtual error signal e output from the second adder 164. e The control filter coefficient W1 is updated so that is minimized.

[0151] When the coefficients W0 and W1 of the control filter W are updated in the control filter update unit 69, the updated coefficients W0 and W1 of the control filter W are output to the control signal output unit 62, and the coefficients W0 and W1 of the control filter W are updated in the control signal output unit 62.

[0152] <Effects of the second embodiment> In the control device 53 according to the second embodiment, SAN filters are used as the control filter W, the primary path filter H^, and the secondary path filter C^. Therefore, the amount of calculations performed by the control device 53 can be reduced compared to when FIR filters are used as these filters. This allows the noise reduction device 51 to be implemented using an inexpensive ECU.

[0153] Although the description of the specific embodiment has been completed above, the present invention is not limited to the above embodiment and its modifications, and can be modified in a wide range of ways. [Explanation of symbols]

[0154] (First embodiment) 1: Vehicle (an example of a moving object) 5: Vehicle cabin (an example of the interior space of a moving object) 11: Active noise reduction device 12: Vibration sensor (an example of a reference signal generator) 13: Speaker (an example of a noise canceling device) 14: Error microphone (an example of an error detection device) 15: Control device C^: Secondary path filter (estimated transfer characteristic of cancellation) C^ me : Cancellation correction filter C e : Transmission characteristics of noise cancellation (from the speaker to the passenger's head position) C m : Transfer characteristics of noise cancellation (from speaker to error microphone) H^: Primary path filter (estimated value of the transmission characteristics of road noise) H^ me:Noise compensation filter H e : Road noise transmission characteristics (from the noise source to the passenger's head position) H m : Road noise transmission characteristics (from noise source to error microphone) W: Control filter d: Road noise (an example of noise) d^ m : Noise estimation signal (position of error microphone) d^ e : Noise estimation signal (occupant head position) e: error signal x :Reference signal y :Cancellation sound y^ m2 : Cancellation estimated signal (position of error microphone) y^ e : Sound cancellation estimation signal (occupant head position) (Second embodiment) 51: Active noise reduction device 52:Reference signal generation device 53: Control device d: Drivetrain noise (example of noise)

Claims

1. An active noise reduction device for reducing noise in an interior space of a moving body, comprising: a reference signal generator for generating a reference signal corresponding to the noise; a canceling sound generating device that generates a canceling sound to cancel the noise; an error detection device that detects an error between the noise and the cancellation sound and generates an error signal corresponding to the error; a control device that controls the cancellation generating device based on the reference signal and the error signal, The control device updating an estimate of the acoustic properties of the interior space based on the reference signal and the error signal; estimating a head position of an occupant present in the interior space based on the updated estimated value of the acoustic characteristic; An active noise reduction device that updates a control filter for controlling the noise canceling device based on the estimated head position of the occupant.

2. The control device generating an estimated signal of the noise at the head position of the occupant and an estimated signal of the cancellation sound at the head position of the occupant based on the estimated head position of the occupant; 2. The active noise reduction device according to claim 1, wherein the control filter is updated so as to minimize an error between the estimated signal of the noise at the position of the occupant's head and the estimated signal of the cancellation at the position of the occupant's head.

3. The control device updating an estimate of a transfer characteristic of the noise from the noise source to the error detection device and an estimate of a transfer characteristic of the cancellation from the cancellation generation device to the error detection device based on the reference signal and the error signal; generating an estimated signal of the noise at the position of the error detection device based on the updated estimated value of the transfer characteristic of the noise from the noise source to the error detection device; correcting the estimated signal of the noise at the position of the error detection device using a predetermined noise correction filter to generate an estimated signal of the noise at the position of the occupant's head; generating an estimated signal of the cancellation at the position of the error detection device based on the updated estimated value of the transfer characteristic of the cancellation from the cancellation generation device to the error detection device; 3. The active noise reduction device according to claim 2, wherein the estimated signal of the noise cancellation at the position of the error detection device is corrected using a predetermined noise cancellation correction filter, thereby generating the estimated signal of the noise cancellation at the position of the occupant's head.

4. the noise cancellation correction filter is defined as a ratio between a transfer characteristic of the noise cancellation from the noise cancellation generating device to the head position of the occupant and a transfer characteristic of the noise cancellation from the noise cancellation generating device to the error detecting device; 4. The active noise reduction device according to claim 3, wherein the noise correction filter is defined as a ratio between a transfer characteristic of the noise from the noise source to the head position of the occupant and a transfer characteristic of the noise from the noise source to the error detection device.

5. 5. The active noise reduction device according to claim 3, wherein the control device stores, in table form, a relationship between the head position of the occupant and the coefficient of the noise cancellation correction filter, and a relationship between the head position of the occupant and the coefficient of the noise correction filter.

6. 6. An active noise reduction device according to claim 1, wherein the control device has a neural network that has learned the relationship between the estimated values ​​of the acoustic characteristics and the head position of the occupant, and estimates the head position of the occupant by inputting the estimated values ​​of the acoustic characteristics into the neural network.

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