Beamforming method, device, storage medium and computer program product

Abstract

This application discloses a beamforming method, device, storage medium, and computer program product, relating to the field of signal processing technology. The method comprises: obtaining a first signal obtained by processing each input signal through a GSC upper branch; obtaining a second signal obtained by processing each input signal through a blocking matrix of a GSC lower branch; filtering a signal related to the first signal from the second signal to obtain a third signal; and inputting the third signal into a subsequent module of the GSC lower branch, so that the subsequent module of the GSC processes the first and third signals to obtain a beamformed output signal. This application aims to address the problem of target signal damage caused by target signal leakage in the GSC lower branch.

Description

Technical Field

[0001] The present application relates to the field of signal processing technology, and in particular to a beamforming method, device, storage medium, and computer program product. Background Art

[0002] Beamforming technology combines multiple signals, suppresses signals in non-target directions, and enhances signals in the target direction. This allows for focused signal capture in a specific direction, effectively improving the signal-to-noise ratio (SNR) of the received signal and also reducing noise. The generalized sidelobe canceler (GSC) is an adaptive beamforming technology based on sensor arrays. Its core concept is to decompose the beamforming problem into two parts: fixed beamforming and adaptive interference cancellation, thereby improving computational efficiency and satisfying constraints.

[0003] However, an inherent problem of GSC is the signal leakage of the lower branch. Due to the accuracy of the steering vector and blocking matrix estimation, the target signal in the lower branch inevitably leaks, which causes a certain degree of target signal damage when subtracted from the upper and lower branch signals.

[0004] The above content is only used to assist in understanding the technical solution of this application and does not constitute an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of this application is to provide a beamforming method, device, storage medium and computer program product, which aim to solve the problem of target signal damage caused by leakage of target signal in the GSC lower branch.

[0006] To achieve the above objectives, the present application proposes a beamforming method, which includes:

[0007] Obtaining a first signal obtained by processing each input signal through an upper branch of a generalized sidelobe canceler GSC;

[0008] Obtaining a second signal obtained by processing the input signals through a blocking matrix of a lower branch of the GSC;

[0009] filtering out a signal related to the first signal from the second signal to obtain a third signal;

[0010] The third signal is input to a subsequent module of the GSC lower branch, so that the first signal and the third signal are processed by the subsequent module of the GSC to obtain a beamforming output signal.

[0011] Optionally, the step of filtering out a signal related to the first signal from the second signal to obtain a third signal includes:

[0012] calculating filter coefficients based on the first signal;

[0013] Calculating a fourth signal according to the filter coefficient and the second signal, wherein the fourth signal is an estimate of a signal in the second signal that is related to the first signal;

[0014] The fourth signal is filtered out from the second signal to obtain a third signal.

[0015] Optionally, the step of calculating filter coefficients according to the first signal includes:

[0016] calculating a cross-correlation vector between the first signal and the second signal;

[0017] calculating an autocorrelation matrix of the second signal;

[0018] Filter coefficients are calculated based on the mutual correlation vector and the autocorrelation matrix.

[0019] Optionally, the step of obtaining the second signal obtained by processing the input signals through the blocking matrix of the GSC lower branch includes:

[0020] calculating a signal energy of the second signal;

[0021] setting a suppression strength parameter according to the signal energy, wherein the suppression strength parameter is used to control the strength with which the signal related to the first signal is filtered out from the second signal, and the greater the signal energy, the smaller the strength with which the signal related to the first signal is filtered out from the second signal according to the suppression strength parameter;

[0022] The step of filtering out the signal related to the first signal from the second signal to obtain the third signal comprises:

[0023] A signal related to the first signal is filtered out from the second signal according to the suppression strength parameter to obtain a third signal.

[0024] Optionally, the suppression strength parameter includes a lower limit threshold for limiting a lower limit of a gain coefficient and / or a bias for adjusting a magnitude of the gain coefficient, wherein the gain coefficient is used to filter out a signal related to the first signal from the second signal to obtain the third signal;

[0025] The step of setting the suppression strength parameter according to the signal energy comprises:

[0026] The lower threshold and / or bias are set according to the signal energy, wherein the smaller the signal energy is, the smaller the lower threshold is, and the smaller the signal energy is, the smaller the bias is.

[0027] Optionally, the step of filtering out a signal related to the first signal from the second signal to obtain a third signal includes:

[0028] performing timing alignment on the second signal and the first signal;

[0029] A signal related to the first signal is filtered out from the second signal after time alignment to obtain a third signal.

[0030] Optionally, the beamforming method is applied to a device with a microphone array, and before the step of obtaining the first signal obtained by processing each input signal by a fixed beamformer of an upper branch of a generalized sidelobe canceller GSC, the method further includes:

[0031] Acquire the input signals collected by the microphone array.

[0032] In addition, to achieve the above-mentioned objectives, the present application also proposes a beamforming device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the beamforming method described above.

[0033] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium. A computer program is stored on the storage medium, and when the computer program is executed by a processor, the steps of the beamforming method described above are implemented.

[0034] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of the beamforming method described above are implemented.

[0035] One or more technical solutions proposed in this application have at least the following technical effects:

[0036] This application adds a processing step after the blocking matrix of the GSC lower branch, using the first signal output by the upper branch as the reference signal, and filtering out the signal related to the first signal from the second signal output after being processed by the blocking matrix, thereby filtering out the signal related to the target signal, that is, filtering out the leaked target signal, thereby avoiding damage to the target signal when the upper and lower branch signals cancel each other out. This embodiment adopts a reverse approach, that is, using the second signal in the original reference channel as the main signal and the first signal in the original main channel as the reference signal, which is equivalent to filtering out the target signal as "noise" in reverse, thereby ultimately solving the target signal damage problem caused by the leakage of the target signal in the GSC lower branch. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0038] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0039] Figure 1 A schematic diagram of a flow chart of the first embodiment of the beamforming method of the present application;

[0040] Figure 2 A schematic diagram of a GSC process involved in the prior art;

[0041] Figure 3 This is a schematic diagram of an improved GSC process according to one embodiment of the present application;

[0042] Figure 4 This is a schematic diagram of another improved GSC process involved in one embodiment of the present application;

[0043] Figure 5 Schematic diagram of the device structure of the hardware operating environment involved in the beamforming method in the embodiment of the present application.

[0044] The purpose, features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0045] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0046] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0047] An inherent problem of GSC is the signal leakage of the lower branch. Due to the accuracy of the steering vector and blocking matrix estimation, the target signal in the lower branch inevitably leaks, which causes a certain degree of target signal damage when subtracted from the upper and lower branch signals.

[0048] In order to solve the above technical problems, the embodiment of the present application adds a processing step after the blocking matrix of the lower branch of the GSC, uses the first signal output by the upper branch as the reference signal, and filters out the signal related to the first signal from the second signal output after the blocking matrix processing, so as to filter out the signal related to the target signal, that is, to filter out the target signal leaked therein, thereby avoiding damage to the target signal when the upper and lower branch signals are offset. The scheme of this embodiment adopts a reverse approach, that is, the second signal in the original reference channel is used as the main signal, and the first signal in the original main channel is used as the reference signal, which is equivalent to filtering the target signal in reverse as "noise", thereby ultimately solving the target signal damage problem caused by the leakage of the target signal in the lower branch of the GSC.

[0049] The following is a first embodiment of the beamforming method of the present application. Figure 1 , Figure 1 This is a flow chart of the first embodiment of the beamforming method of this application. The beamforming method described in this embodiment is applicable to various array signal processing scenarios based on wave propagation. For example, it can be used to perform beamforming processing on audio signals in devices such as headphones and smart speakers, and can be used to perform beamforming processing on radar signals in devices such as vehicle-mounted radars and 5G base stations. The application scenarios are not limited in this embodiment. For ease of description, the following embodiments are described with "beamforming device" as the execution subject. In this embodiment, the beamforming method includes steps S10~S40:

[0050] Step S10: Acquire a first signal obtained by processing each input signal through the GSC upper branch.

[0051] Each input signal is a multi-channel signal collected and input by a sensor array. If the sensor array includes n array elements, n input signals are input. The sensor array can be a microphone array, a radar array, etc., which is not limited in this embodiment.

[0052] GSC achieves target signal enhancement and interference suppression through joint processing of upper and lower branches. The upper branch (also known as the main channel) performs phase alignment and coherent superposition of signals from the target direction, initially enhancing the target signal (some interference and noise remain). The lower branch (also known as the reference channel) generates a reference signal consisting only of interference and noise when the target signal is blocked. This reference signal is used to offset the residual interference and noise in the main channel. The upper branch generally includes a fixed beamformer with a set of predefined fixed weights, which is responsible for initially enhancing the target signal. The processing of the upper branch can be expressed as:

[0053]

[0054] Among them, u(n) is the input signal of each channel, are the fixed weights of the fixed beamformer, satisfying the constraint , is the target direction vector.

[0055] The lower branch generally includes a blocking matrix (BM) and an adaptive interference canceller. The blocking matrix is ​​used to filter out the target signal while retaining interference and noise. The blocking matrix can be implemented using a matrix B that is orthogonal to the target direction vector. The adaptive interference canceller dynamically adjusts weights through an adaptive filter to estimate and eliminate interference in the main channel. The processing of the lower branch blocking matrix can be expressed as:

[0056]

[0057] Where B represents the blocking matrix, which satisfies the constraints: , that is, the column vector of the blocking matrix is Orthogonal.

[0058] The processing of the adaptive interference canceller can be expressed as:

[0059]

[0060] Among them, compared with the use of As the input of the adaptive interference canceller, in this embodiment, As the input of the adaptive interference canceller, Express The signal obtained after the subsequent step S30 processing is Represents the dynamic weight of the adaptive filter.

[0061] It should be noted that, in some feasible implementations, the upper branch may also include other modules besides the fixed beamformer, and the lower branch may also include other modules besides the blocking matrix and the adaptive interference canceller.

[0062] In a specific implementation, the GSC algorithm may be executed in the beamforming device of this embodiment or by other devices. The beamforming device obtains the execution result of the GSC algorithm from the other device, processes it, and then feeds back the processing result to the device.

[0063] In each embodiment, the signal obtained by processing each input signal by the fixed beamformer of the upper branch of the GSC is referred to as the first signal for distinction. The first signal still contains residual interference and noise, which needs to be offset by the reference signal of the lower branch.

[0064] Step S20: Acquire a second signal obtained by processing the input signals through the blocking matrix of the GSC lower branch.

[0065] The signal obtained by processing each input signal through the blocking matrix of the GSC's lower branch is called the second signal for differentiation. While the blocking matrix is ​​intended to block the target signal, a small amount of the target signal may still exist in the second signal, indicating target signal leakage. Therefore, when the lower branch reference signal is used to perform interference and noise cancellation on the main channel output signal, the target signal in the main channel output signal may also be cancelled out, causing target signal damage.

[0066] Step S30: Filter out the signal related to the first signal from the second signal to obtain a third signal.

[0067] In this embodiment, a beamforming device acquires a first signal and a second signal, filters out signals related to the first signal from the second signal, and obtains a remaining signal (referred to as a third signal for clarity). Because the first signal primarily contains the target signal, filtering out signals related to the first signal from the second signal can remove signals related to the target signal, thereby filtering out any leaked target signal. This prevents damage to the target signal caused by the cancellation of the upper and lower branch signals.

[0068] There are many ways to implement filtering out the signal related to the first signal from the second signal, which are not limited in this embodiment. A filter can be used to directly estimate the third signal from the second signal, which filters out the signal related to the first signal, or a filter can be used to first estimate the signal related to the first signal from the second signal, and then filter out the estimated signal from the second signal. For the former, for example, a gain coefficient can be calculated based on the degree of correlation between the first signal and the second signal, and the gain coefficient can be applied to the second signal, that is, multiplied with the second signal. The specific method of calculating the gain coefficient is not limited in this embodiment. For the latter, for example, in a feasible implementation, it can be implemented by designing an adaptive filter, inputting the first signal d(n) as a reference signal into the adaptive filter, and the second signal x(n) as the main input signal, and calculating ,in , is the filter weight vector, which is dynamically adjusted by the algorithm , so that the mean square error minimize, That is, the estimate of the signal in x(n) that is related to d(n), That is, the remaining signal after removing the signal related to the first signal, that is, the third signal.

[0069] Step S40: Input the third signal to a subsequent module of the GSC lower branch, so that the subsequent module of the GSC processes the first signal and the third signal to obtain a beamforming output signal.

[0070] The subsequent modules of the GSC lower branch refer to the modules after the blocking matrix in the original GSC algorithm, such as the adaptive interference canceller. That is, the third signal is further processed using the modules after the blocking matrix in the lower branch, and then the final output signal of the lower branch is offset from the first signal by the GSC cancellation module to finally obtain the beamformed output signal, or the beamformed output signal is obtained after some post-processing.

[0071] In this embodiment, a processing step is added after the blocking matrix of the GSC lower branch. The first signal output by the upper branch is used as the reference signal. Signals related to the first signal are filtered out from the second signal output after processing by the blocking matrix. This removes signals related to the target signal, that is, the leaked target signal, thereby preventing damage to the target signal caused by the cancellation of the upper and lower branch signals. This embodiment adopts a reverse approach, namely, using the second signal in the original reference channel as the main signal and the first signal in the original main channel as the reference signal. This is equivalent to filtering the target signal as "noise" in reverse, thereby ultimately solving the target signal damage problem caused by leakage of the target signal in the GSC lower branch.

[0072] In one feasible implementation, the beamforming method in this embodiment can be applied to a device with a microphone array, that is, the beamforming device can be a device with a microphone array. Before step S10, it also includes: obtaining the input signals collected by the microphone array. Furthermore, the beamforming device can use the upper branch of the GSC to process the input signals to obtain a first audio signal, use the blocking matrix of the lower branch of the GSC to process the input signals to obtain a second audio signal, filter out the signal related to the first audio signal from the second audio signal to obtain a third audio signal, and then use the subsequent module of the lower branch of the GSC to process the third audio signal, and use the subsequent module of the upper branch of the GSC to process the first audio signal, and finally output the beamforming output signal processed by the GSC, that is, the speech signal after enhancement processing. The first audio signal output by the upper branch is used as a reference signal, and the signal related to the first audio signal is filtered out from the second audio signal output after the blocking matrix processing to filter out the signal related to the target speech signal, that is, to filter out the target speech signal leaked therein, thereby avoiding speech damage when the upper and lower branch signals cancel each other out.

[0073] In a feasible implementation manner, the step S30 includes: performing time alignment on the second signal and the first signal; and filtering out a signal related to the first signal from the time-aligned second signal to obtain a third signal.

[0074] To avoid a delay between the first signal processed by the upper branch and the second signal processed by the lower branch blocking matrix, the first and second signals can be time-aligned. After the time alignment, subsequent signal filtering can be performed to obtain the third signal. There are many ways to implement time alignment, which are not limited in this embodiment. For example, a filter, such as an FIR (Finite Impulse Response) filter, can be used to phase-adjust the first signal to align it with the second signal.

[0075] In one feasible embodiment, the step of filtering signals related to the first signal from the second signal to obtain the third signal may include: performing bandpass filtering on the first signal to obtain a fifth signal, wherein the passband range of the bandpass filtering matches the spectral characteristics of the target signal being beamformed; and filtering signals related to the fifth signal from the second signal to obtain the third signal. In addition to the target signal, the first signal also contains some residual noise and interference. When filtering the target signal from the second signal using the first signal as a reference signal, to avoid filtering out the noise and interference in the first signal and thus affecting the beamforming effect, the first signal is bandpass filtered to retain signals within the frequency band where the target signal is primarily concentrated, thereby minimizing the filtering out of the residual noise and interference in the first signal. The passband range of the bandpass filtering can be pre-set based on the spectral characteristics of the target signal, or a matching passband range can be calculated by analyzing the spectral characteristics of the target signal in real time.

[0076] Based on the above first embodiment, a second embodiment of the beamforming method of the present application is proposed. In this embodiment, the same or similar contents as those of the above first embodiment can be referred to above and will not be described in detail. In this embodiment, step S30 includes S301 to S303:

[0077] Step S301: Calculate filter coefficients according to the first signal.

[0078] The signal related to the first signal in the second signal can be estimated by a filter. Specifically, the first signal can be used as a basis for determining the filter coefficient, so that the filter can accurately estimate the signal related to the first signal in the second signal.

[0079] In a specific implementation, different filters may be used to implement the method. When different filters are selected for implementation, the specific calculation method for calculating the filter coefficient according to the first signal may also be different, which is not limited in this embodiment.

[0080] Step S302: Calculate a fourth signal based on the filter coefficient and the second signal, wherein the fourth signal is an estimate of a signal in the second signal that is related to the first signal.

[0081] The estimation of the signal related to the first signal in the second signal is referred to as the fourth signal for distinction. When different filters are selected for implementation, the filter coefficients and the specific calculation method of calculating the fourth signal from the second signal may also differ, which is not limited in this embodiment.

[0082] Step S303: Filter the fourth signal from the second signal to obtain a third signal.

[0083] pass represents the fourth signal, x(n) represents the second signal, and the third signal .

[0084] like Figure 2 The figure shows the flow chart of the current GSC algorithm. The signal x(n) after passing through the blocking matrix B is directly input into the subsequent adaptive filter. ,like Figure 3 Shown is the addition of a filter after the blocking matrix of the GSC algorithm ,pass Estimate the fourth signal and filter the fourth signal from the second signal to obtain the third signal , and then input into the subsequent adaptive filter to be processed.

[0085] In a feasible implementation, a Wiener filter may be used. Specifically, step S301 includes steps S3011 to S3013:

[0086] Step S3011: Calculate the cross-correlation vector between the first signal and the second signal.

[0087] Step S3012: Calculate the autocorrelation matrix of the second signal.

[0088] Step S3013: Calculate filter coefficients based on the mutual correlation vector and the autocorrelation matrix.

[0089] The first signal is denoted as d(n) and the second signal is denoted as x(n); calculate the autocorrelation matrix of x(n) , reflecting the statistical characteristics of the lower branch signal; calculating the cross-correlation vector of x(n) and d(n) , used to establish an association with the target signal; filter coefficient Solve the following equation:

[0090]

[0091] This solution ensures that the fourth signal The mean square error is the smallest. Extract the leakage signal estimate from x(n) , which is the fourth signal, and then through The leakage signal is eliminated to obtain a third signal, which is input into the subsequent module of the lower branch.

[0092] In this embodiment, by calculating the filter coefficient based on the first signal, obtaining an estimate of the signal related to the first signal in the second signal (i.e., the fourth signal) based on the filter coefficient and the second signal, and then filtering the fourth signal from the second signal to obtain the third signal, the target signal leaked in the lower branch signal is filtered out, thereby avoiding damage to the target signal when the upper and lower branch signals cancel each other out.

[0093] Based on the above-mentioned first and / or second embodiments, a third embodiment of the beamforming method of the present application is proposed. In this embodiment, the same or similar contents as those of the above-mentioned first and second embodiments can be referred to the above introduction and will not be repeated hereafter. In this embodiment, considering that the signal-to-noise ratio of the input signal is different in quiet scenes and high-noise scenes, the degree of target signal leakage in the lower branch is also different. For different noise scenes, different suppression strengths are adopted for the target signal leaked in the lower branch. In high-noise scenes, a smaller suppression strength can be adopted, and in quiet scenes, a larger suppression strength is adopted. While improving the target signal damage existing in GSC, it does not affect the noise suppression effect of high-noise scenes. The step S20 includes steps S201~S202:

[0094] Step S201: Calculate the signal energy of the second signal.

[0095] The second signal is the signal obtained after the target signal in each input signal is blocked by the blocking matrix of the lower branch. It mainly includes interference and noise, and its signal energy reflects the noise environment of the current device. The signal energy of the second signal x(n) can be calculated using the following formula:

[0096]

[0097] X is the frequency domain signal after Fourier transform of x(n). The energy is calculated in the frequency band [0, N]. N can be set as needed. k represents the frequency, and l represents the frame index.

[0098] Step S202: setting a suppression strength parameter according to the signal energy, wherein the suppression strength parameter is used to control the strength of filtering out the signal related to the first signal from the second signal. The greater the signal energy, the smaller the strength of filtering out the signal related to the first signal from the second signal according to the suppression strength parameter.

[0099] The greater the signal energy, the more noise there is in the current scene and the smaller the proportion of the target signal. That is, in a high-noise scene, the proportion of the target signal is small, and the target signal leaked in the lower branch is small. When filtering the signal related to the first signal in the second signal, a smaller force is used to remove the leaked target signal, avoiding removing the main interference and noise in the lower branch and affecting the noise suppression effect of subsequent beamforming. Anyway, the smaller the signal energy, the less noise there is in the current scene and the larger the proportion of the target signal. That is, in a low-noise, quiet scene, the proportion of the target signal is large, and the target signal leaked in the lower branch is large. When filtering the signal related to the first signal in the second signal, a larger force is used to effectively remove the leaked target signal. At the same time, due to the small amount of noise and interference, the noise suppression effect of subsequent beamforming will not be affected by removing the main interference and noise in the lower branch.

[0100] The specific form of the suppression strength parameter is not limited in this embodiment. For example, a signal amplitude limit threshold can be used as the suppression strength parameter. After calculating an estimate of the signal related to the first signal in the second signal (the fourth signal), the signal amplitude limit threshold can be used to limit the amplitude of the fourth signal. The larger the signal amplitude limit threshold, the greater the effectiveness of filtering out the signal related to the first signal from the second signal. The smaller the signal amplitude limit threshold, the less effective the filtering out of the signal related to the first signal from the second signal.

[0101] The step S30 includes filtering out the signal related to the first signal from the second signal according to the suppression strength parameter to obtain a third signal.

[0102] The specific implementation of filtering out signals related to the first signal from the second signal based on the suppression strength parameter depends on the specific form of the suppression strength parameter and is not limited in this embodiment. For example, when a signal amplitude limit threshold is used as the suppression strength parameter, the amplitude of the fourth signal is limited by the signal amplitude limit threshold, and the amplitude-limited fourth signal is then filtered out from the second signal to obtain the third signal.

[0103] In one feasible embodiment, if the third signal is obtained by calculating the gain coefficient and applying the gain coefficient to the second signal, then the suppression strength parameter may include a lower threshold value for limiting the lower limit of the gain coefficient and / or a bias for adjusting the size of the gain coefficient. Accordingly, step S202 includes: setting the lower threshold value and / or bias according to the signal energy, wherein the smaller the signal energy, the smaller the lower threshold value, and the smaller the signal energy, the smaller the bias. It should be noted that by adopting a smaller lower threshold value or a smaller bias when the signal energy is small, it is equivalent to allowing more signals to be filtered out from the second signal, that is, it is possible to filter out signals related to the first signal from the second signal with greater strength. Conversely, by adopting a larger lower threshold value or a larger bias when the signal energy is small, it is possible to filter out signals related to the first signal from the second signal with less strength.

[0104] When the suppression strength parameter includes a lower threshold value for limiting the lower limit of the gain coefficient, after the gain coefficient is calculated, the gain coefficient can be compared with the lower threshold value. If it is greater than or equal to the lower threshold value, the gain coefficient is directly used to act on the second signal to obtain the third signal. If it is less than the lower threshold value, the lower threshold value is used as the gain coefficient to act on the second signal to obtain the third signal.

[0105] In the case where the suppression strength parameter includes a bias for adjusting the size of the gain coefficient, after the gain coefficient is calculated, the gain coefficient can be added to the bias and then applied to the second signal to obtain the third signal.

[0106] When the suppression strength parameter includes a lower threshold for limiting the lower limit of the gain coefficient and a bias for adjusting the size of the gain coefficient, after calculating the gain coefficient, the gain coefficient can be added with the bias and compared with the lower threshold. If it is greater than or equal to the lower threshold, the gain coefficient with the bias added is applied to the second signal to obtain the third signal. If it is less than the lower threshold, the lower threshold is used as the gain coefficient to act on the second signal to obtain the third signal.

[0107] In one feasible embodiment, when filtering out the signal related to the first signal from the second signal through steps S301-S303 of the second embodiment described above, it is necessary to calculate the coefficients of a filter (i.e., filter coefficients) applied to the second signal to calculate the signal related to the first signal in the second signal. In this case, the suppression strength parameter can be set to include an upper threshold for limiting the upper limit of the filter gain (hereinafter referred to as filter gain) and / or a bias for adjusting the magnitude of the filter gain. It should be explained that the filter herein refers to a filter used to estimate the signal related to the first signal from the second signal, with the second signal as input and the fourth signal as output. The filter coefficients refer to the basic parameters for constructing the filter transfer function, while the filter gain refers to the ratio of the amplitude of the filter output signal to the amplitude of the input signal, which describes the filter's effect on the signal amplitude. The filter gain is determined by the filter coefficients. The gain coefficient in the above embodiment is the gain coefficient of the third signal obtained by directly applying the second signal. Accordingly, step S202 includes setting the upper threshold and / or bias based on the signal energy, wherein the lower the signal energy, the larger the upper threshold, and the lower the signal energy, the larger the bias. It should be noted that, by adopting a larger upper threshold or a larger bias for the filter gain when the signal energy is small, it is equivalent to allowing the amplitude of the fourth signal estimated from the second signal to be higher, that is, it is possible to filter out the signal related to the first signal from the second signal with greater force. Conversely, by adopting a smaller upper threshold or a smaller bias for the filter gain when the signal energy is small, it is possible to filter out the signal related to the first signal from the second signal with less force.

[0108] In the case where the suppression strength parameter includes an upper threshold value for limiting the upper limit of the filter gain, after the filter coefficient is calculated through step S301, the filter gain corresponding to the filter coefficient can be compared with the upper threshold value. If it is less than or equal to the upper threshold value, steps S302~S303 are directly executed according to the filter coefficient. If it is greater than the upper threshold value, the filter coefficient is adjusted so that the filter gain corresponding to the adjusted filter coefficient is less than or equal to the upper threshold value, and steps S302~S303 are executed with the adjusted filter coefficient.

[0109] In the case where the suppression strength parameter includes a bias for adjusting the size of the filter gain, after the filter coefficient is calculated through step S301, the filter coefficient can be adjusted so that the filter gain corresponding to the adjusted filter coefficient is the sum of the original filter gain and the bias, and steps S302~S303 are executed after the adjustment.

[0110] In the case where the suppression strength parameter includes an upper threshold for limiting the upper limit of the filter gain and a bias for adjusting the size of the filter gain, after the filter coefficient is calculated through step S301, the filter coefficient can be adjusted so that the filter gain corresponding to the adjusted filter coefficient is the sum of the original filter gain and the bias, and the filter gain corresponding to the adjusted filter coefficient is compared with the upper threshold. If it is less than or equal to the upper threshold, steps S302~S303 are executed with the adjusted filter coefficient. If it is greater than the upper threshold, the filter coefficient is adjusted so that the filter gain corresponding to the adjusted filter coefficient is less than or equal to the upper threshold, and steps S302~S303 are executed with the adjusted filter coefficient.

[0111] In one feasible embodiment, when the suppression strength parameter includes an upper threshold for limiting the upper limit of the filter gain and a bias for adjusting the size of the filter gain, the step of filtering out the signal related to the first signal from the second signal according to the suppression strength parameter to obtain the third signal may include: calculating a filter coefficient based on the first signal; adjusting the filter coefficient so that the filter gain corresponding to the adjusted filter coefficient is the sum of the original filter gain and the bias, and comparing the filter gain corresponding to the adjusted filter coefficient with the upper threshold; if the filter gain corresponding to the adjusted filter coefficient is less than or equal to the upper threshold, calculating a fourth signal based on the adjusted filter coefficient and the second signal; if the filter gain corresponding to the adjusted filter coefficient is less than the upper threshold, adjusting the filter coefficient again so that the filter gain corresponding to the adjusted filter coefficient is less than or equal to the upper threshold, and calculating a fourth signal based on the adjusted filter coefficient and the second signal; wherein the fourth signal is an estimate of the signal related to the first signal in the second signal; and filtering the fourth signal from the second signal to obtain the third signal.

[0112] like Figure 4 As shown, a filter is added after the blocking matrix of the GSC algorithm Based on the energy of the second signal x(n), , calculate the suppression strength parameters based on the energy and adjust the filter .

[0113] An embodiment of the present application provides a beamforming device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the beamforming method of each of the above embodiments.

[0114] Reference below Figure 5 , which shows a schematic diagram of the structure of a beamforming device suitable for implementing the embodiment of the present application. The beamforming device in the embodiment of the present application may be a control unit in an RNC system. Figure 5 The beamforming device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0115] like Figure 5 As shown, the beamforming device may include a processing device 1001 (e.g., a DSP processor), which can perform various appropriate actions and processes according to a program stored in a read-only memory 1002 or a program loaded from a storage device 1003 into a random access memory 1004. Random access memory 1004 also stores various programs and data required for the operation of the beamforming device. Processing device 1001, read-only memory 1002, and random access memory 1004 are interconnected via a bus 1005. An input / output interface 1006 is also connected to the bus. Typically, the following systems may be connected to the input / output interface 1006: an input device 1007, such as a microphone or accelerometer; an output device 1008, such as a speaker or vibrator; storage device 1003, such as a magnetic tape or hard disk; and a communication device 1009. Communication device 1009 may allow the beamforming device to communicate with other devices wirelessly or wired to exchange data. While the figure illustrates a beamforming device with various systems, it should be understood that implementation or availability of all of the illustrated systems is not required. Greater or fewer systems may alternatively be implemented or provided.

[0116] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are performed.

[0117] Compared with the prior art, the beneficial effects of the beamforming device provided in the embodiment of the present application are the same as the beneficial effects of the beamforming method provided in the above embodiment, and the other technical features in the beamforming device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0118] It should be understood that the various parts disclosed in the embodiments of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any appropriate manner in any one or more embodiments or examples.

[0119] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0120] An embodiment of the present application provides a computer-readable storage medium having computer-readable program instructions (ie, a computer program) stored thereon, where the computer-readable program instructions are used to execute the beamforming method in the above embodiment.

[0121] The computer-readable storage medium provided in the embodiments of the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0122] The computer-readable storage medium may be included in the beamforming device, or may exist independently without being incorporated into the beamforming device.

[0123] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the beamforming device, the beamforming device performs the functions defined in the method of the embodiment disclosed in this application.

[0124] Computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0125] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of code, and the module, program segment or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, as well as the combination of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0126] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0127] The readable storage medium provided in the embodiment of the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., a computer program) for executing the above-mentioned beamforming method. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the embodiment of the present application are the same as the beneficial effects of the beamforming method provided in the above-mentioned embodiment, and are not further described here.

[0128] An embodiment of the present application further provides a computer program product, including a computer program, which implements the steps of the above-mentioned beamforming method when executed by a processor.

[0129] Compared with the prior art, the beneficial effects of the computer program product provided in the embodiments of the present application are the same as the beneficial effects of the beamforming method provided in the above embodiments, and are not described in detail here.

[0130] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A beamforming method, characterized in that: The beamforming method comprises: Obtaining a first signal obtained by processing each input signal through an upper branch of a generalized sidelobe canceler GSC; Obtaining a second signal obtained by processing the input signals through a blocking matrix of a GSC lower branch, where the second signal includes noise, an interference signal, and a leaked portion of the target signal; filtering a signal correlated with the first signal from the second signal to obtain a third signal, comprising calculating a filter coefficient based on the first signal; calculating a fourth signal based on the filter coefficient and the second signal; and filtering the fourth signal from the second signal to obtain the third signal, wherein the fourth signal is an estimate of a signal correlated with the first signal in the second signal, the correlated signal including the leaked target signal; The third signal is input to a subsequent module of the GSC lower branch, so that the first signal and the third signal are processed by the subsequent module of the GSC to obtain a beamforming output signal.

2. The beamforming method according to claim 1, wherein: The step of calculating the filter coefficient according to the first signal comprises: calculating a cross-correlation vector between the first signal and the second signal; calculating an autocorrelation matrix of the second signal; Filter coefficients are calculated based on the mutual correlation vector and the autocorrelation matrix.

3. The beamforming method according to claim 1, wherein: The step of obtaining the second signal obtained by processing the input signals through the blocking matrix of the GSC lower branch includes: calculating a signal energy of the second signal; setting a suppression strength parameter according to the signal energy, wherein the suppression strength parameter is used to control the strength with which the signal related to the first signal is filtered out from the second signal, and the greater the signal energy, the smaller the strength with which the signal related to the first signal is filtered out from the second signal according to the suppression strength parameter; The step of filtering out the signal related to the first signal from the second signal to obtain the third signal comprises: The step of filtering out a signal related to the first signal from the second signal according to the suppression strength parameter to obtain a third signal is performed.

4. The beamforming method according to claim 3, wherein: The suppression strength parameter includes a lower limit threshold for limiting a lower limit of a gain coefficient and / or a bias for adjusting a magnitude of the gain coefficient, wherein the gain coefficient is used to filter out a signal related to the first signal from the second signal to obtain the third signal; The step of setting the suppression strength parameter according to the signal energy comprises: The lower threshold and / or bias are set according to the signal energy, wherein the smaller the signal energy is, the smaller the lower threshold is, and the smaller the signal energy is, the smaller the bias is.

5. The beamforming method according to claim 1, wherein: Before the step of filtering out the signal related to the first signal from the second signal to obtain the third signal, the method further includes: performing timing alignment on the second signal and the first signal; The step of filtering out the signal related to the first signal from the second signal to obtain the third signal is performed on the second signal after the timing alignment.

6. The beamforming method according to claim 1, wherein: The beamforming method is applied to a device with a microphone array. Before the step of obtaining the first signal obtained by processing each input signal by a fixed beamformer of an upper branch of a generalized sidelobe canceler GSC, the method further includes: Acquire the input signals collected by the microphone array.

7. A beamforming device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the beamforming method according to any one of claims 1 to 6.

8. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the beamforming method according to any one of claims 1 to 6 are implemented.

9. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the beamforming method according to any one of claims 1 to 6 are implemented.

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