CN104427144B - A kind of linear echo removing method and its device - Google Patents

Abstract

The present invention relates to the communications field, a kind of linear echo removing method and its device are disclosed, it is possible to increase the efficiency that linear echo is eliminated.The method includes：The near end signal of the reference signal of full band and full band is parsed into the reference signal of N number of subband and the near end signal of N number of subband respectively, the N is the integer more than 1；Reference signal to N number of subband carries out adaptive-filtering, obtains the estimated echo signal of N number of subband；The near end signal of N number of subband is made into the residual signals that difference obtains N number of subband with the estimated echo signal of N number of subband；Residual signals to N number of subband carry out integrated filter, obtain the residual signals of full band, and the residual signals of the full band are the signal after linear echo elimination.The linear echo removing method is used for the elimination of echo.

Description

A kind of linear echo removing method and its device

Technical field

The present invention relates to the communications field, more particularly to a kind of linear echo removing method and its device.

Background technology

In daily life and work, mobile phone has become indispensable instrument.With multimedia audio skill The development of art, people require also more and more higher to the audio performance of mobile phone.But, echo and make an uproar that the microphone of mobile phone is received Sound etc. can influence the speech quality of mobile phone.The echo received in wireless environments for the microphone of mobile phone and noise, can be with profit Eliminated with echo cancellation technology, so as to provide the user more preferable speech quality.

At present, realize that the technology of adaptive line echo cancellor is mainly based upon NLMS (Normalized least mean Square, normalized least mean-square error).In existing NLMS, calculating one echo signal for the treatment of needs larger meter Calculation amount and process time more long.Example, in real mobile phone communication, echo path length is about 40ms, for The system of 8KHz or 16KHz sample rates, echo path length is about 320 or 640 ranks, in actual Time Domain Processing, 320 ranks return Acoustic path needs 320 multiply-add calculating to obtain an estimated echo sampling point, and the echo path of 640 ranks needs 640 multiply-add meters Calculate to obtain an estimated echo sampling point, amount of calculation is larger.

In NLMS, sef-adapting filter is updated according to steepest descent method, it is to recalculate to update sef-adapting filter Adaptive filter coefficient vector, the change speed of adaptive filter coefficient vector is influenceed by step factor, step-length The factor is used to control the pace of change of adaptive filter coefficient, and theoretically, the step factor is believed by near-end speech again Number and the instantaneous energy of near-end noise signal influence, but, in the full tape handling of time domain, the near-end voice signals and near-end noise Signal fluctuation is very fast, in the mixed signal of the near-end speech, noise and echo, near-end voice signals energy is extracted respectively and is made an uproar Acoustic energy needs extremely complex algorithm, therefore, the step factor estimated using the full tape processing method of time domain is often theoretical with it Value has relatively large deviation.

The content of the invention

It is an object of the invention to provide a kind of linear echo removing method and its device, it is possible to increase linear echo is eliminated Efficiency.

In order to solve the above technical problems, embodiments of the present invention provide a kind of linear echo removing method, including：

The near end signal of the reference signal of full band and full band is parsed into the reference signal and N number of subband of N number of subband respectively Near end signal, the N is the integer more than 1；

Reference signal to N number of subband carries out adaptive-filtering, obtains the estimated echo signal of N number of subband；

The near end signal of N number of subband is made into difference with the estimated echo signal of N number of subband and obtains the residual of N number of subband Difference signal；

Residual signals to N number of subband carry out integrated filter, obtain the residual signals of full band, the residual error of the full band Signal is the signal after linear echo is eliminated.

Embodiments of the present invention provide the device that a kind of linear echo is eliminated, including：

Analysis filter group, including N number of analysis filter, for the near end signal of the reference signal of full band and full band to be divided The reference signal of N number of subband and the near end signal of N number of subband are not parsed into, and the N is the integer more than 1；

Sef-adapting filter group, including N number of sef-adapting filter, for the N number of subband exported to the analysis filter Reference signal carry out adaptive-filtering, obtain the estimated echo signal of N number of subband；

Processing unit, for described N number of son that the near end signal to N number of subband and the sef-adapting filter are exported The estimated echo signal of band makees the residual signals that difference obtains N number of subband；

Synthesis filter group, including N number of synthesis filter, for described N number of subband for being exported to the processing unit Residual signals carry out integrated filter, the residual signals of full band are obtained, after the residual signals of the full band are eliminated for linear echo Signal.

Embodiment of the present invention in terms of existing technologies, first, reference signal and near end signal is passed through respectively to divide Analyse filter analysis into the reference signal of N number of subband and the near end signal of N number of subband so that disappear in the echo for carrying out signal every time During except treatment, the near end signal of the reference signal of N number of subband and N number of subband can simultaneously be processed, then, to N number of son The reference signal of band carries out adaptive-filtering treatment, obtains the N number of subband estimated echo signal after linear echo is eliminated, finally, The residual signals that difference obtains N number of subband are made with the estimated echo signal of N number of subband to the near end signal of N number of subband, And the residual signals to N number of subband carry out integrated filter, full band residual signals are obtained, so by the adaptive-filtering of full band Device coefficient is decomposed in N number of subband, and the sef-adapting filter length of each subband is the 1/N of full strip length, is reduced linear Amount of calculation during echo cancellor, improves the efficiency of linear echo elimination.

In addition, carrying out adaptive-filtering in the reference signal to N number of subband, the estimated echo letter of N number of subband is obtained Number afterwards, methods described also includes：Update the coefficient of the sef-adapting filter, the renewal of the coefficient of the sef-adapting filter Formula is as follows：

Wherein, m is discrete time, and the m is the integer more than or equal to 0, describedFor m moment self adaptation is filtered The coefficient vector of ripple device, it is describedIt is the coefficient vector of (m+1) moment sef-adapting filter, when the μ (m) is m The step factor of sef-adapting filter is carved, the e (m) is that, at the m moment, the X reference signal of subband is filtered by self adaptation The X residual signals of subband obtained after the adaptive-filtering of ripple device, it is describedIt is the X ginseng of subband of m moment Signal vector is examined, it is describedIt is the X transposed vector of the reference signal of subband of m moment, T represents transposition, the △ It is a constant more than 0, the K (m) is the m positive diagonal square matrix of moment scale factor.

Because subband has the characteristics of bandwidth is small, and signal fluctuation is slow, therefore, believed using the reference signal in subband and near-end Number estimate that the coefficient ratio of sef-adapting filter for obtaining estimates the step-length for obtaining using the reference signal and near end signal in full band The factor is accurate.

In addition, in the coefficient for updating the sef-adapting filter, the μ (m) is calculated according to equation below：A, root The estimation for obtaining near end signal p (m), the m moment X subbands of the m moment X subbands respectively according to below equation is returned Acoustical signalWith the instantaneous energy R of residual signals e (m) of the m moment X subbands_pp(m)、R_ee(m), specifically Formula is as follows：

R_pp(m)=λ R_pp(m-1)+(1-λ)p²(m)

R_ee(m)=λ R_ee(m-1)+(1-λ)e²(m)

Wherein, λ is first order recursive smoothing factor；

B, according to the R_pp(m)、R_ee(m), material calculation factor mu (m), the formula for calculating the μ (m) is：

Wherein, ε is the constant more than 0, and abs () represents the computing that takes absolute value, and max () is represented and taken maximum operation.

Because subband has the characteristics of bandwidth is small, and signal fluctuation is slow, therefore, believed using the reference signal in subband and near-end Number estimate that the step factor Billy that obtains estimates that the step factor for obtaining is accurate with the reference signal and near end signal in full band.

Brief description of the drawings

Fig. 1 is the linear echo removing method schematic flow sheet of first embodiment of the invention；

Fig. 2 is the linear echo canceling device structural representation of first embodiment of the invention；

Fig. 3 is the linear echo removing method schematic flow sheet of second embodiment of the invention；

Fig. 4 is the Structures of Fast Realizing schematic diagram of the analysis filter group of second embodiment of the invention；

Fig. 5 is the Structures of Fast Realizing schematic diagram of the synthesis filter group of second embodiment of the invention；

Fig. 6 is the linear echo canceling device structural representation of third embodiment of the invention；

Fig. 7 is the structural representation of the sef-adapting filter of fifth embodiment of the invention；

Fig. 8 is the structural representation of the adaptive step computing unit of fifth embodiment of the invention.

Specific embodiment

To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with accompanying drawing to each reality of the invention The mode of applying is explained in detail.However, it will be understood by those skilled in the art that in each implementation method of the invention, In order that reader more fully understands the application and proposes many ins and outs.But, even if without these ins and outs and base Many variations and modification in following implementation method, it is also possible to realize the application each claim technical side required for protection Case.

First embodiment of the invention provides a kind of linear echo removing method, as shown in figure 1, the method includes：

101st, the near end signal of the reference signal of full band and full band is parsed into the reference signal of N number of subband and N number of respectively The near end signal of subband.

The N is the integer more than 1.

The reference signal is the useful voice signal that transmitter sends, and the near end signal is near-end speech, near-end The real echo signal that noise and the reference signal are produced is overlapped the signal of composition, and the near-end speech is microphone The voice signal of the speaker of reception, the ambient noise signal that the near-end noise is received for transmitter, the reference signal The real echo signal for producing is that the useful voice signal that the transmitter sends is reflected back microphone by loudspeaker Signal.

As shown in Fig. 2 Fig. 2 eliminates structural representation for the linear echo that first embodiment of the invention is provided.In figure, x N () represents reference signal, b (n) represents near-end noise signal, and d (n) represents reference signal x (n) by real echo pathThe real echo signal for obtaining, s (n) represents near-end voice signals.P (n) represents near end signal.Near-end noise signal b The mutual statistical independence of (n), real echo signal d (n) and near-end voice signals s (n), and its Fourier spectrum estimation in short-term Average is 0.

201 is the first analysis filter group, and N group analysis wave filters are had in first analysis filter group, and N is more than 1 Integer, for being the reference signal of N number of subband by the analysis of reference signal x (n) of full band, as shown in Fig. 2 reference signal x (n) The reference signal x of N number of subband is obtained by the first analysis filter group₀(n)、x₁(n)、...、x_N-1(n), the ginseng of N number of subband Examining signal can be expressed as x_jN (), j values are the integer between 0 to N-1.First analysis filter is by described with reference to letter Number x (n) analysis is prior art for the method for the reference signal of N number of subband, and specific embodiment may be referred to prior art, Therefore not to repeat here for the present invention；202 is the second analysis filter group, and the filtering of N group analysis is had in second analysis filter group Device, for being the near end signal of N number of subband by near end signal p (n) analysis of full band, as shown in Fig. 2 near end signal p (n) passes through Analysis filter group obtains the near end signal p of N number of subband₀(n)、p₁(n)、...、p_N-1N (), the near end signal of N number of subband can To be expressed as p_jN (), j values are the integer between 0 to N-1.Second analysis filter divides near end signal p (n) Analyse as the method for the near end signal of N number of subband is prior art, specific embodiment may be referred to prior art, and the present invention exists This is not repeated.

First analysis filter group exports the reference signal of N number of subband, the N number of analysis filtering in the first analysis filter group Device is corresponded with the reference signal of N number of subband, and the second analysis filter group exports the near end signal of N number of subband, the second analysis N number of analysis filter in wave filter group is corresponded with the near end signal of N number of subband.

102nd, the reference signal to N number of subband carries out adaptive-filtering, obtains the estimated echo signal of N number of subband.

As shown in Fig. 2 in Fig. 2 203 be sef-adapting filter group, have N number of adaptive-filtering in the sef-adapting filter group DeviceThe value of j is the integer between 0 to N-1, and the reference signal of N number of sef-adapting filter and N number of subband is one by one Correspondence, each sef-adapting filter is used for a filtering for subband.The N that sef-adapting filter is exported to the first analysis filter group The reference signal of individual subband carries out adaptive-filtering for prior art, and specific embodiment may be referred to prior art, this hair It is bright to will not be repeated here.As shown in Fig. 2 carry out adaptive-filtering to the reference signal of N number of subband, the N number of subband for obtaining is estimated Counting echo signal isThe estimated echo signal of N number of subband can be expressed as J values are the integer between 0 to N-1.The estimated echo signal of each subbandIt is the reference signal x of each subband_jN () passes through Cross its corresponding Subband adaptive filtersOutput.

103rd, the estimated echo signal of the near end signal of N number of subband and N number of subband is made into the residual error letter that difference obtains N number of subband Number.

Residual signals subtract remaining signal after estimated echo for signal that near-end is received.In Fig. 2, e₀(n)、e₁ (n)、...、e_N-1N () is residual signals, the residual signals can be expressed as e_jN (), j values are the integer between 0 to N-1.Should The residual signals e of N number of subband_jN () is the near end signal p of corresponding N number of subband_jThe estimated echo of (n) and corresponding N number of subband SignalMake what difference was obtained.

104th, the residual signals to N number of subband carry out integrated filter, obtain the residual signals of full band.

It is full the signal after linear echo is eliminated with residual signals, the full band residual signals are that near end signal passes through linear returning Voice signal after sound elimination.As shown in Fig. 2 204 being synthesis filter group in Fig. 2, synthesis filter group is residual to N number of subband Difference signal e_jN () obtains full band residual signals e (n) after carrying out integrated filter.The synthesis filter group is to the residual of N number of subband Difference signal e_jN method that () carries out integrated filter is prior art, and specific embodiment may be referred to prior art, the present invention Therefore not to repeat here.

Embodiment of the present invention in terms of existing technologies, first, reference signal and near end signal is passed through respectively to divide Analyse filter analysis into the reference signal of N number of subband and the near end signal of N number of subband so that disappear in the echo for carrying out signal every time During except treatment, the near end signal of the reference signal of N number of subband and N number of subband can simultaneously be processed, then, to N number of son The reference signal of band carries out adaptive-filtering treatment, obtains the N number of subband estimated echo signal after linear echo is eliminated, finally, The residual signals that difference obtains N number of subband are made with the estimated echo signal of N number of subband to the near end signal of N number of subband, And the residual signals to N number of subband carry out integrated filter, full band residual signals are obtained, so by the adaptive-filtering of full band Device coefficient is decomposed in N number of subband, and the sef-adapting filter length of each subband is the 1/N of full strip length, is reduced linear Amount of calculation during echo cancellor, improves the efficiency of linear echo elimination.

Second embodiment of the invention provides another linear echo removing method, second embodiment and the first embodiment party Formula is roughly the same, as shown in figure 3, main distinction part is：Self adaptation filter is carried out in the reference signal to N number of subband Ripple, obtains after the estimated echo signal of N number of subband, first updates the coefficient of sef-adapting filter, then perform first embodiment In step 103 and 104.The formula for updating the coefficient of sef-adapting filter is as follows：

Wherein, m is discrete time, and m is the integer more than or equal to 0,It is the coefficient of m moment sef-adapting filters Vector,It is the coefficient vector of (m+1) moment sef-adapting filter, μ (m) is the step of m moment sef-adapting filters The factor long, e (m) be at the m moment, the X reference signal of subband by the X adaptive-filtering of sef-adapting filter it The X residual signals of subband for obtaining afterwards,It is the X reference signal vector of subband of m moment,It is m The X transposed vector of the reference signal of subband of moment, Δ be one more than 0 constant, K (m) be m moment scale factor just Diagonal square matrix, calculates the diagonal element k of K (m)_iM the formula of () is：

Wherein, α is the sparse factor relevant with the sparse degree of echo path, in the range from (- 1,1),w_jM () is the adaptive filter coefficient at m moment, j is from 0 to L_W- 1 integer,It is expressed as the adaptive filter coefficient w that the m moment estimates_j The transposition of the matrix of (m) composition, L_wIt is sef-adapting filter length.By using signal fluctuation in subband it is slow the characteristics of, in son Calculated in band and update sef-adapting filter, the convergence and stability of effective control sef-adapting filter.

Particularly, before the coefficient of sef-adapting filter is updated, the linear echo removing method also includes：

μ (m) is calculated, μ (m) is calculated and is comprised the following steps：

A, near end signal p (m) according to m moment X subbands, the estimated echo signal of m moment X subbandsWith Residual signals e (m) of m moment X subbands obtain near end signal p (m) of m moment X subbands, m moment X respectively The estimated echo signal of bandWith the instantaneous energy R of residual signals e (m) of m moment X subbands_pp(m)、R_ee M (), specific formula is as follows：

R_pp(m)=λ R_pp(m-1)+(1-λ)p²(m)

R_ee(m)=λ R_ee(m-1)+(1-λ)e²(m)

Wherein, λ is first order recursive smoothing factor；

B, according to R_pp(m)、R_ee(m), material calculation factor mu (m), calculate μ (m) formula be：

Wherein, ε is 0 value.

Specifically, the method and step for calculating adaptive filter coefficient are as follows：

Assuming that calculating the X coefficient of the sef-adapting filter of subband of the n-th moment.First, according to the n-th moment reference signal VectorThe echo signal vector estimated with the n-th moment sef-adapting filterCalculate the n-th moment linear estimated echo SignalComputing formula is：Then, obtained according to the n-th moment near end signal p (n) and the n-th moment Linear Estimation echo signalTo calculate residual signals e (n), computing formula is：Then, according to n-th The Linear Estimation echo signal that near end signal p (n) at moment, the n-th moment obtainWith residual signals e (n) at the n-th moment, To estimate the instantaneous energy of above-mentioned three kinds of signals, the formula for calculating the instantaneous energy of near end signal is：R_pp(n)=λ R_pp(n-1)+ (1-λ)p²(n)；The formula of instantaneous energy for calculating Linear Estimation echo signal is：Calculate residual The formula of the instantaneous energy of difference signal is：R_ee(n)=λ R_ee(n-1)+(1-λ)e²(n).In above three formula, λ is single order Recurrence smoothing factor, general value is 0.9.Then, the instantaneous energy R according near end signal_pp(n), Linear Estimation echo signal Instantaneous energyAnd the instantaneous energy R of residual signals_eeN () calculates step factor μ (n) at the n-th moment, calculates μ (n) Formula be：Wherein abs () is modulo operation, max () To take maximum operation, ε be one it is less for 0 value, ensure that denominator is not 0.Again, according to the n-th moment self adaptation The echo path vector that wave filter is estimatedTo calculate scale factor square formation K (n) at the n-th moment, the formula of K (n) is calculated For：

Wherein, α is the sparse factor relevant with the sparse degree of echo path, in the range from (- 1,1),w_jN () is the adaptive filter coefficient at the n-th moment, j be from 0 to L_W- 1 integer, T is transposition, L_wIt is sef-adapting filter length.Finally obtain the adaptive filter coefficient after updating Wherein Δ is a less value, generally 10^-3。

Finally, reference signal can be updatedWith near end signal p (n), the self adaptation filter at (n+1) moment is then calculated The coefficient of ripple device.

Because subband has the characteristics of bandwidth is small, and signal fluctuation is slow, therefore, using reference signal in subband and near end signal Step factor is carried out to estimate that the step factor for obtaining can be more accurate.

Especially, embodiments of the present invention provide a kind of DFT (discrete Fourier transform, Discrete Fourier Transform) the quick implementation of wave filter group, for realizing analysis filter group and synthesis filter group.Due to first As being achieved in that of analysis filter group and the second analysis filter group, hereafter for convenience of description, filtered with analysis Ripple device group represents the first analysis filter group and the second analysis filter group.

In actual applications, analysis filter group is in the form of the modulated filter group of multinomial structure.The multinomial structure Modulated filter group the use of length is L_PFIR (Finite Impulse Response, there is limit for length's impulse response) Imitative tenth of the twelve Earthly Branches ptototype filter h (n), by after complex-exponential-modulation, obtaining N number of Subband Analysis Filter, N number of Subband Analysis Filter H can be expressed as_KZ (), k values are 0 to N-1 integer.Complex-exponential-modulation mode is prior art, be will not be repeated here. In the description of the quick implementation of following DFT wave filter groups, T is modulation matrix, and for DFT wave filter groups, T represents discrete Fourier transformation；For cosine modulated filters group, T represents discrete cosine transform.L₁To extract matrix, L₂It is a sequence square Battle array.

For the analysis filter group with N number of subband, the multinomial I types of wave filter of its k-th subband can be expressed as：

Wherein H_k|nZ () is H_kMultinomial n-th component of I types of (z), D for extract or interpolation number (used here as extract and insert The consistent wave filter group of value).

For reference signal X (z), its multinomial II type can be decomposed into：

Wherein, X_nZ () is multinomial n-th component of II types of X (z).

The vector form that reference signal and analysis filter group can be written as：

So, analysis filter group is output as：

Can be expressed as：Assuming that L_pSimultaneously It is D and the multiple of subband number N, then the modulation sequence of k-th sub-filter isThe The coefficient of the wave filter after the modulation of k sub-filter isTherefore,

Wherein I_DIt is D × D unit matrix, p_i, i=0,1 ..., L_p- 1 is ptototype filter coefficient.

In element with N as cycle, order

It is the complex-exponential-modulation vector in a cycle N.

Final modulation matrix is：

Then the Multi-Nominal Matrix of analysis filter group can be expressed as：

H(z)=T·L₂·P·L₁(z)

Then analysis filter group is output as：

The perfect reconstruction filter bank of analysis filter group can be：

F (z) H (z)=Δ (z), Δ (z) is pure time delay,

Perfect reconstruction filter bank and ptototype filter according to analysis filter group are paraunitary filters, can obtain comprehensive filter The Multi-Nominal Matrix of ripple device group is：

F (z)=Δ (z) H^H(z^-1)=Δ (z) L₁ ^T(z^-1)·P·L₂ ^T·T^H

Subscript H represents conjugate transposition, for Δ (z) L₁ ^T(z^-1) item, order

WhereinIt is L_p×L_pAnti- unit matrix：

For the ease of realizing, by reconstruction signalIt is divided into two parts, adds an intermediate variable V Z (), then has

Wherein I_DWith 0_DThe respectively null matrix of the unit matrix of D × D and D × D.

Then synthesis filter group is output as：

That is last N number of element of V (z).

Example, a kind of Structures of Fast Realizing schematic diagram of analysis filter group that Fig. 4 is provided for embodiment of the present invention, A kind of Structures of Fast Realizing schematic diagram of synthesis filter group that Fig. 5 is provided for embodiment of the present invention.DFT wave filter groups it is fast Fast implementation is not only limited to this, and the embodiment of the present invention is merely illustrative, and those skilled in the art is without creativeness Work, any implementation expected all should be comprising within the scope of the present invention.

Third embodiment of the invention provides a kind of linear echo canceling device 60, as shown in fig. 6, the linear echo is eliminated Device 60 includes：

Analysis filter group 601, including N number of analysis filter, for the near-end of the reference signal of full band and full band to be believed Number the reference signal of N number of subband and the near end signal of N number of subband are parsed into respectively, the N is the integer more than 1；

Sef-adapting filter group 602, including N number of sef-adapting filter, for the N number of son exported to the analysis filter The reference signal of band carries out adaptive-filtering, obtains the estimated echo signal of N number of subband.

Processing unit 603, for the N that the near end signal to N number of subband and the sef-adapting filter are exported The estimated echo signal of individual subband makees the residual signals that difference obtains N number of subband.

Synthesis filter group 604, including N number of synthesis filter, for the described N number of subband exported to the processing unit Residual signals carry out integrated filter, the residual signals of full band are obtained, after the residual signals of the full band are eliminated for linear echo Signal.

In terms of existing technologies, analysis filter group distinguishes reference signal and near end signal to embodiment of the present invention The reference signal of N number of subband and the near end signal of N number of subband are parsed into by analysis filter so that carrying out signal every time During echo cancellation process, the near end signal of the reference signal of N number of subband and N number of subband can simultaneously be processed, self adaptation Wave filter group carries out adaptive-filtering treatment to the reference signal of N number of subband, obtains the N number of subband after linear echo is eliminated and estimates Echo signal, processing unit makees difference and obtains N to the near end signal of N number of subband with the estimated echo signal of N number of subband The residual signals of individual subband, synthesis filter group carries out integrated filter to the residual signals of N number of subband, obtains full band residual error Signal, during the adaptive filter coefficient of full band so decomposed into N number of subband, the sef-adapting filter length of each subband It is the 1/N of full strip length, reduces amount of calculation when linear echo is eliminated, improves the efficiency of linear echo elimination.

Four embodiment of the invention provides another linear echo canceling device, the 4th implementation method and the 3rd embodiment party Formula is roughly the same, and main distinction part is：Each sef-adapting filter in the sef-adapting filter group also includes：Update Unit 6021, the coefficient for updating the sef-adapting filter before integrated filter calculates new sef-adapting filter The formula of coefficient is as follows：

Wherein, m is discrete time, and the m is the integer more than or equal to 1, describedIt is m moment adaptive-filterings The coefficient vector of device, it is describedIt is the coefficient vector of (m+1) moment sef-adapting filter, the μ (m) is the m moment The step factor of sef-adapting filter, the e (m) is that, at the m moment, the X reference signal of subband is by the X self adaptation The X residual signals of subband obtained after the adaptive-filtering of wave filter, it is describedIt is the X subband of m moment Reference signal vector, the Δ is a constant more than 0, and the K (m) is the m positive diagonal square matrix of moment scale factor.

Fifth embodiment of the invention provides another linear echo canceling device, the 5th implementation method and the 4th embodiment party Formula is roughly the same, and main distinction part is：As shown in fig. 7, each sef-adapting filter in the sef-adapting filter group Also include：

Diagonal components computing unit 6022, for calculating the K (m).

Adaptive step computing unit 6023, for calculating the μ (m).

The formula for calculating the K (m) is：

Wherein, the α is the sparse factor relevant with the sparse degree of echo path, described in the range from (- 1,1)w_jM () is the adaptive filter coefficient at m moment, j is from 0 to L_W- 1 integer, it is describedIt is expressed as the sef-adapting filter that the m moment estimates Coefficient vector, the L_wIt is sef-adapting filter length.By using signal fluctuation in subband it is slow the characteristics of, calculate in a sub-band And update the μ (m) of sef-adapting filter, the convergence and stability of effective control sef-adapting filter.

As shown in figure 8, adaptive step computing unit 6023 includes following subelement：Instantaneous energy computation subunit 60231, near end signal p (m) according to m moment subbands, estimated echo signalObtained respectively with residual signals e (m) Obtain near end signal p (m), the estimated echo signalWith the instantaneous energy R of residual signals e (m)_pp(m)、R_eeM (), specific formula is as follows：

R_pp(m)=λ R_pp(m-1)+(1-λ)p²(m)

R_ee(m)=λ R_ee(m-1)+(1-λ)e²(m)

Wherein, λ is first order recursive smoothing factor.

Step factor computation subunit 60232, for according to the R_pp(m)、R_ee(m), material calculation factor mu M (), the formula for calculating the μ (m) is：

Wherein, ε is the constant more than 0, and abs () represents the computing that takes absolute value；Max () is represented and is taken maximum operation.

Because subband has the characteristics of bandwidth is small, and signal fluctuation is slow, therefore, using reference signal in subband and near end signal Step factor is carried out to estimate that the step factor for obtaining can be more accurate.

It is noted that each module involved in present embodiment is logic module, in actual applications, one Individual logic unit can be a part for a physical location, or a physical location, can also be with multiple physics lists The combination of unit is realized.The operation principle of each physical location may be referred to the narration in embodiment of the method, and the present invention is herein no longer Repeat.Additionally, in order to protrude innovative part of the invention, not by the skill proposed by the invention with solution in present embodiment The less close unit of art issue concerns is introduced, but this is not intended that in present embodiment do not exist other units.

It will be understood by those skilled in the art that the respective embodiments described above are to realize specific embodiment of the invention, And in actual applications, can to it, various changes can be made in the form and details, without departing from the spirit and scope of the present invention.

Claims (6)

1. a kind of linear echo removing method, it is characterised in that including：

By the near end signal of the reference signal of full band and full band be parsed into respectively N number of subband reference signal and N number of subband it is near End signal, the N is the integer more than 1；

Reference signal to N number of subband carries out adaptive-filtering, obtains the estimated echo signal of N number of subband；

The coefficient of the sef-adapting filter is updated, the more new formula of the coefficient of the sef-adapting filter is as follows：

$\stackrel{\→}{W}(m+1)=\stackrel{\→}{W}\left(m\right)+\frac{\mathrm{\μ}\left(m\right)e\left(m\right)\stackrel{\→}{X}\left(m\right)K\left(m\right)}{{\stackrel{\→}{X}}^T\left(m\right)K\left(m\right)\stackrel{\→}{X}\left(m\right)+\mathrm{\Δ}}$

Wherein, m is discrete time, and the m is the integer more than or equal to 0, describedIt is m moment sef-adapting filters Coefficient vector, it is describedIt is the coefficient vector of (m+1) moment sef-adapting filter, the μ (m) is that the m moment is adaptive The step factor of wave filter is answered, the e (m) is that, at the m moment, the X reference signal of subband is by sef-adapting filter The X residual signals of subband obtained after adaptive-filtering, it is describedIt is the X reference signal of subband of m moment Vector, it is describedIt is the X transposed vector of the reference signal of subband of m moment, T represents transposition, and the Δ is one Constant more than 0, the K (m) is the m positive diagonal square matrix of moment scale factor；

The estimated echo signal of the near end signal of N number of subband and N number of subband is made into the residual error letter that difference obtains N number of subband Number；

Residual signals to N number of subband carry out integrated filter, obtain the residual signals of full band, the residual signals of the full band Signal after being eliminated for linear echo.

2. linear echo removing method according to claim 1, it is characterised in that update the adaptive-filtering described In the coefficient of device, the K (m) is calculated according to equation below：

The diagonal components k of m moment K (m) is calculated according to equation below_i(m)：

$k_i\left(m\right)=\frac{(1-\mathrm{\α})}{2L_w}+(1+\mathrm{\α})\frac{\left|w_i\left(m\right)\right|}{\sqrt{{\stackrel{\→}{W}}^T\left(m\right)\stackrel{\→}{W}\left(m\right)}},i=0,1,...,L_w-1$

It is described

Wherein, the α is the sparse factor relevant with the sparse degree of echo path, described in the range from (- 1,1)Wherein, the w_iM () is the m momentIn i-th component, The i is from 0 to L_W- 1 integer, the L_wIt is sef-adapting filter length.

3. linear echo removing method according to claim 1, it is characterised in that update the adaptive-filtering described In the coefficient of device, the μ (m) is calculated according to equation below：

A, near end signal p (m) that m moment X subbands are obtained according to below equation, the estimated echo letter of m moment X subbands NumberWith the instantaneous energy R of residual signals e (m) of m moment X subbands_pp(m)、R_ee(m)：

R_pp(m)=λ R_pp(m-1)+(1-λ)p²(m)

$R_{d\hat{d}}\left(m\right)={\mathrm{\λR}}_{d\hat{d}}(m-1)+(1-\mathrm{\λ}){\hat{d}}^2\left(m\right)$

R_ee(m)=λ R_ee(m-1)+(1-λ)e²(m)

Wherein, the λ is first order recursive smoothing factor；

B, according to the R_pp(m)、R_ee(m), material calculation factor mu (m), the formula for calculating the μ (m) is：

$\mathrm{\μ}\left(m\right)=max(1-\sqrt{\frac{abs\left(R_{pp}\right(m)-R_{d\hat{d}}(m\left)\right)}{R_{ee}\left(m\right)+\mathrm{\ϵ}}},0)$

Wherein, the ε is the constant more than 0, and abs () represents the computing that takes absolute value, and max () is represented and taken maximum operation.

4. a kind of linear echo canceling device, it is characterised in that including：

Analysis filter group, including N number of analysis filter, for the near end signal of the reference signal of full band and full band to be divided respectively The reference signal of N number of subband and the near end signal of N number of subband are analysed into, the N is the integer more than 1；

Sef-adapting filter group, including N number of sef-adapting filter, the ginseng of the N number of subband for being exported to the analysis filter Examining signal carries out adaptive-filtering, obtains the estimated echo signal of N number of subband；

Updating block, the coefficient for updating the sef-adapting filter, the more new formula of the coefficient of the sef-adapting filter It is as follows：

$\stackrel{\→}{W}(m+1)=\stackrel{\→}{W}\left(m\right)+\frac{\mathrm{\μ}\left(m\right)e\left(m\right)\stackrel{\→}{X}\left(m\right)K\left(m\right)}{{\stackrel{\→}{X}}^T\left(m\right)K\left(m\right)\stackrel{\→}{X}\left(m\right)+\mathrm{\Δ}}$

Wherein, m is discrete time, and the m is the integer more than or equal to 0, describedIt is m moment sef-adapting filters Coefficient vector, it is describedIt is the coefficient vector of (m+1) moment sef-adapting filter, the μ (m) is that the m moment is adaptive The step factor of wave filter is answered, the e (m) is that, at the m moment, the X reference signal of subband is by the X adaptive-filtering The X residual signals of subband obtained after the adaptive-filtering of device, it is describedIt is the X reference of subband of m moment Signal vector, it is describedIt is the X transposed vector of the reference signal of subband of m moment, T represents transposition, and the Δ is One constant more than 0, the K (m) is the m positive diagonal square matrix of moment scale factor；

Processing unit, the described N number of subband exported for the near end signal to N number of subband and the sef-adapting filter Estimated echo signal makees the residual signals that difference obtains N number of subband；

Synthesis filter group, including N number of synthesis filter, the residual error of the described N number of subband for being exported to the processing unit Signal carries out integrated filter, obtains the residual signals of full band, and the residual signals of the full band are the signal after linear echo elimination.

5. linear echo canceling device according to claim 4, it is characterised in that every in the sef-adapting filter group Individual sef-adapting filter also includes：

Diagonal components computing unit, for calculating the K (m),

Calculate m moment K (m) diagonal components k_iM the formula of () is：

$k_i\left(m\right)=\frac{(1-\mathrm{\α})}{2L_W}+(1+\mathrm{\α})\frac{\left|w_i\left(m\right)\right|}{\sqrt{{\stackrel{\→}{W}}^T\left(m\right)\stackrel{\→}{W}\left(m\right)}},i=0,1,...,L_W-1$

Wherein, the α is the sparse factor relevant with the sparse degree of echo path, described in the range from (- 1,1)Wherein, the w_iM () is the m momentIn i-th component, The i is from 0 to L_W- 1 integer, the L_wIt is sef-adapting filter length.

6. linear echo canceling device according to claim 4, it is characterised in that every in the sef-adapting filter group Individual sef-adapting filter also includes：

Adaptive step computing unit, for calculating the μ (m), the adaptive step computing unit includes following subelement：

Instantaneous energy computation subunit, near end signal p (m) according to m moment subbands, estimated echo signalWith it is residual Difference signal e (m) obtains near end signal p (m), the estimated echo signal respectivelyWith the wink of residual signals e (m) Shi Nengliang R_pp(m)、R_eeM (), specific formula is as follows：

R_pp(m)=λ R_pp(m-1)+(1-λ)p²(m)

$R_{d\hat{d}}\left(m\right)={\mathrm{\λR}}_{d\hat{d}}(m-1)+(1-\mathrm{\λ}){\hat{d}}^2\left(m\right)$

R_ee(m)=λ R_ee(m-1)+(1-λ)e²(m)

Wherein, λ is first order recursive smoothing factor；

Step factor computation subunit, for according to the R_pp(m)、R_eeM (), material calculation factor mu (m) calculates institute The formula for stating μ (m) is：

$\mathrm{\μ}\left(m\right)=max(1-\sqrt{\frac{abs\left(R_{pp}\right(m)-R_{d\hat{d}}(m\left)\right)}{R_{ee}\left(m\right)+\mathrm{\ϵ}}},0)$

Wherein, the ε is the constant more than 0, and abs () represents the computing that takes absolute value；Max () is represented and is taken maximum operation.