Method, Compensation Method, Apparatus, and Device for Determining Filter Coefficients for Amplitude Bandwidth Compensation

Abstract

The present application relates to a method for determining filter coefficients for amplitude bandwidth compensation, a compensation method, an apparatus, and a computer device. The method includes: obtaining a first amplitude-frequency response of a channel to be compensated for bandwidth by means of frequency sweeping; determining ideal filter coefficients of a filter for compensation based on the first amplitude-frequency response; obtaining various window functions, respectively truncating the ideal filter coefficients by means of the various window functions, and determining a target window function based on a first error between an amplitude-frequency response corresponding to the truncated ideal filter coefficients and an amplitude-frequency response corresponding to the ideal filter coefficients before truncation; and determining target filter coefficients based on the target window function and the ideal filter coefficients. By using this method, FPGA resources can be saved and a better compensation effect can be obtained.

Description

Technical Field

[0001] This application relates to the field of chip technology, and particularly to a method for determining filter coefficients for amplitude bandwidth compensation, a compensation method, a device, and a computer device. Background Art

[0002] Chip testing is an important process in the semiconductor manufacturing process, and its purpose is to ensure that the chip has no defects during the design and manufacturing processes and can work according to the expected functions and performances. A digital tester is a key device for chip testing in the semiconductor industry, which includes an analog-digital hybrid board that can support the testing of digital and analog signals to meet different types of testing requirements. Devices, traces, cables, etc. in the hardware circuit all have amplitude-frequency characteristics. In addition to a large attenuation of high-frequency components, the amplitude attenuation degree of intermediate-frequency components will also fluctuate up and down; and the resistance devices in different voltage ranges are different, which will result in different amplitude-frequency characteristics in different ranges. Therefore, when performing AC parameter testing, in order to ensure that the signal is not affected by the amplitude-frequency characteristics of the hardware channel itself, compensation should be performed for this arbitrary amplitude attenuation characteristic.

[0003] Commonly used are three signal compensation techniques: pre-emphasis, de-emphasis, and equalization. Pre-emphasis and de-emphasis cannot meet the attenuation compensation of arbitrary amplitude characteristics, and when there is crosstalk on the line, the enhancement of high-frequency components by pre-emphasis will cause the high-frequency crosstalk components to be amplified, thus exacerbating the harm of crosstalk. De-emphasis reduces the energy of the signal, which will make the signal more significantly affected by noise and may cause difficulties for the subsequent circuit module to identify the signal. Equalization can make up for the defects of pre-emphasis and de-emphasis. For example, in the method of an FIR digital filter, if high performance requirements are imposed on the compensation effect, the order of the FIR filter usually needs to be increased, which will increase the difficulty of implementing the FIR filter on an FPGA and consume more FPGA resources.

[0004] Therefore, there is an urgent need for a filter that can save FPGA resources and obtain a better compensation effect. Summary of the Invention

[0005] Based on this, in view of the above technical problems, it is necessary to provide a method for determining filter coefficients for amplitude bandwidth compensation, a compensation method, a device, and a computer device that can save FPGA resources and obtain a better compensation effect.

[0006] In a first aspect, this application provides a method for determining filter coefficients for amplitude bandwidth compensation, and the method includes:

[0007] Obtain a first amplitude-frequency response of the bandwidth to be compensated of the channel by means of frequency sweeping;

[0008] Determine ideal filter coefficients of a filter for compensation based on the first amplitude-frequency response;

[0009] Obtain each window function, truncate the ideal filter coefficients respectively through each of the window functions, and determine the target window function based on the first error between the amplitude-frequency response corresponding to the truncated ideal filter coefficients and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation;

[0010] Determine the target filter coefficients based on the target window function and the ideal filter coefficients.

[0011] In one embodiment, the determining the ideal filter coefficients of the filter for compensation based on the first amplitude-frequency response includes:

[0012] Determine the third amplitude-frequency response in the frequency domain of the filter for compensation based on the first amplitude-frequency response;

[0013] Expand the third amplitude-frequency response in the frequency domain to obtain the fourth amplitude-frequency response in the range of 0 to 2π in the frequency domain;

[0014] Convert the frequency response to the time domain to obtain the ideal filter coefficients.

[0015] In one embodiment, the expanding the second amplitude-frequency response in the frequency domain to obtain the frequency response in the range of 0 to 2π in the frequency domain includes:

[0016] Expand the second amplitude-frequency response in the frequency domain based on the type of the filter for compensation and the sampling frequency to obtain the third amplitude-frequency response in the range of 0 to π in the frequency domain;

[0017] Expand the third amplitude-frequency response based on the property that the amplitude-frequency response of a real coefficient filter is an even function and the phase-frequency characteristic is an odd function to obtain the frequency response in the range of 0 to 2π in the frequency domain.

[0018] In one embodiment, the obtaining each window function, truncating the ideal filter coefficients respectively through each of the window functions, and determining the target window function based on the first error between the amplitude-frequency response corresponding to the truncated ideal filter coefficients and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation includes at least one of the following:

[0019] Obtain each different known window function, truncate the ideal filter coefficients respectively through each of the known window functions, and determine the target window function based on the first error between the amplitude-frequency response corresponding to the ideal filter coefficients truncated by the known window function and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the known window function; or

[0020] By changing the Kaiser window parameters, different Kaiser windows are determined. Each of the Kaiser windows is used to truncate the ideal filter coefficients, and based on the first error between the amplitude-frequency response corresponding to the ideal filter coefficients after being truncated by the Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the Kaiser window, a target window function is determined.

[0021] In one embodiment, the method of changing the Kaiser window parameters to determine different Kaiser windows, truncating the ideal filter coefficients by each of the Kaiser windows, and determining the target window function based on the first error between the amplitude-frequency response corresponding to the ideal filter coefficients after being truncated by the Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the Kaiser window includes:

[0022] Determine a coarse grid search range based on the parameter range of the Kaiser window parameters;

[0023] Determine each first parameter value within the coarse grid search range with a first step size, and obtain an initial Kaiser window based on each of the first parameter values;

[0024] Calculate the second error corresponding to each of the initial Kaiser windows. The second error is determined by truncating the ideal filter coefficients by each of the initial Kaiser windows and based on the amplitude-frequency response corresponding to the ideal filter coefficients after being truncated by the initial Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the initial Kaiser window;

[0025] Determine a fine grid search range based on the initial Kaiser window corresponding to the second error that meets the first error requirement;

[0026] Determine each second parameter value within the fine grid search range with a second step size, and obtain a Kaiser window to be processed based on each of the second parameter values, where the second step size is smaller than the first step size;

[0027] Calculate the third error corresponding to each of the Kaiser windows to be processed. The third error is determined by truncating the ideal filter coefficients by each of the Kaiser windows to be processed and based on the amplitude-frequency response corresponding to the ideal filter coefficients after being truncated by the Kaiser window to be processed and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the Kaiser window to be processed;

[0028] Select the Kaiser window to be processed whose third error meets the second error requirement as the target window function.

[0029] In one embodiment, determining different Kaiser windows by changing Kaiser window parameters, truncating the ideal filter coefficients through each of the Kaiser windows respectively, and determining a target window function based on a first error between the amplitude-frequency response corresponding to the ideal filter coefficients after being truncated by the Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the Kaiser window includes:

[0030] Determine a target search range from the parameter range of the Kaiser window parameters based on the type and amplitude-frequency characteristics of the filter for compensation;

[0031] Determine each third parameter value within the target search range with a third step size, and obtain a target Kaiser window based on each of the third parameter values;

[0032] Calculate a fourth error corresponding to each of the target Kaiser windows respectively, where the fourth error is determined based on truncating the ideal filter coefficients through each of the target Kaiser windows and based on the amplitude-frequency response corresponding to the ideal filter coefficients after being truncated by the target Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the target Kaiser window;

[0033] Select the target Kaiser window whose fourth error meets the third error requirement as the target window function.

[0034] In one embodiment, the determining a target search range from the parameter range of the Kaiser window parameters based on the type and amplitude-frequency characteristics of the filter for compensation includes:

[0035] In the case where the amplitude spectrum flatness of the filter for compensation is less than a flatness threshold or the frequency component width is greater than a width threshold, determine, from the parameter range of the Kaiser window parameters, a parameter range whose distance from 0 is less than a first distance threshold as the target search range;

[0036] In the case where the amplitude accuracy of the filter for compensation is greater than a first accuracy threshold and the frequency accuracy is greater than a second accuracy threshold, determine, from the parameter range of the Kaiser window parameters, a parameter range whose distance from 2.5 is less than a second distance threshold as the target search range;

[0037] In the case where the amplitude accuracy of the filter for compensation is greater than a second accuracy threshold, determine, from the parameter range of the Kaiser window parameters, a parameter range whose distance from 5.44 is less than a third distance threshold as the target search range; where the second accuracy threshold is greater than the first accuracy threshold.

[0038] In one embodiment, the determining a target filter based on the target window function and the ideal filter coefficients includes:

[0039] Truncate the ideal filter coefficients by the target window function to obtain target compensation filter coefficients;

[0040] Perform normalization processing on the target compensation filter coefficients to obtain target filter coefficients.

[0041] In a second aspect, the present application further provides a method for compensating the amplitude bandwidth of a tester channel, and the method includes:

[0042] Based on the filter coefficient determination method for amplitude bandwidth compensation in any of the above embodiments, obtain target filter coefficients;

[0043] Obtain the tester channel time-domain data;

[0044] Compensate the amplitude bandwidth of the tester channel by convolving the channel time-domain data with the target filter coefficients.

[0045] In a third aspect, the present application further provides a device for determining filter coefficients for amplitude bandwidth compensation, and the device includes:

[0046] A first amplitude-frequency response determination module, configured to obtain the first amplitude-frequency response of the bandwidth to be compensated of the channel by means of frequency sweeping;

[0047] An ideal filter coefficient determination module, configured to determine the ideal filter coefficients of the filter for compensation based on the first amplitude-frequency response;

[0048] A target window function determination module, configured to obtain each window function, truncate the ideal filter coefficients respectively through each of the window functions, and determine the target window function based on the first error between the amplitude-frequency response corresponding to the truncated ideal filter coefficients and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation;

[0049] A first target filter coefficient determination module, configured to determine target filter coefficients based on the target window function and the ideal filter coefficients.

[0050] In a fourth aspect, the present application further provides a device for compensating the amplitude bandwidth of a tester channel, and the device includes:

[0051] A second target filter coefficient determination module, configured to obtain target filter coefficients based on the device for determining filter coefficients for amplitude bandwidth compensation in any of the above embodiments;

[0052] A channel time-domain data acquisition module, configured to acquire the tester channel time-domain data;

[0053] A compensation module, configured to compensate the amplitude bandwidth of the tester channel by convolving the channel time-domain data with the target filter coefficients.

[0054] In a fifth aspect, the present application further provides a computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the steps of the method in any one of the above embodiments are implemented.

[0055] In a sixth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method in any one of the above embodiments are implemented.

[0056] In a seventh aspect, the present application further provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps of the method in any one of the above embodiments are implemented.

[0057] The above method, apparatus, computer device, computer-readable storage medium, and computer program product for determining filter coefficients for amplitude bandwidth compensation obtain a first amplitude-frequency response of the bandwidth to be compensated for a channel by means of frequency sweeping; determine ideal filter coefficients of a filter for compensation based on the first amplitude-frequency response; obtain various window functions, truncate the ideal filter coefficients respectively through each of the window functions, and determine a target window function based on a first error between the amplitude-frequency response corresponding to the truncated ideal filter coefficients and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation; determine target filter coefficients based on the target window function and the ideal filter coefficients. In this way, for different amplitudes of the same analog-to-digital board card channel with different attenuation characteristics, without increasing the order of the FIR filter (that is, without increasing FPGA resources), the filter is optimized by combining frequency sampling and different window functions to obtain a better compensation effect, save FPGA resources, and can obtain a good compensation effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments of the present application or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other related drawings can be obtained without creative efforts based on these drawings.

[0059] Figure 1 It is a schematic flowchart of a method for determining filter coefficients for amplitude bandwidth compensation in an embodiment;

[0060] Figure 2 It is a flowchart of a step for determining ideal filter coefficients in an embodiment;

[0061] Figure 3Schematic diagram of a method for determining filter coefficients for amplitude bandwidth compensation in another embodiment;

[0062] Figure 4 Schematic diagram of a method for amplitude bandwidth compensation of a test machine channel in one embodiment;

[0063] Figure 5 Block diagram of a device for determining filter coefficients for amplitude bandwidth compensation in one embodiment;

[0064] Figure 6 Block diagram of a device for amplitude bandwidth compensation of a test machine channel in one embodiment;

[0065] Figure 7 Internal structure diagram of a computer device in one embodiment. Specific embodiments

[0066] In order to make the objectives, technical solutions, and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0067] In one embodiment, as Figure 1 shown, a method for determining a filter for amplitude bandwidth compensation is provided. In this embodiment, the method is illustrated by applying it to an analog-digital hybrid board. It can be understood that the method can also be applied to a host computer, an industrial control computer, or a communication intelligent device, and can also be applied to include calibration hardware. In this embodiment, the method includes the following steps:

[0068] S102: Obtain the first amplitude-frequency response of the bandwidth to be compensated for the channel by means of frequency sweeping.

[0069] The frequency sweeping method refers to obtaining signal characteristics at specific frequencies. In the present application, amplitude-frequency compensation is mainly performed. Therefore, the first amplitude-frequency response of the bandwidth to be compensated for the channel is obtained by means of frequency sweeping.

[0070] In the present application, key frequency points can be determined first, and then frequency sweeping is performed on the key frequency points to obtain the first amplitude-frequency response corresponding to the key frequency points, and then the first amplitude-frequency response corresponding to other frequency points is obtained by interpolation.

[0071] Specifically, the first amplitude-frequency characteristic of the bandwidth to be calibrated for the channel is obtained by means of frequency sweeping , where represents the amplitude corresponding to the L-th frequency, and the equally spaced frequency point vector , is the reference point for flatness calibration, and the frequency interval of each frequency point is , where the amplitude-frequency response is a characteristic that describes the amplitude response of a system or signal at different frequencies. To improve the calibration efficiency of the amplitude-frequency response, after selecting the key frequency points of key concern for frequency sweeping, a linear interpolation method is adopted to obtain the first amplitude-frequency response , where the first amplitude-frequency response includes L frequency points.

[0072] S104: Determine the ideal filter coefficients of the filter for compensation based on the first amplitude-frequency response.

[0073] The ideal filter coefficients are obtained based on the first amplitude-frequency response. The ideal filter coefficients are a concept in the time domain. First, the second amplitude-frequency response of the filter for compensation in the frequency domain is obtained from the first amplitude-frequency response, then the frequency response in the range of 0 to 2π in the frequency domain is obtained by expanding the second amplitude-frequency response in the frequency domain, and finally the frequency response is converted to the time domain to obtain the ideal filter coefficients.

[0074] S106: Obtain each window function, truncate the ideal filter coefficients respectively through each window function, and determine the target window function based on the first error between the amplitude-frequency response corresponding to the truncated ideal filter coefficients and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation.

[0075] Among them, the determination method of the target filter in this application can include two types, and the two types respectively correspond to different acquisition methods of the window function.

[0076] Among them, the design method of the target filter is to first give the required ideal filter frequency response , and then design a target filter frequency response to approximate . It can be designed in the time domain by the window function method or designed from the frequency domain by the frequency sampling method.

[0077] Among them, the ideal filter frequency response is a continuous frequency expression, and its corresponding discrete expression is .

[0078] The selection of the window function can include two methods. The first method is to select from known window functions. The second method is to determine different window functions by changing parameters. For the second method, the parameter change in this application can be determined by the parameter search method. The parameter search method can include at least two searches, and the step size of each search is different, that is, the precision of the parameters is different. The precision of the last search is determined based on the precision requirement, and the precision of other searches is determined based on the precision of the subsequent search. That is, the search precision at the beginning is the lowest, and then it approaches the precision requirement in turn to determine the optimal parameters.

[0079] In some alternative embodiments, various window functions are obtained, the ideal filter coefficients are truncated respectively by the various window functions, and a target window function is determined based on a first error between the amplitude-frequency response corresponding to the truncated ideal filter coefficients and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation, including at least one of the following: obtaining various different known window functions, truncating the ideal filter coefficients respectively by the various known window functions, and determining the target window function based on the first error between the amplitude-frequency response corresponding to the ideal filter coefficients truncated by the known window functions and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the known window functions; or by changing Kaiser window parameters, determining different Kaiser windows, truncating the ideal filter coefficients respectively by the various Kaiser windows, and determining the target window function based on the first error between the amplitude-frequency response corresponding to the ideal filter coefficients truncated by the Kaiser windows and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the Kaiser windows.

[0080] The first way to obtain a window function is to first design different known window functions with a length added based on the frequency sampling method to truncate the ideal filter coefficients to obtain multiple compensated filter coefficients. Optional types of known window functions include rectangular window, triangular window, Hamming window, Blackman window, Kaiser window, etc. Only the above window functions are listed in this embodiment, and other window functions may also be included in other embodiments.

[0081] Then calculate the first error between the amplitude-frequency responses corresponding to the multiple compensated filter coefficients (i.e., the amplitude-frequency response corresponding to the truncated ideal filter coefficients) and the amplitude-frequency response corresponding to the ideal filter coefficients, and finally select the window function with the smallest first error R as the target window function.

[0082] The second way to obtain a window function is a combined design of the frequency sampling method and the Kaiser window. By changing the flexibility of window function selection is improved. The expression of the Kaiser window function with a window length of N is:

[0083]

[0084] where is the first kind of modified Bessel function of the zero order. Changing can adjust the main lobe width and sidelobe level of the window function. The larger is, the narrower the window is, and the stronger the suppression ability for sidelobes is, but the main lobe width will increase and the spectral resolution will decrease. Therefore, for a window function, high spectral resolution and high sidelobe suppression ratio cannot be achieved at the same time. According to when the Kaiser window is equal to the rectangular window, when , perform a coarse grid search on (such as the first interval is 0.5, and in other embodiments, the first interval can also be other values) to find the value near the minimum point, and then refine the grid near the minimum point to perform a fine grid search (such as the second interval is 0.1, and in other embodiments, the second interval can also be other values, only need to ensure that the second interval is less than the first interval) to find the minimum value of the approximation error. This process can be continuously iterated and refined according to the accuracy requirements.

[0085] It should be noted that the search in this application can include at least two times. The accuracy of the last search is determined based on the accuracy requirements, and the accuracy of other searches is determined based on the accuracy of the subsequent search. That is, the search accuracy at the beginning is the lowest, and then it approaches the accuracy requirements in turn to determine the optimal .

[0086] Each time after determining the window function, truncate the ideal filter coefficients through each window function, and then select the window function with the smallest error as the target window function based on the first error between the amplitude-frequency response corresponding to the truncated ideal filter coefficients and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation.

[0087] S108: Determine the target filter coefficients based on the target window function and the ideal filter coefficients.

[0088] In one optional embodiment, determining the target filter coefficients based on the target window function and the ideal filter coefficients includes: truncating the ideal filter coefficients through the target window function to obtain the target compensation filter coefficients; performing normalization processing on the target compensation filter coefficients to obtain the target filter coefficients.

[0089] Specifically, select the target window function with the smallest truncation approximation error and multiply it by the ideal filter coefficients to obtain the final target compensation filter coefficients . That is

[0090]

[0091] Among them, in order to ensure that the DC point is not affected, normalize it to obtain the target filter coefficients .

[0092] The above method for determining a filter for amplitude bandwidth compensation obtains the first amplitude-frequency response of the bandwidth to be compensated for a channel by means of frequency sweeping; determines the ideal filter coefficients of the filter for compensation based on the first amplitude-frequency response; obtains various window functions, truncates the ideal filter coefficients respectively through the various window functions, and determines the target window function based on the first error between the amplitude-frequency response corresponding to the truncated ideal filter coefficients and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation; determines the target filter based on the target window function and the ideal filter coefficients. In this way, for different amplitudes of the same analog-to-digital board card channel, there are different attenuation characteristics. Without increasing the order of the FIR filter (that is, without increasing FPGA resources), the filter is optimized by combining frequency sampling and different window functions to obtain a better compensation effect, save FPGA resources, and can obtain a good compensation effect.

[0093] In one alternative embodiment, determining the ideal filter coefficients of the filter for compensation based on the first amplitude-frequency response includes: determining the second amplitude-frequency response of the filter for compensation in the frequency domain based on the first amplitude-frequency response; expanding the second amplitude-frequency response in the frequency domain to obtain the frequency response in the range of 0 to 2π in the frequency domain; converting the frequency response to the time domain to obtain the ideal filter coefficients.

[0094] Specifically, in combination with Figure 2 as shown in Figure 2 is a flowchart of the steps for determining the ideal filter coefficients in an embodiment.

[0095] Among them, determining the second amplitude-frequency response of the filter for compensation in the frequency domain based on the first amplitude-frequency response specifically includes: directly obtaining the ideal filter amplitude-frequency response , including L frequency points; it should be noted that the ideal filter amplitude-frequency response involved in this application in digital signal processing is discrete.

[0096] Then, the second amplitude-frequency response is sampled through frequency sampling to obtain the frequency response in the range of 0 to 2π.

[0097] In one alternative embodiment, expanding the second amplitude-frequency response in the frequency domain to obtain the frequency response in the range of 0 to 2π in the frequency domain includes: expanding the second amplitude-frequency response in the frequency domain based on the type of the filter for compensation and the sampling frequency to obtain the third amplitude-frequency response in the range of 0 to π in the frequency domain; expanding the third amplitude-frequency response based on the property that the amplitude-frequency response of a real coefficient filter is an even function and the phase-frequency characteristic is an odd function to obtain the frequency response in the range of 0 to 2π in the frequency domain (that is, the frequency response of the entire frequency band).

[0098] Among them, the sampling frequency can only be an integer multiple of is the number of sampling points. First, expand the second magnitude response according to the actual required compensation filter type and sampling frequency to obtain the discrete ideal third magnitude response . For example, if a low-pass filter is to be designed, then ; if it is to be designed as an all-pass filter type, then .

[0099] Then, based on the property that the magnitude response of a real-coefficient filter is an even function and the phase response is an odd function, obtain the frequency response of the discrete ideal filter over the entire frequency band , and the calculation expression is:

[0100]

[0101] Finally, convert the frequency response to the time domain to obtain the ideal filter coefficients in the time domain. For example, for the frequency response perform point inverse Fourier transform with the number of sampling points to obtain order ideal filter coefficients .

[0102] Among them, if the first method is adopted in this application, that is, truncating the ideal filter coefficients with different window functions, it can specifically include the following steps:

[0103] Truncate the ideal filter coefficients with different window functions (known) to obtain the compensation filter coefficients , perform point Fourier transform on the compensation filter coefficients to obtain . The ideal filter frequency response obtained above is . Select the window function corresponding to the minimum approximation error as the final window function . The calculation method of the approximation error is as follows:

[0104]

[0105] Among them, is the magnitude response corresponding to the compensation filter coefficients , and is the magnitude response corresponding to the ideal filter coefficients.

[0106] In one alternative embodiment, if the window function is determined by the second method, that is, the window function is searched in multiple steps, this embodiment takes the two-step search as an example for illustration, where the accuracies of the step sizes in the two-step search process are different. The accuracy of the step size in the second step is greater than that in the first step, that is, the step size in the second step is smaller than that in the first step. There are at least two ways to determine the search range in the first step of this application: The first way is to directly determine the coarse grid search range based on the parameter range of the Kaiser window parameters; the second way is to determine the target search range from the parameter range of the Kaiser window parameters based on the type and amplitude-frequency characteristics of the filter used for compensation.

[0107] Specifically, by changing the Kaiser window parameters, different Kaiser windows are determined, and the ideal filter coefficients are truncated by each Kaiser window respectively. Based on the first error between the amplitude-frequency response corresponding to the ideal filter coefficients after being truncated by the Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the Kaiser window, the target window function is determined, including: determining the coarse grid search range based on the parameter range of the Kaiser window parameters; determining each first parameter value within the coarse grid search range with the first step size, and obtaining the initial Kaiser window based on each first parameter value; calculating the second error corresponding to each initial Kaiser window respectively, where the second error is determined based on truncating the ideal filter coefficients by each initial Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients after being truncated by the initial Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the initial Kaiser window; determining the fine grid search range based on the initial Kaiser window corresponding to the second error that meets the first error requirement; determining each second parameter value within the fine grid search range with the second step size, and obtaining the Kaiser window to be processed based on each second parameter value, where the second step size is smaller than the first step size; calculating the third error corresponding to each Kaiser window to be processed respectively, where the third error is determined based on truncating the ideal filter coefficients by each Kaiser window to be processed and the amplitude-frequency response corresponding to the ideal filter coefficients after being truncated by the Kaiser window to be processed and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the Kaiser window to be processed; selecting the Kaiser window to be processed whose third error meets the second error requirement as the target window function.

[0108] Among them, the coarse grid search range in this embodiment is determined based on the parameter range of the Kaiser window parameters, where the parameter range of the Kaiser window parameters can be preset, and then each first parameter value is determined within the coarse grid search range with the first step size and the initial Kaiser window is obtained based on each first parameter value. In this way, the ideal filter coefficients are truncated by the initial Kaiser window, and the second error between the amplitude-frequency response corresponding to the ideal filter coefficients after being truncated and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated is calculated.

[0109] The first error requirement may be to select the second error with the smallest error, or other requirements, which are not specifically limited herein. In this application, the initial Kaiser window corresponding to the smallest second error is selected, and the fine grid search range is determined based on this initial Kaiser window. For example, the fine grid search range is obtained by floating within a certain range above and below the initial Kaiser window. For example, for the floating within a certain range above and below, for example, the fine grid search range is , where 0.5 here is only for illustration, and other values can also be taken in other embodiments. The larger this value is, the larger the fine grid search range is, and thus the search efficiency is reduced. The smaller this value is, the smaller the fine grid search range is, and thus the search efficiency is improved.

[0110] After determining the fine grid search range, each second parameter value is determined within the fine grid search range by the second step size, and then a new window function, that is, the Kaiser window to be processed, is determined based on the second parameter value. The ideal filter coefficients are truncated by the Kaiser window to be processed, and the third error between the amplitude-frequency response corresponding to the truncated ideal filter coefficients and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation is calculated.

[0111] The second error requirement may be to select the third error with the smallest error, or other requirements, which are not specifically limited herein. In this application, the Kaiser window to be processed corresponding to the smallest third error is selected as the target window function.

[0112] In one optional embodiment, different Kaiser windows are determined by changing the Kaiser window parameters. The ideal filter coefficients are respectively truncated by each Kaiser window, and the target window function is determined based on the first error between the amplitude-frequency response corresponding to the ideal filter coefficients truncated by the Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation by the Kaiser window, including: determining the target search range from the parameter range of the Kaiser window parameters based on the type and amplitude-frequency characteristics of the filter for compensation; determining each third parameter value within the target search range by the third step size, and obtaining the target Kaiser window based on each third parameter value; respectively calculating the fourth error corresponding to each target Kaiser window, where the fourth error is determined based on truncating the ideal filter coefficients by each target Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients truncated by the target Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation by the target Kaiser window; selecting the target Kaiser window whose fourth error meets the third error requirement as the target window function.

[0113] In this embodiment, the target search range is determined based on the type and amplitude-frequency characteristics of the filter for compensation, without the need for coarse grid search.

[0114] In one of the optional embodiments, based on the type and amplitude-frequency characteristics of the filter for compensation, a target search range is determined from the parameter range of Kaiser window parameters, including: when the amplitude spectrum flatness of the filter for compensation is less than the flatness threshold, or the frequency component width is greater than the width threshold, a parameter range with a distance less than the first distance threshold from 0 is determined as the target search range from the parameter range of Kaiser window parameters; when the amplitude accuracy of the filter for compensation is greater than the first accuracy threshold and the frequency accuracy is greater than the second accuracy threshold, a parameter range with a distance less than the second distance threshold from 2.5 is determined as the target search range from the parameter range of Kaiser window parameters; when the amplitude accuracy of the filter for compensation is greater than the second accuracy threshold, a parameter range with a distance less than the third distance threshold from 5.44 is determined as the target search range from the parameter range of Kaiser window parameters; where the second accuracy threshold is greater than the first accuracy threshold.

[0115] Specifically, after a preliminary analysis of the type and characteristics of the compensation filter required for the current channel, the type of window function needed can be determined more quickly, narrowing the range, improving the search efficiency, reducing the number of iterations. For example, when the amplitude spectrum is relatively flat or the frequency components are relatively wide, it is recommended to use a smaller , and the search range can be limited near 0 ( , 0 is equivalent to a rectangular window, and the rectangular window has the highest frequency resolution); if both amplitude accuracy and frequency accuracy are required, can be increased, and the range can be limited near 2.5; if higher amplitude accuracy is required, a larger is needed, and the range can be limited near 5.44 (5.44 is equivalent to a Hamming window, which has strong side lobe suppression ability).

[0116] After determining the target search range, the third parameter values are determined within the target search range with a third step size, and then a new window function, that is, the target Kaiser window, is determined based on the third parameter values. The ideal filter coefficients are truncated by the target Kaiser window, and the fourth error between the amplitude-frequency response corresponding to the truncated ideal filter coefficients and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation is calculated.

[0117] The third error requirement can be to select the fourth error with the smallest error, or other requirements, which are not specifically limited here. In this application, the target Kaiser window corresponding to the smallest fourth error is selected as the target window function.

[0118] For ease of understanding, as shown in Figure 3 Figure 3 ​A schematic flowchart of a method for determining a filter for amplitude bandwidth compensation in another embodiment. In this embodiment, first, the first amplitude-frequency response of the channel is obtained by frequency sweeping. Then, the second amplitude-frequency response of the filter for compensation required to calibrate the first amplitude-frequency response is calculated in the frequency domain. Then, the second amplitude-frequency response is extended to obtain the third amplitude-frequency response corresponding to 0 to π. Due to the properties of the amplitude-frequency response and phase-frequency response of a real coefficient filter, the frequency response in the frequency domain can be Fourier inverse-transformed to obtain the time-domain expression, that is, the ideal filter coefficients .

[0119] Subsequently, based on the ideal filter coefficients and the corresponding window function selection method, a target window function is generated.

[0120] Specifically, the first window function selection method can be to select the corresponding window function from known window functions, truncate the ideal filter coefficients using each window function, and obtain the approximation error R after truncation. The window function with the smallest approximation error R is selected as the target window function.

[0121] The second window function selection method is based on the Kaiser window, and the grid search method is used to determine the window function with the smallest approximation error R as the target window function. The grid search method includes two types: The first is to first determine the parameter range coarse grid search range based on the Kaiser window parameters, then determine the fine grid search range based on the coarse grid search range, and finally determine the target window function based on the fine grid search range. The second is to determine the target search range based on the type and amplitude-frequency characteristics of the compensated filter, and then determine the target window function based on the target search range. The specific method can be referred to above.

[0122] After determining the target window function, the final N - 1 order FIR compensation filter is calculated , and in order to ensure that the DC point is not affected, it is normalized .

[0123] In the above embodiment, when the FPGA resources are limited, without increasing the order of the FIR filter, the filter performance is optimized based on the window function, and the Kaiser window with the best attenuation compensation effect for the current channel amplitude gear can be found using the grid search method, improving flexibility and efficiency.

[0124] In one alternative embodiment, the present application also provides a method for compensating the amplitude bandwidth of a test machine channel, in combination with Figure 4 , this method includes:

[0125] S402: Obtain the target compensation filter coefficients based on the filter coefficient determination method for amplitude bandwidth compensation in any of the above embodiments.

[0126] S404: Obtain the time-domain data of the tester channel.

[0127] S406: Compensate the amplitude bandwidth of the tester channel by convolving the time-domain data of the channel with the target compensation filter coefficients.

[0128] Among them, during AC testing, after convolving the time-domain data of the tester channel (i.e., the AC data of the channel) with the target compensation filter coefficients, the channel will obtain AC amplitude broadband compensation.

[0129] It should be understood that although the steps in the flowcharts involved in the above embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0130] Based on the same inventive concept, the embodiments of the present application also provide a filter determination device for amplitude bandwidth compensation for implementing the filter determination method for amplitude bandwidth compensation involved above and a tester channel amplitude bandwidth compensation device for the tester channel amplitude bandwidth compensation method. The implementation solutions provided by this device to solve problems are similar to the implementation solutions described in the above method. Therefore, the specific limitations in one or more embodiments of the filter determination device for amplitude bandwidth compensation and the tester channel amplitude bandwidth compensation device provided below can refer to the limitations on the filter determination method for amplitude bandwidth compensation and the tester channel amplitude bandwidth compensation method in the above text, and will not be repeated here.

[0131] In an exemplary embodiment, as Figure 5 shown, a filter determination device for amplitude bandwidth compensation is provided, including: a first amplitude-frequency response determination module 501, an ideal filter coefficient determination module 502, a target window function determination module 503, and a first target filter determination module 504, where:

[0132] The first amplitude-frequency response determination module 501 is configured to obtain the first amplitude-frequency response of the bandwidth to be compensated of the channel by means of frequency sweeping;

[0133] An ideal filter coefficient determination module 502, configured to determine ideal filter coefficients of a filter for compensation based on a first amplitude-frequency response;

[0134] A target window function determination module 503, configured to obtain each window function, truncate the ideal filter coefficients respectively through each window function, and determine a target window function based on a first error between an amplitude-frequency response corresponding to the truncated ideal filter coefficients and an amplitude-frequency response corresponding to the ideal filter coefficients before truncation;

[0135] A first target filter determination module 504, configured to determine target filter coefficients based on the target window function and the ideal filter coefficients.

[0136] In one optional embodiment, the above-mentioned ideal filter coefficient determination module 502 is specifically configured to determine a second amplitude-frequency response of a filter for compensation in the frequency domain based on the first amplitude-frequency response; expand the second amplitude-frequency response in the frequency domain to obtain a frequency response in the range of 0 to 2π in the frequency domain; convert the frequency response to the time domain to obtain the ideal filter coefficients.

[0137] In one optional embodiment, the above-mentioned ideal filter coefficient determination module 502 is specifically configured to expand the second amplitude-frequency response in the frequency domain based on the type of the filter for compensation and the sampling frequency to obtain a third amplitude-frequency response in the range of 0 to π in the frequency domain; based on the property that the amplitude-frequency response of a real coefficient filter is an even function and the phase-frequency characteristic is an odd function, expand the third amplitude-frequency response to obtain a frequency response in the range of 0 to 2π in the frequency domain.

[0138] In one optional embodiment, the above-mentioned target window function determination module 503 is configured to determine the target window function based on the following method: obtain each different known window function, truncate the ideal filter coefficients respectively through each known window function, and determine the target window function based on a first error between an amplitude-frequency response corresponding to the ideal filter coefficients truncated by the known window function and an amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the known window function; or determine different Kaiser windows by changing Kaiser window parameters, truncate the ideal filter coefficients respectively through each Kaiser window, and determine the target window function based on a first error between an amplitude-frequency response corresponding to the ideal filter coefficients truncated by the Kaiser window and an amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the Kaiser window.

[0139] In one alternative embodiment, the above-mentioned target window function determination module 503 is specifically configured to determine a coarse grid search range based on the parameter range of Kaiser window parameters; determine each first parameter value within the coarse grid search range with a first step size, and obtain an initial Kaiser window based on each first parameter value; calculate the second error corresponding to each initial Kaiser window respectively, where the second error is determined based on truncating the ideal filter coefficients with each initial Kaiser window, and based on the amplitude-frequency response corresponding to the ideal filter coefficients truncated by the initial Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the initial Kaiser window; determine a fine grid search range based on the initial Kaiser window corresponding to the second error that meets the first error requirement; determine each second parameter value within the fine grid search range with a second step size, and obtain the Kaiser window to be processed based on each second parameter value, where the second step size is smaller than the first step size; calculate the third error corresponding to each Kaiser window to be processed respectively, where the third error is determined based on truncating the ideal filter coefficients with each Kaiser window to be processed, and based on the amplitude-frequency response corresponding to the ideal filter coefficients truncated by the Kaiser window to be processed and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the Kaiser window to be processed; select the Kaiser window to be processed whose third error meets the second error requirement as the target window function.

[0140] In one alternative embodiment, the above-mentioned target window function determination module 503 is specifically configured to determine a target search range from the parameter range of Kaiser window parameters based on the type and amplitude-frequency characteristics of the filter for compensation; determine each third parameter value within the target search range with a third step size, and obtain a target Kaiser window based on each third parameter value; calculate the fourth error corresponding to each target Kaiser window respectively, where the fourth error is determined based on truncating the ideal filter coefficients with each target Kaiser window, and based on the amplitude-frequency response corresponding to the ideal filter coefficients truncated by the target Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the target Kaiser window; select the target Kaiser window whose fourth error meets the third error requirement as the target window function.

[0141] In one alternative embodiment, the above-mentioned target window function determination module 503 is specifically configured to, when the amplitude spectrum flatness of the filter for compensation is less than the flatness threshold or the frequency component width is greater than the width threshold, determine the parameter range with a distance less than the first distance threshold from 0 in the parameter range of Kaiser window parameters as the target search range; when the amplitude accuracy of the filter for compensation is greater than the first accuracy threshold and the frequency accuracy is greater than the second accuracy threshold, determine the parameter range with a distance less than the second distance threshold from 2.5 in the parameter range of Kaiser window parameters as the target search range; when the amplitude accuracy of the filter for compensation is greater than the second accuracy threshold, determine the parameter range with a distance less than the third distance threshold from 5.44 in the parameter range of Kaiser window parameters as the target search range; where the second accuracy threshold is greater than the first accuracy threshold.

[0142] In one optional embodiment, the above-mentioned first target filter determination module 504 is specifically configured to truncate the ideal filter coefficients through a target window function to obtain target compensation filter coefficients; and perform normalization processing on the target compensation filter coefficients to obtain target filter coefficients.

[0143] In an exemplary embodiment, as Figure 6 shown, a test machine channel amplitude bandwidth compensation device is provided, including: a second target filter determination module 601, a channel time-domain data acquisition module 602, and a compensation module 603, where:

[0144] The second target filter determination module 601 is configured to obtain target compensation filter coefficients based on the filter coefficient determination device for amplitude bandwidth compensation in claim 11;

[0145] The channel time-domain data acquisition module 602 is configured to acquire test machine channel time-domain data;

[0146] The compensation module 603 is configured to compensate the test machine channel amplitude bandwidth by convolving the channel time-domain data with the target compensation filter coefficients.

[0147] Each module in the above-mentioned filter determination device for amplitude bandwidth compensation and the test machine channel amplitude bandwidth compensation device can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or stored in a memory in the computer device in the form of software, so as to facilitate the processor to call and execute the operations corresponding to each of the above modules.

[0148] In an exemplary embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 7As shown in the figure. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a method for determining a filter for amplitude bandwidth compensation and a method for amplitude bandwidth compensation of a test machine channel. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0149] Those skilled in the art can understand that Figure 7 the structure shown in the figure is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0150] In one embodiment, a computer device is further provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiments are implemented.

[0151] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by the processor, the steps in the above method embodiments are implemented.

[0152] In one embodiment, a computer program product is provided, including a computer program. When the computer program is executed by the processor, the steps in the above method embodiments are implemented.

[0153] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, artificial intelligence (AI) processors, etc., without limitation.

[0154] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope recorded in the present application.

[0155] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method for determining filter coefficients for amplitude bandwidth compensation, characterized in that, The method includes: Obtaining a first amplitude-frequency response of the bandwidth to be compensated for the channel by means of frequency sweeping; Determining ideal filter coefficients of a filter for compensation based on the first amplitude-frequency response; Obtaining each window function, respectively truncating the ideal filter coefficients through each of the window functions, and determining a target window function based on a first error between the amplitude-frequency response corresponding to the truncated ideal filter coefficients and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation; Determining target filter coefficients based on the target window function and the ideal filter coefficients; The obtaining each window function, respectively truncating the ideal filter coefficients through each of the window functions, and determining a target window function based on a first error between the amplitude-frequency response corresponding to the truncated ideal filter coefficients and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation includes at least one of the following: Obtaining each different known window function, respectively truncating the ideal filter coefficients through each of the known window functions, and determining a target window function based on a first error between the amplitude-frequency response corresponding to the ideal filter coefficients truncated by the known window function and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the known window function; or Determining different Kaiser windows by changing Kaiser window parameters, respectively truncating the ideal filter coefficients through each of the Kaiser windows, and determining a target window function based on a first error between the amplitude-frequency response corresponding to the ideal filter coefficients truncated by the Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the Kaiser window.

2. The method according to claim 1, wherein The determining ideal filter coefficients of a filter for compensation based on the first amplitude-frequency response includes: Determining a second amplitude-frequency response of the filter for compensation in the frequency domain based on the first amplitude-frequency response; Expanding the second amplitude-frequency response in the frequency domain to obtain a frequency response in the range of 0 to 2π in the frequency domain; Converting the frequency response to the time domain to obtain ideal filter coefficients.

3. The method according to claim 2, wherein The expanding the second amplitude-frequency response in the frequency domain to obtain a frequency response in the range of 0 to 2π in the frequency domain includes: Expanding the second amplitude-frequency response in the frequency domain based on the type of the filter for compensation and the sampling frequency to obtain a third amplitude-frequency response in the range of 0 to π in the frequency domain; Expanding the third amplitude-frequency response based on the property that the amplitude-frequency response of a real coefficient filter is an even function and the phase-frequency characteristic is an odd function to obtain a frequency response in the range of 0 to 2π in the frequency domain.

4. The method according to claim 1, characterized in that, The determining different Kaiser windows by changing Kaiser window parameters, respectively truncating the ideal filter coefficients through each of the Kaiser windows, and determining a target window function based on a first error between the amplitude-frequency response corresponding to the ideal filter coefficients truncated by the Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before being truncated by the Kaiser window includes: Determining a coarse grid search range based on the parameter range of the Kaiser window parameters; Determining each first parameter value within the coarse grid search range with a first step size, and obtaining an initial Kaiser window based on each of the first parameter values; Calculate the second error corresponding to each of the initial Kaiser windows respectively. The second error is determined based on truncating the ideal filter coefficients by each of the initial Kaiser windows and based on the amplitude-frequency response corresponding to the ideal filter coefficients after truncation by the initial Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation by the initial Kaiser window; Determine the fine grid search range based on the initial Kaiser window corresponding to the second error that meets the first error requirement; Determine each second parameter value within the fine grid search range with a second step size, and obtain the Kaiser window to be processed based on each second parameter value, where the second step size is smaller than the first step size; Calculate the third error corresponding to each of the Kaiser windows to be processed respectively. The third error is determined based on truncating the ideal filter coefficients by each of the Kaiser windows to be processed and based on the amplitude-frequency response corresponding to the ideal filter coefficients after truncation by the Kaiser window to be processed and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation by the Kaiser window to be processed; Select the Kaiser window to be processed whose third error meets the second error requirement as the target window function.

5. The method according to claim 1, characterized in that, The method of determining different Kaiser windows by changing the Kaiser window parameters, truncating the ideal filter coefficients by each of the Kaiser windows respectively, and determining the target window function based on the first error between the amplitude-frequency response corresponding to the ideal filter coefficients after truncation by the Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation by the Kaiser window includes: Determine the target search range from the parameter range of the Kaiser window parameters based on the type and amplitude-frequency characteristics of the filter for compensation; Determine each third parameter value within the target search range with a third step size, and obtain the target Kaiser window based on each third parameter value; Calculate the fourth error corresponding to each of the target Kaiser windows respectively. The fourth error is determined based on truncating the ideal filter coefficients by each of the target Kaiser windows and based on the amplitude-frequency response corresponding to the ideal filter coefficients after truncation by the target Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation by the target Kaiser window; Select the target Kaiser window whose fourth error meets the third error requirement as the target window function.

6. The method according to claim 5, characterized in that, The determining the target search range from the parameter range of the Kaiser window parameters based on the type and amplitude-frequency characteristics of the filter for compensation includes: In the case where the amplitude spectrum flatness of the filter for compensation is less than the flatness threshold or the frequency component width is greater than the width threshold, determine the parameter range whose distance from 0 is less than the first distance threshold from the parameter range of the Kaiser window parameters as the target search range; In the case where the amplitude accuracy of the filter for compensation is greater than the first accuracy threshold and the frequency accuracy is greater than the second accuracy threshold, determine the parameter range whose distance from 2.5 is less than the second distance threshold from the parameter range of the Kaiser window parameters as the target search range; When the amplitude accuracy of the filter for compensation is greater than a second accuracy threshold, a parameter range with a distance less than a third distance threshold from 5.44 is determined from the parameter range of the Kaiser window parameters as the target search range; wherein the second accuracy threshold is greater than the first accuracy threshold.

7. The method according to claim 1, characterized in that The determining the target filter coefficients based on the target window function and the ideal filter coefficients includes: Truncating the ideal filter coefficients by the target window function to obtain target compensation filter coefficients; Normalizing the target compensation filter coefficients to obtain target filter coefficients.

8. A method for compensating the channel amplitude bandwidth of a testing machine, characterized in that, The method includes: Based on the method for determining filter coefficients for amplitude bandwidth compensation according to any one of claims 1 to 7, obtaining target filter coefficients; Obtaining the channel time-domain data of the test machine; Compensating the amplitude bandwidth of the test machine channel by convolving the channel time-domain data with the target filter coefficients.

9. A filter determination device for amplitude bandwidth compensation, characterized in that The device includes: A first amplitude-frequency response determination module, configured to obtain a first amplitude-frequency response of the bandwidth to be compensated of the channel by means of frequency sweeping; An ideal filter coefficient determination module, configured to determine ideal filter coefficients of the filter for compensation based on the first amplitude-frequency response; A target window function determination module, configured to obtain each window function, truncate the ideal filter coefficients by each of the window functions respectively, and determine a target window function based on a first error between the amplitude-frequency response corresponding to the ideal filter coefficients after truncation and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation; A first target filter coefficient determination module, configured to determine target filter coefficients based on the target window function and the ideal filter coefficients; The target window function determination module is configured to obtain a target window function based on at least one of the following methods: obtaining each different known window function, truncating the ideal filter coefficients by each of the known window functions respectively, and determining a target window function based on a first error between the amplitude-frequency response corresponding to the ideal filter coefficients after truncation by the known window function and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation by the known window function; or By changing the Kaiser window parameters, determining different Kaiser windows, truncating the ideal filter coefficients by each of the Kaiser windows respectively, and determining a target window function based on a first error between the amplitude-frequency response corresponding to the ideal filter coefficients after truncation by the Kaiser window and the amplitude-frequency response corresponding to the ideal filter coefficients before truncation by the Kaiser window.

10. A test machine channel amplitude bandwidth compensation device, characterized in that, The device includes: A second target filter coefficient determination module, configured to obtain target filter coefficients based on the device for determining filter coefficients for amplitude bandwidth compensation according to claim 9; A channel time-domain data acquisition module, configured to acquire the channel time-domain data of the test machine; A compensation module, configured to compensate the amplitude bandwidth of the test machine channel by convolving the channel time-domain data with the target filter coefficients.

11. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

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