CN108900943A - A kind of scene adaptive active denoising method and earphone - Google Patents
A kind of scene adaptive active denoising method and earphone Download PDFInfo
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- CN108900943A CN108900943A CN201810818230.7A CN201810818230A CN108900943A CN 108900943 A CN108900943 A CN 108900943A CN 201810818230 A CN201810818230 A CN 201810818230A CN 108900943 A CN108900943 A CN 108900943A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R1/00—Details of transducers, loudspeakers or microphones
- H04R1/10—Earpieces; Attachments therefor ; Earphones; Monophonic headphones
- H04R1/1091—Details not provided for in groups H04R1/1008 - H04R1/1083
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R2460/00—Details of hearing devices, i.e. of ear- or headphones covered by H04R1/10 or H04R5/033 but not provided for in any of their subgroups, or of hearing aids covered by H04R25/00 but not provided for in any of its subgroups
- H04R2460/01—Hearing devices using active noise cancellation
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Abstract
The invention discloses a kind of scene adaptive active denoising methods, including：It picks up ambient noise and is converted into primary noise electric signal；Noise Identification module determines noise type；EQ filter parameter is selected to be loaded into active noise reduction module from filter bank；Active noise reduction module carries out adaptive-filtering to primary noise electric signal, and generates the de-noising electric signal of excitation loudspeaker；After loudspeaker receives de-noising electric signal, de-noising sound wave is generated, and the audio signal after secondary counteracting is issued, the de-noising sound wave is identical as the primary noise electric signal spectrum distribution, acoustic pressure size is identical and opposite in phase.A kind of scene adaptive active noise reduction earphone, including microphone, loudspeaker and active noise reduction module.Noise cancelling headphone can adjust EQ filter parameter in FXLMS noise reduction algorithm, offset the noise that passive noise reduction fails to remove according to the difference of noise energy concentrated area in noise scenarios, export the influence of audio to earphone so as to improve the external noise of scene locating for human ear.
Description
Technical field
The present invention relates to noise cancelling headphone fields, are a kind of scene adaptive active denoising method and earphone specifically.
Background technique
With people's traffic trip increasingly frequently, ambient noise has seriously affected the quality of trip.Traditional noise reduction
Means mainly have sound insulation, material absorption etc., but are limited to the factors such as arrangement space, material property and cost, and conventional method is to height
Frequency noise remove effect is preferable, but not satisfactory to low-frequency noise effect.Therefore, active noise reduction start from civil aviaton's military field by
Gradually enter into popular life.It is different from traditional noise reduction means, active noise controlling (ANC) be by the principle of sound wave interference cancellation,
Original noise is offset using secondary sound source sounding to realize that noise is eliminated.Active noise reduction can be according to environmental change adjust automatically
Noise reduction strategies, and it is capable of the noise of the processing special frequency channel of selectivity, to be obviously improved noise reduction quality.Currently, actively
The most famous control algolithm that noise cancelling headphone uses is the Filtered-X LMS algorithm (FXLMS) proposed by Widrow.The algorithm characteristic is
A filter identical with secondary channel transmission characteristic is placed in reference signal channel to carry out LMS algorithm weight update, with solution
Certainly introduce secondary channel bring systematic jitters problem.But based on the noise cancelling headphone of FXLMS algorithm design, in use process
The problems such as it is slow that there are convergence rates, only good to narrow-band noise effect, and undesirable to broadband noise control effect, therefore very much
Preferable noise reduction effect is unable to get under scene.
Summary of the invention
The purpose of the present invention is to provide a kind of scene adaptive active denoising method and earphones, for solving the prior art
It is middle slow using FXLMS algorithm progress active noise reduction convergence rate, and to the problem of broadband noise control effect difference.
The present invention is solved the above problems by following technical proposals：
A kind of scene adaptive active denoising method, including：
Step S1：Microphone picks up ambient noise and is converted into primary noise electric signal；
Step S2：Noise Identification module extracts noise energy collection Mid Frequency and frequency distribution according to primary noise electric signal
Characteristic, and matched with preset noise pattern in noise pattern library, determine noise type；
Step S3：EQ filter parameter is selected to be loaded into active noise reduction module, the EQ filter ginseng from filter bank
Number includes centre frequency f, bandwidth Q and amount of gain GAIN；
Step S4：Active noise reduction module carries out adaptive-filtering to primary noise electric signal, and generates excitation loudspeaker
De-noising electric signal；
Step S5：After loudspeaker receives de-noising electric signal, de-noising sound wave is generated, and by the audio signal after secondary counteracting
It issues, the de-noising sound wave is identical as the primary noise electric signal spectrum distribution, acoustic pressure size is identical and opposite in phase.
Principle：
Microphone is converted into electric signal after being picked up to ambient noise at earphone；In Noise Identification module, extraction is made an uproar
Acoustical signal energy collection Mid Frequency and frequency distribution feature, and the noise characteristic extracted is compared in default noise pattern library
It is right, it obtains and the immediate noise pattern classification of this scene；According to the type of noise, corresponding EQ is selected in noise pattern library
Filter parameter (centre frequency (f), bandwidth (Q) and amount of gain (GAIN)), and be loaded into active noise reduction module EQ filter
In wave device, active noise module loading EQ filter parameter, active noise reduction module is on the basis of Filtered-X LMS algorithm (FXLMS)
On, EQ filter is introduced, is by Noise Identification module, to noise signal energy collection Mid Frequency, frequency due to EQ filter parameter
After rate distribution characteristics is analyzed, be compared in noise pattern library after determine, therefore, the introducing of EQ filter enhances
Processing and generation de-noising electric signal to noise collection Mid Frequency, and loudspeaker is motivated to generate de-noising sound wave and noise cancellation, and
The audio signal after secondary counteracting is issued by loudspeaker.Therefore, either narrow-band noise or broadband noise, can lead to
It crosses Noise Identification module and determines type, and then load corresponding EQ filter parameter, obtain the noise reduction capability under the scene greatly
Amplitude is promoted, and the noise for entering human ear can be offset according to scene, improves locating noise circumstance, allows user in noisy environment
In can also obtain lossless, high-fidelity audio.
Further, the step S4 is specifically included：
Step S41：EQ filter in active noise reduction module loads the EQ filter parameter；
Step S42：Secondary channel is introduced, the secondary channel includes sequentially connected inverse filter Inv_S (z), adaptive
Filter W (z) and secondary channel system S (z) are answered, the inverse filter Inv_S (z) is for offsetting secondary channel interference；
Step S43：Signal is generated by noise generator to train secondary channel, to obtain secondary channel transmission function
Identification result
Step S44：By the secondary channel transmission function result of the identificationIt substitutes into inverse filter Inv_S (z), then defeated
Enter sef-adapting filter W (z) and carries out the processing of LMS adaptive-filtering；
Step S45：Error-filter in active noise reduction module generates the de-noising electric signal of excitation loudspeaker.
Principle：
For better noise reduction, active noise reduction module includes main channel and secondary channel, and signal X (n) is respectively by main logical
Error originated from input filter after sound wave counteracting is carried out after road P (z) and secondary channel, signal X (n) signal after main channel P (z) is
D (n), signal X (n) are signal after preposition inverse filter Inv_S (z) on secondary channelSignalThrough
Crossing sef-adapting filter W (z) afterwards is signal y (n), and signal y (n) exports de-noising electric signal s by secondary channel system S (z)
(n), signal e (n) the error originated from input sensor after de-noising electric signal s (n) and signal d (n) sound wave are offset；SignalBy secondary
Grade channel transfer function identification resultIt is afterwards signalSignalSignal q (n) after EQ filter with
LMS is carried out in signal e1 (n) input adaptive filter W (z) of the signal e (n) after another EQ filter adaptively to filter
Wave.
Further, the step S43 is specifically included：In initialization, pumping signal is generated by external control circuit, it should
Signal by secondary channel and recognizes it, then picks up the signal by error pick-up, uses after sending circuit system back to
LMS algorithm calculates the transmission function of secondary channel, to obtain the estimated value of the channel transfer function S (n)
Principle：It first has to exclusion introducing secondary channel to interfere to noise reduction bring, therefore first to obtain secondary channel transmitting
The estimated value of functionSecondary channel interference is offset in the noise reduction module using preposition inverse filter Inv_S (z).Estimate
EvaluationBe by external circuit generate pumping signal, after secondary channel send back to circuit system with LMS algorithm into
What row was calculated.
Further, the step S44 is specifically included：
A, the signal e (n) that error pick-up receives is solved, specially：
The input signal X (n) of active noise reduction module can reach error through main channel P (z) and two paths of secondary channel and pass
Sensor, secondary channel output are expressed as：If assuming at this time adaptive
It answers filter W (z) weight coefficient to remain unchanged in a bit of time L, enables r (n)=x (n) * s (n), can be obtainedThe signal e (n) that error pick-up receives at this time is main channel P
(z) and the sum of the output signal of secondary channel, i.e.,：
E (n)=d (n)+s (n)=d (n)+rT(n) W (n), wherein d (n) is signal X (n) after main channel P (z)
Output signal, W (n) are the transmission function of sef-adapting filter；
B, the best weight coefficient of sef-adapting filter is solved, specially：
Objective function of the least-mean-square-error criterion as signal e (n) is selected, is enabled P=E [d (n) r (n)], R=E [r (n) rT
(n)],
(1) when steady input signal X (n), then the Quadratic Function Optimization of weight vector
Since matrix R is that positive definite is symmetrical, show J (n) existence anduniquess minimum value, thus can calculate best weight coefficient arrow
Amount, calculates to obtain W0=-R-1P；
(2) it when input signal X (n) is unstable, is solved using recursion, i.e. the output recursion of sef-adapting filter W (z)
Relationship is：W (n+1)=W (n)-μ Δ W (n), wherein μ is the convergence step-length that automatic adjusument introduces, using single error signal
Estimation of the squared gradient as mean square error gradient：Obtain sef-adapting filter
Weight coefficient vector more new formula is：W (n+1)=- 2 μ e (n) r (n) of W (n).
The table of the main channel by loudspeaker, the signal e (n) after the sound wave counteracting after secondary channel is given in step A
It is related with sef-adapting filter W (z), main channel P (z) and secondary channel system S (z) up to formula, whereinIn, variable l, the i.e. L of small letter.Signal e (n) can be considered random change
Amount further solves the best weight coefficient of sef-adapting filter W (z), and according to input signal, two ways can be taken to be counted
Calculate optimum weight vector.
Further, there are two the EQ filter is set, one of EQ filter is for receiving secondary channel transmitting letter
Number identification resultOutput signal is simultaneously filtered rear input adaptive filter W (z), another EQ filter is for receiving
Error pick-up received signal e (n) is simultaneously filtered rear input adaptive filter W (z).
It can be seen that the signal of different frequency distribution character from second of calculation for calculating optimum weight vector,
Its noise energy is also concentrated in different frequency range, thus in order to enhance active noise reduction module to the noise reduction effect of a certain scene, master
Dynamic noise reduction module introduces processing of the enhancing of EQ filter two to noise collection Mid Frequency.After increasing EQ filter, sef-adapting filter W
(z) bigger weight can be occupied by frequency range being selected in weight coefficient recurrence calculation, finally allow noise reduction of the noise reduction module under the scene
Ability is improved significantly.
Further, there are three the EQ filter is set, one of EQ filter is for receiving secondary channel transmitting letter
Number identification resultOutput signal is simultaneously filtered rear input adaptive filter W (z), other two EQ filter is used respectively
It is filtered in by the output signal of main channel P (z), secondary channel system S (z), filtered signal carries out sound wave counteracting and inputs
Error-filter and sef-adapting filter W (z).
EQ filter filtering first is carried out to main channel signal and secondary channel signal before entering error pick-up, this
When, the signal d'(n of main channel error originated from input sensor)=d (n) * eq (n), the signal y' of secondary channel error originated from input sensor
(n)=s (n) * eq (n), it can be seen that EQ filter, which is equivalent to, has different gains to each frequency range of S (n), and selectes frequency
Duan Zengyi is bigger, therefore the d'(n exported) in select frequency range amplitude bigger, and then allow selected frequency range pair into sef-adapting filter
The adjusting weight of sef-adapting filter increases, and so that noise energy collection Mid Frequency is occupied bigger weight in weight coefficient update, most
Noise reduction capability of the noise reduction module under the scene is allowed to be improved significantly eventually.
A kind of scene adaptive active noise reduction earphone, including microphone and loudspeaker, the microphone are sequentially connected preposition
Amplifying circuit, Noise Identification module, active noise reduction module and power amplification circuit, the power amplification circuit and the loudspeaker
Connection, wherein：
Microphone, for picking up ambient noise and being converted to primary noise electric signal；
Noise Identification module, for extracting noise immune collection Mid Frequency and frequency distribution from the primary noise electric signal
Characteristic, and matched in noise pattern library with preset noise pattern, it determines noise type, is then selected in filter bank
It selects corresponding EQ filter parameter and is loaded into active noise reduction module；
Active noise reduction module carries out the processing of the improvement FXLMS adaptive-filtering based on EQ filter to primary noise signal,
The de-noising electric signal of excitation loudspeaker is generated, and is exported to power amplification circuit；
Loudspeaker generates de-noising sound wave, the de-noising sound wave and primary noise signal spectrum after receiving de-noising electric signal
Distribution, acoustic pressure size are identical, opposite in phase, and loudspeaker exports the audio signal after offset noise.
Active noise reduction module makes sub-loudspeaker generate the de-noising sound wave opposite with main loudspeaker amplitude same phase, reaches
Active noise reduction.
Compared with prior art, the present invention having the following advantages that and beneficial effect：
(1) noise cancelling headphone can adjust FXLMS noise reduction algorithm according to the difference of noise energy concentrated area in noise scenarios
Middle EQ filter parameter offsets the noise that passive noise reduction fails to remove, so as to improve scene locating for human ear external noise to ear
The influence of machine output audio.
(2) present invention improves the FXLMS algorithm of type using EQ filter, can be had according to scene difference, signal
Different frequency distribution characteristics, noise energy are also concentrated in different frequency range, in order to enhance active noise reduction module to special scenes
Noise reduction effect, the noise reduction module introduces EQ filter to enhance to the processing of noise collection Mid Frequency, can be under many scenes
It realizes to broadband noise filter effect.
Detailed description of the invention
Fig. 1 is Headphone structure block diagram of the invention；
Fig. 2 is noise reduction flow chart of the invention；
Fig. 3 is the schematic diagram of the third specific embodiment of the invention；
Fig. 4 is the schematic diagram of specific embodiment in the present invention the 4th.
Specific embodiment
Firstly, being given to the signal being referred to herein before introducing specific embodiments of the present invention and being explained as follows table：
The present invention is described in further detail below with reference to embodiment, embodiments of the present invention are not limited thereto.
Embodiment 1：
In conjunction with shown in attached drawing 1 and Fig. 2, a kind of scene adaptive active denoising method, including：
Step S1：Microphone picks up ambient noise and is converted into primary noise electric signal；
Step S2：Noise Identification module extracts noise energy collection Mid Frequency and frequency distribution according to primary noise electric signal
Characteristic, and matched with preset noise pattern in noise pattern library, determine noise type；
Step S3：EQ filter parameter is selected to be loaded into active noise reduction module, the EQ filter ginseng from filter bank
Number includes centre frequency f, bandwidth Q and amount of gain GAIN；
Step S4：Active noise reduction module carries out adaptive-filtering to primary noise electric signal, and generates excitation loudspeaker
De-noising electric signal；
It specifically includes：Step S41：EQ filter in active noise reduction module loads the EQ filter parameter；
Step S42：Secondary channel is introduced, the secondary channel includes sequentially connected inverse filter Inv_S (z), adaptive
Filter W (z) and secondary channel system S (z) are answered, the inverse filter Inv_S (z) is for offsetting secondary channel interference；
Step S43：Signal is generated by noise generator to train secondary channel, to obtain secondary channel transmission function
Identification result
Step S44：By the secondary channel transmission function result of the identificationIt substitutes into inverse filter Inv_S (z), then defeated
Enter sef-adapting filter W (z) and carries out the processing of LMS adaptive-filtering；
Step S45：Error-filter in active noise reduction module generates the de-noising electric signal of excitation loudspeaker；
Step S5：After loudspeaker receives de-noising electric signal, de-noising sound wave is generated, and by the audio signal after secondary counteracting
It issues, the de-noising sound wave is identical as the primary noise electric signal spectrum distribution, acoustic pressure size is identical and opposite in phase.
Principle：
Microphone is converted into electric signal after being picked up to ambient noise at earphone；In Noise Identification module, extraction is made an uproar
Acoustical signal energy collection Mid Frequency and frequency distribution feature, and the noise characteristic extracted is compared in default noise pattern library
It is right, it obtains and the immediate noise pattern classification of this scene；According to the type of noise, corresponding EQ is selected in noise pattern library
Filter parameter (centre frequency (f), bandwidth (Q) and amount of gain (GAIN)), and be loaded into active noise reduction module EQ filter
In wave device.Active noise reduction module includes main channel and secondary channel, and signal X (n) passes through main channel P (z) and secondary channel respectively
Error originated from input filter after progress sound wave counteracting afterwards, signal X (n) signal after main channel P (z) is d (n), and signal X (n) exists
It is signal after preposition inverse filter Inv_S (z) on secondary channelSignalBy sef-adapting filter W
It (z) is afterwards signal y (n), signal y (n) is by secondary channel system S (z) output de-noising electric signal s (n), de-noising electric signal s (n)
Signal e (n) error originated from input sensor after being offset with signal d (n) sound wave；SignalIt is recognized by secondary channel transmission function
As a resultIt is afterwards signalSignalSignal q (n) and signal e (n) after EQ filter pass through another EQ
LMS adaptive-filtering is carried out in signal e1 (n) input adaptive filter W (z) after filter.EQ filter, which loads noise, to be known
The filter parameter selected in other module is to be concentrated by Noise Identification module to noise signal energy due to EQ filter parameter
After frequency range, frequency distribution feature are analyzed, be compared in noise pattern library after determine, therefore, EQ filter draws
Enter the processing enhanced to noise collection Mid Frequency and generate de-noising electric signal, and loudspeaker is motivated to generate de-noising sound wave and noise
It offsets, and is issued the audio signal after secondary counteracting by loudspeaker.Therefore, either narrow-band noise or broadband noise,
Type can be determined by Noise Identification module, and then loads corresponding EQ filter parameter, make the noise reduction capability under the scene
It is improved significantly, the noise for entering human ear can be offset according to scene, improves locating noise circumstance, allows user in noise
Also lossless, high-fidelity audio can be obtained in heterocycle border.
Embodiment 2：
On the basis of embodiment 1, the step S44 is specifically included：
A, the signal e (n) that error pick-up receives is solved, specially：
The input signal X (n) of active noise reduction module can reach error through main channel P (z) and two paths of secondary channel and pass
Sensor, secondary channel output are expressed as：If assuming at this time adaptive
It answers filter W (z) weight coefficient to remain unchanged in a bit of time L, enables r (n)=x (n) * s (n), can be obtainedThe signal e (n) that error pick-up receives at this time is main channel P
(z) and the sum of the output signal of secondary channel, i.e.,：
E (n)=d (n)+s (n)=d (n)+rT(n) W (n), wherein d (n) is signal X (n) after main channel P (z)
Output signal, W (n) are the transmission function of sef-adapting filter；
B, the best weight coefficient of sef-adapting filter is solved, specially：
Objective function of the least-mean-square-error criterion as signal e (n) is selected, is enabled P=E [d (n) r (n)], R=E [r (n) rT
(n)],
(1) when steady input signal X (n), then the Quadratic Function Optimization of weight vector
Since matrix R is that positive definite is symmetrical, show J (n) existence anduniquess minimum value, thus can calculate best weight coefficient arrow
Amount, calculates to obtain W0=-R-1P；
(2) it when input signal X (n) is unstable, is solved using recursion, i.e. the output recursion of sef-adapting filter W (z)
Relationship is：W (n+1)=W (n)-μ Δ W (n), wherein μ is the convergence step-length that automatic adjusument introduces, using single error signal
Estimation of the squared gradient as mean square error gradient：Obtain sef-adapting filter
Weight coefficient vector more new formula is：W (n+1)=- 2 μ e (n) r (n) of W (n).
The table of the main channel by loudspeaker, the signal e (n) after the sound wave counteracting after secondary channel is given in step A
It is related with sef-adapting filter W (z), main channel P (z) and secondary channel system S (z) up to formula.Signal e (n) can be considered with
Machine variable further solves the best weight coefficient of sef-adapting filter W (z), and according to input signal, can take two ways into
Row calculates optimum weight vector.
Embodiment 3：
On the basis of embodiment 2, in conjunction with shown in attached drawing 3, there are two the EQ filter is set, one of EQ filter
For receiving secondary channel transmission function identification resultOutput signal is simultaneously filtered rear input adaptive filter W (z),
Another EQ filter is for receiving error pick-up received signal e (n) and being filtered rear input adaptive filter W
(z)。
It can be seen that the signal of different frequency distribution character from second of calculation for calculating optimum weight vector,
Its noise energy is also concentrated in different frequency range, thus in order to enhance active noise reduction module to the noise reduction effect of a certain scene, master
Dynamic noise reduction module introduces processing of the enhancing of EQ filter two to noise collection Mid Frequency.After increasing EQ filter, sef-adapting filter W
(z) bigger weight can be occupied by frequency range being selected in weight coefficient recurrence calculation, finally allow noise reduction of the noise reduction module under the scene
Ability is improved significantly.
Embodiment 4：
On the basis of embodiment 2, in conjunction with shown in attached drawing 4, there are three the EQ filter is set, one of EQ filter
For receiving secondary channel transmission function identification resultOutput signal is simultaneously filtered rear input adaptive filter W (z),
Other two EQ filter is respectively used to filter the output signal of main channel P (z), secondary channel system S (z), filtered
Signal carries out sound wave and offsets simultaneously error originated from input filter and sef-adapting filter W (z).
EQ filter filtering first is carried out to main channel signal and secondary channel signal before entering error pick-up, this
When, the signal d'(n of main channel error originated from input sensor)=d (n) * eq (n), the signal y' of secondary channel error originated from input sensor
(n)=s (n) * eq (n) equally makes noise energy collection Mid Frequency occupy bigger weight in weight coefficient update, finally allows described
Noise reduction capability of the noise reduction module under the scene is improved significantly.
Embodiment 5：
As shown in connection with fig. 1, a kind of scene adaptive active noise reduction earphone, including microphone and loudspeaker, the microphone
It is sequentially connected pre-amplification circuit, Noise Identification module, active noise reduction module and power amplification circuit, the power amplification circuit
It is connect with the loudspeaker, wherein：
Microphone, for picking up ambient noise and being converted to primary noise electric signal；
Noise Identification module, for extracting noise immune collection Mid Frequency and frequency distribution from the primary noise electric signal
Characteristic, and matched in noise pattern library with preset noise pattern, it determines noise type, is then selected in filter bank
It selects corresponding EQ filter parameter and is loaded into active noise reduction module；
Active noise reduction module carries out the processing of the improvement FXLMS adaptive-filtering based on EQ filter to primary noise signal,
The de-noising electric signal of excitation loudspeaker is generated, and is exported to power amplification circuit；
Loudspeaker generates de-noising sound wave, the de-noising sound wave and primary noise signal spectrum after receiving de-noising electric signal
Distribution, acoustic pressure size are identical, opposite in phase, and loudspeaker exports the audio signal after offset noise.
Active noise reduction module makes sub-loudspeaker generate the de-noising sound wave opposite with main loudspeaker amplitude same phase, reaches
Active noise reduction.
Although reference be made herein to invention has been described for explanatory embodiment of the invention, and above-described embodiment is only this hair
Bright preferable embodiment, embodiment of the present invention are not limited by the above embodiments, it should be appreciated that those skilled in the art
Member can be designed that a lot of other modification and implementations, these modifications and implementations will fall in principle disclosed in the present application
Within scope and spirit.
Claims (7)
1. a kind of scene adaptive active denoising method, which is characterized in that including：
Step S1：Microphone picks up ambient noise and is converted into primary noise electric signal；
Step S2：Noise Identification module extracts noise energy collection Mid Frequency according to primary noise electric signal and frequency distribution is special
Property, and matched with preset noise pattern in noise pattern library, determine noise type；
Step S3：EQ filter parameter is selected to be loaded into active noise reduction module, the EQ filter parameter packet from filter bank
Include centre frequency f, bandwidth Q and amount of gain GAIN；
Step S4：Active noise reduction module carries out adaptive-filtering to primary noise electric signal, and generates the de-noising of excitation loudspeaker
Electric signal；
Step S5：After loudspeaker receives de-noising electric signal, de-noising sound wave is generated, and the audio signal after secondary counteracting is sent out
Out, the de-noising sound wave is identical as the primary noise electric signal spectrum distribution, acoustic pressure size is identical and opposite in phase.
2. a kind of scene adaptive active denoising method according to claim 1, which is characterized in that the step S4 is specific
Including：
Step S41：EQ filter in active noise reduction module loads the EQ filter parameter；
Step S42：Secondary channel is introduced, the secondary channel includes sequentially connected inverse filter Inv_S (z), adaptive filter
Wave device W (z) and secondary channel system S (z), the inverse filter Inv_S (z) is for offsetting secondary channel interference；
Step S43：Signal is generated to train secondary channel by noise generator, to obtain the identification of secondary channel transmission function
As a result
Step S44：By the secondary channel transmission function result of the identificationIt substitutes into inverse filter Inv_S (z), then inputs certainly
Adaptive filter W (z) carries out the processing of LMS adaptive-filtering；
Step S45：Error-filter in active noise reduction module generates the de-noising electric signal of excitation loudspeaker.
3. a kind of scene adaptive active denoising method according to claim 2, which is characterized in that the step S43 tool
Body includes：In initialization, pumping signal is generated by external control circuit, which by secondary channel and distinguishes it
Know, the signal then picked up by error pick-up, send back to after circuit system with LMS algorithm to the transmission function of secondary channel into
Row calculates, to obtain the estimated value of the channel transfer function S (n)
4. a kind of scene adaptive active denoising method according to claim 3, which is characterized in that the step S44 tool
Body includes：
A, the signal e (n) that error pick-up receives is solved, specially：
The input signal X (n) of active noise reduction module can reach error pick-up through main channel P (z) and two paths of secondary channel,
Secondary channel output is expressed as：If assuming adaptive-filtering at this time
Device W (z) weight coefficient remains unchanged in a bit of time L, enables r (n)=x (n) * s (n), can be obtainedThe signal e (n) that error pick-up receives at this time is main channel P
(z) and the sum of the output signal of secondary channel, i.e. e (n)=d (n)+s (n)=d (n)+rT(n) W (n), wherein d (n) is signal X
(n) output signal after main channel P (z), W (n) are the transmission function of sef-adapting filter；
B, the best weight coefficient of sef-adapting filter is solved, specially：
Objective function of the least-mean-square-error criterion as signal e (n) is selected, is enabled P=E [d (n) r (n)], R=E [r (n) rT(n)],
(1) when steady input signal X (n), then the Quadratic Function Optimization of weight vector
J (n)=E [e2(n)]=E [d2 (n)]+2E [d (n) rT(n)]W+WTE[r(n)rT(n)] W=E [d2(n)]+2PTW+WTBy
It is that positive definite is symmetrical in matrix R, shows J (n) existence anduniquess minimum value, thus can calculate optimum weight vector, calculate to obtain W0
=-R-1P；
(2) it when input signal X (n) is unstable, is solved using recursion, i.e. the output recurrence relation of sef-adapting filter W (z)
For：W (n+1)=W (n)-μ Δ W (n), wherein μ is the convergence step-length that automatic adjusument introduces, using the flat of single error signal
Estimation of the square gradient as mean square error gradient：Obtain sef-adapting filter power system
Counting vector more new formula is：W (n+1)=- 2 μ e (n) r (n) of W (n).
5. a kind of scene adaptive active denoising method according to claim 4, which is characterized in that the EQ filter is set
There are two, one of EQ filter is for receiving secondary channel transmission function identification resultOutput signal is simultaneously filtered
Input adaptive filter W (z) afterwards, another EQ filter is for receiving error pick-up received signal e (n) and being filtered
Input adaptive filter W (z) after wave.
6. a kind of scene adaptive active denoising method according to claim 4, which is characterized in that the EQ filter is set
There are three, one of EQ filter is for receiving secondary channel transmission function identification resultOutput signal is simultaneously filtered
Input adaptive filter W (z) afterwards, other two EQ filter are respectively used to main channel P (z), secondary channel system S (z)
Output signal filtering, filtered signal carries out sound wave and offsets and error originated from input filter and sef-adapting filter W (z).
7. a kind of scene adaptive active noise reduction earphone, which is characterized in that including microphone and loudspeaker, the microphone is successively
Connect pre-amplification circuit, Noise Identification module, active noise reduction module and power amplification circuit, the power amplification circuit and institute
Loudspeaker connection is stated, wherein：
Microphone, for picking up ambient noise and being converted to primary noise electric signal；
Noise Identification module, it is special for extracting noise immune collection Mid Frequency and frequency distribution from the primary noise electric signal
Property, and matched in noise pattern library with preset noise pattern, it determines noise type, is then selected in filter bank
Corresponding EQ filter parameter is loaded into active noise reduction module；
Active noise reduction module carries out the processing of the improvement FXLMS adaptive-filtering based on EQ filter to primary noise signal, generates
The de-noising electric signal of loudspeaker is motivated, and is exported to power amplification circuit；
Loudspeaker receives and generates de-noising sound wave after de-noising electric signal, the de-noising sound wave and the distribution of primary noise signal spectrum,
Acoustic pressure size is identical, opposite in phase, and loudspeaker exports the audio signal after offset noise.
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