CN113783551A - Filter coefficient determination method, echo cancellation method and device - Google Patents

Abstract

The application provides a filter coefficient determining method, an echo eliminating method and a device. The filter coefficient determination method includes: constructing a plurality of sub far-end signals based on the far-end signals; calculating the step length of each filter based on the sub far-end signal corresponding to each filter by taking the error signal obtained by the next filtering of each filter as the calculation condition, wherein the product of the filter coefficient lengths of all the filters is equal to the length of the far-end signal; the next filter coefficient for each filter is calculated based on the step size of each filter. The application can improve the convergence speed of the filter.

Description

Filter coefficient determination method, echo cancellation method and device

technical field

The present application relates to the field of filtering technologies, and in particular, to a method for determining filter coefficients, a method and apparatus for echo cancellation.

Background technique

In real life, when people use a mobile phone to turn on a hands-free phone or a video conference terminal to conduct a video conference, the sound played by the speaker will be collected by the microphone again due to the loudspeaker, resulting in an echo problem. Generally speaking, the echo signal will seriously affect the call quality and reduce the accuracy of speech recognition, so it is necessary to use an adaptive filter to cancel the generated echo. But the existing adaptive filters have slow convergence speed.

SUMMARY OF THE INVENTION

The present application provides a filter coefficient determination method, an echo cancellation method, and an apparatus, so as to solve the problem of the slow convergence speed of the existing adaptive filter.

In order to solve the above problems, the present application provides a method for determining filter coefficients, the method comprising:

Constructing multiple sub-remote signals based on the remote signal;

Taking the error signal obtained by the next filtering of each filter equal to the near-end signal as the calculation condition, the step size of each filter is calculated based on the sub-end signal corresponding to each filter, where the length of the filter coefficients of all filters is equal to The product is equal to the length of the far-end signal;

The next filter coefficient for each filter is calculated based on the step size of each filter.

Wherein, the step of constructing multiple sub-remote signals based on the remote signal includes:

The calculation is performed based on the far-end signal and the current filter coefficients of other filters to obtain the sub-remote signal corresponding to each filter.

Wherein, the step of constructing multiple sub-remote signals based on the remote signal includes:

Construct two sub-remote signals based on the remote signal;

The two sub-remote signals are in one-to-one correspondence with the two filters, and the product of the filter coefficient lengths of the two filters is equal to the length of the remote signal.

Wherein, the steps of calculating based on the remote signal and the current filter coefficients of other filters include:

Perform Kronecker multiplication of the current filter coefficients of other filters and the identity matrix to obtain the first matrix of other filters;

Multiply the first matrix of other filters and the far-end signals to obtain sub-remote signals corresponding to each filter.

Wherein, the error signal obtained by the next filtering of each filter is equal to the near-end signal as the calculation condition, and the step of calculating the step size of each filter based on the sub-end signal corresponding to each filter includes:

Substitute the near-end signal as the error signal of the next filter into the first relationship formula of each filter, and the first relationship formula is the error signal of the next filter, the error signal of the current filter, the sub-end of each filter. The formula for the relationship between the signal and the step size to get the step size for each filter.

The first relational formula of each filter is calculated by using the next filter coefficient calculation formula of each filter, the error signal calculation formula of the next filter, and the error signal calculation formula of the current filter.

Among them, the first relational formula of the ith filter is as follows:

为第i个滤波器对应的子远端信号的转置矩阵，μ_i(n)为第i个滤波器的步长，ξ为预设常数。Among them, v(n) is the near-end signal, e _i (n) is the error signal currently filtered by the ith filter, m _i (n) is the sub-end signal corresponding to the ith filter,

is the transposed matrix of the sub-remote signal corresponding to the ith filter, μ _i (n) is the step size of the ith filter, and ξ is a preset constant.

Wherein, the step of calculating the next filter coefficient of each filter based on the step size of each filter includes:

The filter coefficients of all filters are fused to obtain a total filter coefficient, so that the far-end signal is processed by the total filter coefficient to obtain an analog echo signal of the far-end signal.

In order to solve the above problems, the present application provides an echo cancellation method, the method includes:

The received far-end audio signal is input to the adaptive filter as a far-end signal to obtain an analog echo signal, wherein the filter coefficient in the adaptive filter is determined according to the above-mentioned filter coefficient determination method;

The echo-cancelled signal is obtained based on the analog echo signal and the near-end acquisition signal.

To solve the above problem, the present application provides an electronic device, the electronic device includes a processor; the processor is configured to execute instructions to implement the steps of the above method.

In order to solve the above problems, the present application provides a computer storage medium on which instructions/program data are stored, and the steps of the above method are implemented when the instructions/program data are executed.

The method of the present application is to construct a plurality of sub-remote-end signals based on the remote-end signals, wherein the plurality of sub-remote-end signals are in one-to-one correspondence with a plurality of filters, so as to use the plurality of sub-end-end signals to train their corresponding filters respectively, and due to The product of the filter coefficient lengths of the multiple filters is equal to the length of the far-end signal, and the total number of filter coefficients updated in this embodiment is smaller than the amount of filter coefficients in the existing “directly train a filter by using the far-end signal” scheme, and A plurality of filters in this embodiment can be updated at the same time, so that the speed of filter convergence can be improved.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present application more clearly, the following briefly introduces the drawings that are used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without creative effort.

1 is a schematic flowchart of an implementation method of a filter coefficient determination method of the present application;

2 is a schematic flowchart of an embodiment of an echo cancellation method of the present application;

FIG. 3 is a schematic structural diagram of an embodiment of the electronic device of the present application;

FIG. 4 is a schematic structural diagram of an embodiment of a computer storage medium of the present application.

Detailed ways

In order for those skilled in the art to better understand the technical solutions of the present application, the method for determining filter coefficients, the method and apparatus for echo cancellation provided by the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

The terms "first", "second" and "third" in this application are only used for descriptive purposes, and should not be construed as indicating or implying relative importance or implying the number of indicated technical features. Thus, a feature defined as "first", "second", "third" may expressly or implicitly include at least one of that feature. In the description of the present application, "a plurality of" means at least two, such as two, three, etc., unless otherwise expressly and specifically defined.

Reference herein to an "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment can be included in at least one embodiment of the present application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor a separate or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments without conflict.

As shown in FIG. 1 , FIG. 1 is a schematic flowchart of the first embodiment of the filter coefficient determination method of the present application. The filter coefficient determination method of the present application may include the following steps. Wherein, the filter filtering algorithm of the present application may be a Least Mean Square (Least Mean Square, LMS) algorithm or a Normalized Least Mean Square (Normalized Least Mean Squares, NLMS), etc., which is not limited herein. For ease of description, the following content takes the LMS algorithm as an example to describe the filter coefficient update process. It should be noted that the following step numbers are only used to simplify the description, and are not intended to limit the execution sequence of the steps. The execution sequence of each step in this embodiment can be changed arbitrarily without violating the technical idea of the present application.

S101: Construct a plurality of sub-remote signals based on the remote signals.

Multiple sub-remote signals can be constructed based on the far-end signals, wherein the multiple sub-remote signals are in one-to-one correspondence with multiple filters, so that the corresponding filters can be trained respectively by using the multiple sub-remote signals, and due to the multiple filters The product of the filter coefficient lengths of the filter is equal to the length of the far-end signal, and the total number of filter coefficients updated in this embodiment is smaller than the number of filter coefficients in the existing scheme of “directly training a filter by using the far-end signal”, and this embodiment Multiple filters of can be updated at the same time, which can improve the speed of filter convergence.

Optionally, can be calculated based on the current filter coefficients of the far-end signal and other filters to obtain the sub-remote signal corresponding to each filter, so that the sub-remote signal and the coefficient length of its corresponding filter are matched, so that The filter can process its corresponding sub-remote signal, so that the coefficient of the filter can be updated by using the sub-remote signal, and the update process of the filter coefficients of the two filters will use the data of the other filter, so that the filter coefficients of the two filters can be updated. Make sure that the filter can converge.

The "other filters" mentioned above may refer to at least one filter other than each filter itself among the multiple filters corresponding to the multiple sub-remote signals. For example, if the number of sub-remote signals is two, and the number of filters is also two, the current filter coefficient of the second filter can be used to calculate the sub-remote signals corresponding to the first filter, and the first filter can be used to calculate the corresponding sub-remote signals. The current filter coefficient of , calculates the sub-remote signal corresponding to the second filter.

Wherein, the step of calculating based on the far-end signal and the current filter coefficients of other filters may include: performing Kronecker multiplication operation on the current filter coefficients of other filters and the identity matrix to obtain the first matrix of the other filters; The first matrices of other filters are multiplied by the far-end signals to obtain sub-remote signals corresponding to each filter.

Further, the current filter coefficients of the respective filters may be divided into a plurality of coefficient data. Wherein, the lengths of the number of coefficients of each filter may be equal. For example, the length of the current filter coefficient of a filter is 6, and it is divided into two coefficient data, the first three filter coefficients in the current filter coefficient of the filter can be used as the first coefficient data of the filter, The last three filter coefficients in the current filter coefficients of the filter are used as the second coefficient data of the filter.

The step of performing the Kronecker multiplication operation on the current filter coefficients and the unit matrix of other filters can be embodied as follows: perform Kronecker multiplication operation on each coefficient data of other filters and the unit matrix, and obtain the first number of each coefficient data. Correspondingly, the step of multiplying the first matrix of the other filters and the far-end signal can be embodied as: multiplying the first matrix of the coefficient data of the other filters and the far-end signal to obtain the other filter Then, the processed signals of all the coefficient data of other filters can be combined to obtain the sub-remote signal corresponding to each filter.

The specific calculation formula can be as follows:

为第i个滤波器的第d个系数数据，其中d＝[1,D]，而D为各个滤波器的当前滤波系数的划分数量，具体可根据实际情况进行设置，在此不做限制，例如可为2；

为第i个滤波器的当前滤波系数，

为单位矩阵，L_i为第i个滤波器的滤波系数长度，

表示克罗内克乘，

为第i个滤波器的第d个系数数据的第一矩阵，x(n)为远端信号，

为第i个滤波器的第d个系数数据处理后的信号；x_i(n)为利用第i个滤波器的当前滤波系数计算出的子远端信号，若i取值范围为1或2，在i＝1的情况下，x_i(n)为第二个滤波器对应的子远端信号，在i＝2的情况下，x_i(n)为第一个滤波器对应的子远端信号。in,

is the d-th coefficient data of the i-th filter, where d=[1, D], and D is the number of divisions of the current filter coefficients of each filter, which can be set according to the actual situation, which is not limited here. For example, it can be 2;

is the current filter coefficient of the ith filter,

is the identity matrix, L _i is the filter coefficient length of the ith filter,

represents the Kronecker multiplication,

is the first matrix of the d-th coefficient data of the i-th filter, x(n) is the far-end signal,

is the signal processed by the d-th coefficient data of the ith filter; x _i (n) is the sub-remote signal calculated by using the current filter coefficient of the ith filter, if the value range of i is 1 or 2 , in the case of i=1, x _i (n) is the sub-remote signal corresponding to the second filter, and in the case of i=2, x _i (n) is the sub-remote corresponding to the first filter. terminal signal.

S102: Calculate the step size of each filter based on the sub-end signal corresponding to each filter on the condition that the error signal obtained by the next filtering of each filter is equal to the near-end signal.

After constructing a plurality of sub-remote signals based on step S101, the error signal obtained by the next filtering of each filter is equal to the near-end signal as the calculation condition, and each filter can be calculated based on the sub-remote signal corresponding to each filter. Therefore, the optimal step size can be calculated, so that the next filter coefficient calculated based on the calculated step size is better than the next filter coefficient calculated with the fixed step size, thereby speeding up the convergence speed of the filter.

The product of the filter coefficient lengths of all filters is equal to the length of the far-end signal, and the filter coefficient lengths of all filters are greater than 1, so the total number of filter coefficients updated in this embodiment is smaller than the existing "Using the far-end signal to directly train a The number of filter coefficients in the filter scheme reduces the computational complexity and improves the convergence speed of the filter.

Optionally, the near-end signal can be substituted into the first relational formula of each filter as the error signal of the next filtering to obtain the step size of each filter, wherein the first relational formula is each filter. The relationship formula between the next filtered error signal of the filter, the current filtered error signal, the sub-remote signal and the step size.

Exemplarily, the first relational formula of each filter may be respectively as follows:

为第i个滤波器对应的子远端信号的转置矩阵，μ_i(n)为第i个滤波器的步长，ξ为一个预设常数，可根据实际情况进行设定，例如可为0.0001，以保证分母为不会出现0的情况。其中，m_i(n)可根据步骤S101进行计算，在此不做赘述，例如假设子远端信号和滤波器的数量均为二，m₁(n)＝x₂(n)，m₂(n)＝x₁(n)。Among them, v(n) is the near-end signal, e _i (n) is the error signal currently filtered by the ith filter, m _i (n) is the sub-end signal corresponding to the ith filter,

is the transposed matrix of the sub-remote signal corresponding to the ith filter, μ _i (n) is the step size of the ith filter, and ξ is a preset constant, which can be set according to the actual situation, for example, it can be 0.0001 to ensure that the denominator will not appear 0. Wherein, m _i (n) can be calculated according to step S101, which will not be repeated here. For example, assuming that the number of sub-remote signals and filters are both two, m ₁ (n)=x ₂ (n), m ₂ ( n)=x ₁ (n).

The first relational formula of each filter is calculated by using the calculation formula of the next filter coefficient of each filter, the calculation formula of the error signal of the next filter, and the calculation formula of the error signal of the current filter. Among them, the next filter coefficient of each filter is the filter coefficient used in the next filter of each filter, and the error signal of the next filter of each filter is obtained in the next filter of each filter. error signal.

Wherein, the calculation formula of the current filtered error signal of each filter can be:

The calculation formula of the next filter coefficient of each filter can be:

The calculation formula of the next filtered error signal of each filter can be:

为第i个滤波器的当前滤波系数的转置矩阵，e_i(n)为第i个滤波器的当前滤波的误差信号，

为第i个滤波器的当前滤波系数，

为第i个滤波器的下一滤波系数，μ_i(n)为第i个滤波器的步长，∈_i(n)为第i个滤波器的下一滤波的误差信号。Among them, y(n) is the near-end acquisition signal, m _i (n) is the sub-end-end signal corresponding to the ith filter,

is the transposed matrix of the current filter coefficient of the ith filter, e _i (n) is the error signal of the current filter of the ith filter,

is the current filter coefficient of the ith filter,

is the next filter coefficient of the ith filter, μ _i (n) is the step size of the ith filter, and ∈ _i (n) is the error signal of the next filter of the ith filter.

Optionally, using the calculation formula of the next filter coefficient of each filter, the calculation formula of the error signal of the next filter and the calculation formula of the error signal of the current filter to calculate the step of obtaining the first relationship formula of each filter may include: : The calculation formula of the error signal of the next filter of each filter is subtracted from the calculation formula of the error signal of the current filter of each filter to obtain the second relationship formula; the calculation of the next filter coefficient of each filter is calculated. The formula is substituted into the second relational formula for each filter to obtain the first relational formula for each filter.

In order to avoid errors in the step size calculation, causing the filter to fail to converge, the calculation formula of the next filter coefficient of each filter is substituted into the second relational formula of each filter to obtain the third relational formula of each filter. where, the third relational formula is an equation, and one end of the third relational formula is the error signal of the next filter of each filter, and the other end of the third relational formula is expected to be equal to the expectation of the near-end signal, Thus, the first relational formula for each filter is obtained.

Among them, the third relational formula of each filter can be:

Finding the expectation on the other side of the third relational formula and making it equal to the expectation of the near-end signal can be as follows:

S103: Calculate the next filter coefficient of each filter based on the step size of each filter.

After the step size of each filter is calculated based on step S102, the next filter coefficient of each filter may be calculated based on the step size of each filter.

)的计算公式计算出每个滤波器的下一滤波系数。Optionally, the calculation formula of the next filter coefficient of each filter can be used (for example,

) to calculate the next filter coefficient of each filter.

After calculating the next filter coefficient of each filter based on step S103, it can be judged whether each filter converges; if the filter converges, any filter can be used to perform echo cancellation on the near-end collected signal, or all filters can be used for echo cancellation. Calculate the filter coefficient of the filter to obtain the filter coefficient of a total filter, so that the total filter can be used to directly process the far-end signal corresponding to the near-end acquisition signal; if the filter does not converge, the filter coefficient of each filter can be The next filter coefficient is used as the current filter coefficient of each filter, and the process returns to step S101 to update the filter coefficient again until the filter converges.

Wherein, assuming that the number of filters is two, the following formula can be used to calculate the filter coefficients of all filters to obtain the filter coefficients of a total filter;

为第i个滤波器的第d个系数数据，i＝1或2，其中d＝[1,D]，而D为各个滤波器的当前滤波系数的划分数量，具体可根据实际情况进行设置，在此不做限制，例如可为2；

为第i个滤波器的第d个系数数据的第一矩阵的转置矩阵，

为总滤波器的滤波系数。

is the d-th coefficient data of the i-th filter, i=1 or 2, where d=[1, D], and D is the number of divisions of the current filter coefficients of each filter, which can be set according to the actual situation, There is no limit here, for example, it can be 2;

is the transpose matrix of the first matrix of the d-th coefficient data of the ith filter,

is the filter coefficient of the total filter.

In this implementation manner, a plurality of sub-remote-end signals are constructed based on the far-end signals, wherein the sub-remote-end signals are in a one-to-one correspondence with a plurality of filters, so as to use the plurality of sub-remote-end signals to train their corresponding filters respectively, and since The product of the filter coefficient lengths of the multiple filters is equal to the length of the far-end signal, and the total number of filter coefficients updated in this embodiment is smaller than the amount of filter coefficients in the existing “directly train a filter by using the far-end signal” scheme, and A plurality of filters in this embodiment can be updated at the same time, so that the speed of filter convergence can be improved.

In order to better describe the filter coefficient determination method of the present application, the following specific embodiments of filter coefficient determination are provided for illustrative illustration.

Example

The essence of adaptive filtering is to find a finite impulse response, so that the difference between the signal obtained by convolving the response with the far-end signal and the target echo signal is the smallest, namely:

为待估计量；h(n) is the received echo signal, d(n) is the target echo, x(n) is the far-end signal,

to be estimated;

Generally speaking, for the near-end acquisition signal can be expressed as:

y(n)=ω ^T x(n)+v(n) (2)

y(n) represents the near-end acquisition signal, that is, the input signal, v(n) represents the near-end signal, and ω ^T x(n) represents the analog echo signal;

Usually, the LMS algorithm is used to estimate ω, that is:

where μ(n) is the step size, and e(n) is the error signal;

In this embodiment, two filters are used to update the filter coefficients, and two sub-remote signals can be constructed first by using the current filter coefficients and the remote signals of the two filters;

表示克罗内克乘，其中D为经验系数，通常设为2，

为单位矩阵，L_i为第i个滤波器的滤波系数长度；where i=1,2, where L ₁ ×L ₂ =N;

represents the Kronecker multiplication, where D is the empirical coefficient, usually set to 2,

is the identity matrix, L _i is the filter coefficient length of the ith filter;

The currently filtered error signals of the two filters in this scheme can be expressed as the following two formulas respectively:

Among them, e ₁ (n) and e ₂ (n) are completely equal. The purpose of distinguishing e ₁ (n) and e ₂ (n) here is to be consistent with the two sub-remote signals split previously.

According to equation (4), the iteration of the adaptive filter can be transformed into:

And equations (11), (12) can be calculated in equations (9), (10) to obtain the next error signal;

Equations (9), (10) are called the prior error of adaptive filtering, and the posterior error is calculated as follows:

Subtracting equations (13) and (14) from equations (9) and (10) respectively, and using the conversion formulas of equations (11) and (12), we can get:

Equation (15) and Equation (16) take the expectation and make it equal to the expectation of the near-end signal, that is:

then you can get:

ξ is a constant, usually set to 0.0001, to ensure that the denominator does not appear 0;

After calculating the step size μ ₁ (n) and the step size μ ₂ (n) of the two filters based on formula (19) and formula (20), respectively, the calculated step size μ ₁ (n) and step size can be converted into μ ₂ (n) is substituted into equations (11) and (12) respectively to calculate the next filter coefficients of the two filters.

If the calculated next filter coefficients of the two filters converge, the following formula can be used to calculate the next filter coefficients of the two filters to obtain the filter coefficients of the total filter:

Please refer to FIG. 2 , which is a schematic flowchart of an embodiment of an echo cancellation method of the present application. It should be noted that, if there is substantially the same result, the present embodiment is not limited to the sequence of the processes shown in FIG. 2 . In this embodiment, the echo cancellation method includes the following steps:

S301: Input the received far-end audio signal as a far-end signal to an adaptive filter to obtain an analog echo signal.

Wherein, the filter coefficients in the adaptive filter are determined according to the above-mentioned filter coefficient determination method.

S302: Obtain a signal after echo cancellation processing based on the analog echo signal and the near-end acquisition signal.

Please refer to FIG. 3 , which is a schematic structural diagram of an embodiment of the electronic device of the present application. The electronic device 10 includes a processor 12 for executing instructions to implement the filter coefficient determination method and the echo cancellation method described above. For the specific implementation process, please refer to the description of the above-mentioned implementation manner, which will not be repeated here.

The processor 12 may also be referred to as a CPU (Central Processing Unit, central processing unit). The processor 12 may be an integrated circuit chip with signal processing capability. Processor 12 may also be a general purpose processor, digital signal processor (DSP), application specific integrated circuit (ASIC), field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components . A general purpose processor may be a microprocessor or the processor 12 may be any conventional processor or the like.

The electronic device 10 may further include a memory 11 for storing instructions and data required for the operation of the processor 12 .

The processor 12 is configured to execute instructions to implement the method provided by any of the above-mentioned embodiments of the filter coefficient determination method and the echo cancellation method of the present application and any non-conflicting combination.

Please refer to FIG. 4 , which is a schematic structural diagram of a computer-readable storage medium in an embodiment of the present application. The computer-readable storage medium 30 of this embodiment of the present application stores instructions/program data 31, and when the instruction/program data 31 is executed, implements any of the embodiments of the method for determining filter coefficients and the method for echo cancellation of the present application and any non-conflicting combination provided method. Wherein, the instruction/program data 31 can be stored in the above-mentioned storage medium 30 in the form of a program file in the form of a software product, so that a computer device (may be a personal computer, a server, or a network device, etc.) or a processor (processor) Perform all or part of the steps of the methods of the various embodiments of the present application. The aforementioned storage medium 30 includes: U disk, removable hard disk, Read-Only Memory (ROM, Read-Only Memory), Random Access Memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program codes , or terminal devices such as computers, servers, mobile phones, and tablets.

In the several embodiments provided in this application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are only illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods, for example, multiple units or components may be combined or integrated. to another system, or some features can be ignored, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.

The above are only the embodiments of the present application, and are not intended to limit the scope of the patent of the present application. Any equivalent structure or equivalent process transformation made by using the contents of the description and drawings of the present application, or directly or indirectly applied in other related technical fields, All are similarly included in the scope of patent protection of the present application.

Claims (11)

1. a filter coefficient determination method, is characterized in that, described method comprises: Constructing multiple sub-remote signals based on the remote signal; Taking the error signal obtained by the next filtering of each of the filters equal to the near-end signal as the calculation condition, the step size of each of the filters is calculated based on the sub-end signal corresponding to each of the filters. The product of the filter coefficient lengths of the filter is equal to the length of the far-end signal; The next filter coefficient for each of the filters is calculated based on the step size of each of the filters. 2. The filter coefficient determination method according to claim 1, wherein the step of constructing a plurality of sub-remote signals based on the remote signal comprises: The calculation is performed based on the far-end signal and the current filter coefficients of other filters to obtain the sub-remote signal corresponding to each of the filters. 3. The filter coefficient determination method according to claim 2, wherein the step of constructing a plurality of sub-remote signals based on the remote signal comprises: Construct two sub-remote signals based on the remote signal; The two sub-remote signals are in one-to-one correspondence with the two filters, and the product of the filter coefficient lengths of the two filters is equal to the length of the remote signal. 4. filter coefficient determination method according to claim 3, is characterized in that, the described step of calculating based on the current filter coefficient of far-end signal and other filters comprises: Kronecker multiplication is performed on the current filter coefficients of the other filters and the identity matrix to obtain the first matrix of the other filters; Multiplying the first matrix of the other filters and the far-end signal to obtain a sub-remote signal corresponding to each of the filters. 5. The method for determining filter coefficients according to claim 1, wherein the calculation condition is that the error signal obtained by the next filtering of each of the filters is equal to the near-end signal, and based on each of the filters The step of calculating the step size of each of the filters for the corresponding sub-remote signals includes: Substitute the near-end signal as the error signal of the next filter into the first relational formula of each of the filters, and the first relational formula is the error signal of the next filtering of each of the filters, the current filtered error signal, The relationship between the error signal, the sub-remote signal, and the step size is formulated to obtain the step size of each of the filters. 6. filter coefficient determination method according to claim 5, is characterized in that, the described first relational formula of each filter is to utilize the error signal of next filter coefficient calculation formula of each filter, next filter The calculation formula and the current filtered error signal calculation formula are calculated. 7. filter coefficient determination method according to claim 5, is characterized in that, described first relational formula of ith filter is as follows:

Among them, v(n) is the near-end signal, e _i (n) is the error signal currently filtered by the ith filter, m _i (n) is the sub-end signal corresponding to the ith filter,

is the transposed matrix of the sub-remote signal corresponding to the ith filter, μ _i (n) is the step size of the ith filter, and ξ is a preset constant. 8. The filter coefficient determination method according to claim 1, wherein the step of calculating the next filter coefficient of each of the filters based on the step size of each of the filters comprises: The filter coefficients of all filters are fused to obtain a total filter coefficient, so as to process the far-end signal through the total filter coefficient to obtain an analog echo signal of the far-end signal. 9. A method for echo cancellation, characterized in that the method comprises: The received far-end audio signal is input to the adaptive filter as a far-end signal to obtain an analog echo signal, wherein the filter coefficient in the adaptive filter is according to the filtering described in any one of claims 1-7 The method for determining the coefficient of the device is determined; An echo-cancelled signal is obtained based on the analog echo signal and the near-end acquisition signal. 10. An electronic device, characterized in that the electronic device comprises a processor; the processor is configured to execute instructions to implement the steps of the method according to any one of claims 1-9. 11. A computer-readable storage medium on which programs and/or instructions are stored, characterized in that, when the programs and/or instructions are executed, the steps of the method according to any one of claims 1-9 are implemented.

Images