Simulation test method and system based on multi-cascaded filter and electronic device

Abstract

The application discloses a simulation test method and system based on a multi-cascaded filter and electronic equipment, and relates to the technical field of communication. The method comprises the following steps: extracting voltage gain values and phase angles of each frequency point from signal transfer function data; determining a target response function according to the voltage gain values and the phase angles, wherein the target response function is used for eliminating inherent characteristic influence factors in a simulation system; determining a multi-cascaded filter combination according to the target response function; determining an overall signal transfer function of the multi-cascaded filter combination according to coefficients of each filter in the multi-cascaded filter combination; and performing simulation test on an input signal through the cascaded filter combination after gain bias adjustment and phase compensation are performed on the overall transfer function. The application solves the technical problem that the signal simulation test efficiency is low due to the fact that the combination mode of the filter cannot be flexibly adjusted in the simulation process in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication, in particular to a simulation test method and system based on multi-cascaded filter and electronic equipment. BACKGROUND

[0002] In the design and optimization process of active noise cancellation (ANC) system, simulation technology plays a crucial role. Existing ANC simulation tools and platforms, such as Python-based programming environment or some dedicated software tools, can assist engineers to complete the verification and debugging of noise reduction algorithm to a certain extent, but these tools have several significant technical limitations, especially in adaptive filtering and parameter flexible adjustment.

[0003] For example, most existing tools only support preset filter types and fixed cascading methods, and cannot dynamically adjust the combination of filters according to the specific needs of ANC system. This means that when facing complex and variable noise reduction scenarios, engineers often need to repeatedly test multiple preset filter combinations to find the optimal solution, which greatly increases the debugging time and complexity.

[0004] In summary, due to the inability to provide flexible filter combinations, the existing ANC simulation technology significantly limits the efficiency and accuracy of signal simulation testing in the design and optimization process of complex ANC systems, and there is an urgent need for a more advanced and flexible simulation tool to overcome these challenges and improve the speed and quality of ANC technology research and development.

[0005] At present, no effective solution has been proposed to solve the above problems. SUMMARY

[0006] The embodiments of the present application provide a simulation test method and system based on multi-cascaded filter and electronic equipment to at least solve the technical problem that the efficiency of signal simulation testing is low due to the inability to adaptively and flexibly adjust the combination of filters in the simulation process in the prior art.

[0007] According to an aspect of the embodiments of the present application, a simulation test method based on a multi-cascaded filter is provided, comprising: extracting voltage gain values and phase angles of each frequency point from signal transfer function data; determining a target response function according to the voltage gain values and the phase angles, wherein the target response function is used to eliminate inherent characteristic influence factors in a simulation system; determining a multi-cascaded filter combination according to the target response function, wherein the multi-cascaded filter combination comprises at least one filter; determining an overall signal transfer function of the multi-cascaded filter combination according to coefficients of each filter in the multi-cascaded filter combination; and performing simulation test on an input signal through the cascaded filter combination after gain bias adjustment and phase compensation are performed on the overall signal transfer function.

[0008] Optionally, determining the target response function according to the voltage gain values and the phase angles comprises: converting the voltage gain values into linear domain voltage values and converting the phase angles into radian format; determining a frequency response function according to the linear domain voltage values and the phase angles in the radian format; determining system characteristic reference path information and noise control path information feedforward path information according to the frequency response function; and determining the target response function according to the system characteristic reference path data, the noise control path data feedforward path data.

[0009] Optionally, determining the target response function according to the system characteristic reference path data, the noise control path data feedforward path data comprises: calculating a difference between the noise control path data and the system characteristic reference path data to obtain a first function; calculating a difference between the feedforward path data and the system characteristic reference path data to obtain a second function; calculating a difference between the second function and the first function to obtain a third function; and calculating a ratio between the first function and the third function to obtain the target response function.

[0010] Optionally, after the target response function is determined according to the voltage gain values and the phase angles, a first curve and a second curve are determined according to the target response function, wherein the first curve is used to represent amplitude-frequency information in the target response function, and the second curve is used to represent phase-frequency information in the target response function, and the second curve is a curve after period jump elimination processing; and the first curve and the second curve are rendered and displayed.

[0011] Optionally, determining the overall signal transfer function of the multi-cascaded filter combination according to the coefficients of each filter in the multi-cascaded filter combination comprises: determining signal transfer functions of each filter according to the coefficients of each filter; and performing product calculation on the signal transfer functions of each filter to obtain the overall signal transfer function.

[0012] Optionally, before determining the overall signal transfer function of the multi-cascade filter combination according to the coefficients of each filter in the multi-cascade filter combination, the sampling frequency, the center frequency, the quality factor and the target gain of each filter in the multi-cascade filter combination are determined, wherein the sampling frequency is used to control the filter frequency response range, the center frequency is used to determine the key frequency point of the filter response, the quality factor is used to control the relationship between the bandwidth and the center frequency of the filter, and the target gain is used to adjust the amplitude enhancement or attenuation of the frequency band; the coefficients of each filter are determined according to the sampling frequency, the center frequency, the quality factor and the target gain of each filter.

[0013] Optionally, the coefficients of each filter are determined according to the sampling frequency, the center frequency, the quality factor and the target gain of each filter, comprising: determining the digital angular frequency of each filter according to the sampling frequency and the center frequency of each filter, wherein the digital angular frequency is used to map the analog frequency to the digital domain; determining the damping coefficient of each filter according to the digital angular frequency and the quality factor of each filter, wherein the damping coefficient is used to control the bandwidth and resonance characteristics of the filter; when any one filter in the multi-cascade filter combination belongs to a parametric equalization filter, the coefficients of the filter are determined according to the damping coefficient, the digital angular frequency and the target gain of the filter; when any one filter in the multi-cascade filter combination belongs to a frequency selective filter, the coefficients of the filter are determined according to the damping coefficient and the digital angular frequency of the filter.

[0014] Optionally, the gain bias adjustment and the phase compensation of the overall signal transfer function comprise: receiving the gain bias value and the phase bias value input by the user through the interactive interface; adjusting the gain bias of the overall signal transfer function according to the gain bias value; compensating the phase of the overall signal transfer function according to the phase bias value.

[0015] According to another aspect of the present application, there is also provided a simulation test system based on a multi-cascaded filter, comprising: a data import module configured to import single-group or multi-group signal transfer function data and extract voltage gain values and phase angles of each frequency point from the signal transfer function data; a target response calculation module connected to the data import module and configured to receive and process the signal transfer function data, and determine a target response function according to the voltage gain values and the phase angles, wherein the target response function is configured to eliminate inherent characteristic influence factors in the simulation system; a second-order filter module connected to the target response calculation module and configured to determine a multi-cascaded filter combination according to the target response function, and determine an overall signal transfer function of the multi-cascaded filter combination according to coefficients of each filter in the multi-cascaded filter combination, wherein the multi-cascaded filter combination comprises at least one filter; and a data compensation module connected to the second-order filter module and configured to perform gain bias adjustment and phase compensation on the overall signal transfer function, and perform simulation test on an input signal through the multi-cascaded filter combination.

[0016] According to another aspect of the present application, there is also provided a computer readable storage medium having a computer program stored therein, wherein the computer program, when executed, causes a device in which the computer readable storage medium is located to perform the simulation test method based on a multi-cascaded filter.

[0017] According to another aspect of the present application, there is also provided an electronic device, comprising one or more processors and a memory configured to store one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the simulation test method based on a multi-cascaded filter.

[0018] In the present application, there is provided a simulation test method based on a multi-cascaded filter, comprising: firstly extracting voltage gain values and phase angles of each frequency point from signal transfer function data, and then determining a target response function according to the voltage gain values and the phase angles, wherein the target response function is configured to eliminate inherent characteristic influence factors in the simulation system. Subsequently, a multi-cascaded filter combination is determined according to the target response function, wherein the multi-cascaded filter combination comprises at least one filter; and an overall signal transfer function of the multi-cascaded filter combination is determined according to coefficients of each filter in the multi-cascaded filter combination. Finally, after gain bias adjustment and phase compensation are performed on the overall signal transfer function, simulation test is performed on an input signal through the multi-cascaded filter combination.

[0019] From the above, through the deep analysis of the voltage gain value and the phase angle of the frequency point in the signal transfer function data, the application can accurately determine the target response function, which can effectively eliminate the inherent characteristic influence factor in the simulation system, and ensure that the simulation result is closer to the performance of the actual ANC system.

[0020] Secondly, based on the target response function, the application can flexibly select and combine at least one filter, such as but not limited to a peak notch filter, a low shelf filter, a high shelf filter, a low pass filter and a high pass filter. The ability to dynamically adjust the filter combination makes the simulation test process more closely meet the real needs of the ANC system, so that the type, parameter and cascade mode of the filter can be freely set according to the specific noise reduction scene, greatly improving the pertinence and efficiency of the test.

[0021] In addition, the application determines the overall signal transfer function in real time by calculating the coefficients of each filter in the multi-cascade filter combination. This means that each adjustment of the filter parameters can be immediately reflected in the final simulation result, without the need to re-run the entire simulation process, saving a lot of debugging time and improving the test experience of engineers. In the last stage of the simulation test, the application provides gain bias adjustment and phase compensation functions to ensure that the overall signal transfer function and the target response function are maximally matched in amplitude and phase, thereby eliminating the accumulation of errors in the test and further improving the accuracy and reliability of the simulation result.

[0022] Through the above technical related steps, the application realizes the adaptive and flexible adjustment of the combination of filters in the simulation test, effectively solving the problem of low test efficiency in the prior art. This method not only simplifies the debugging process of ANC system design, but also improves the consistency of simulation results and actual system response. BRIEF DESCRIPTION OF DRAWINGS

[0023] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:

[0024] Figure 1 is a flowchart of an optional simulation test method based on a multi-cascade filter according to an embodiment of the application;

[0025] Figure 2 is an architecture diagram of an optional simulation test system according to an embodiment of the application. DETAILED DESCRIPTION

[0026] In the following, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative effort should belong to the protection scope of the present application.

[0027] It should be noted that the terms "first", "second" and the like in the description and claims of the present application and the above drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the application described herein can be implemented in other than the order illustrated or described herein. In addition, the terms "comprise" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to the process, method, product or device.

[0028] It should also be noted that the information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) collected by the present application are information and data authorized by the user or authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of related data comply with relevant laws, regulations and standards in relevant regions, necessary security measures are taken, public order and good customs are not violated, and appropriate operation portals are provided for users to choose authorization or refusal. For example, interfaces are provided between the system and related users or agencies, and before obtaining relevant information, the interface needs to send an acquisition request to the aforementioned user or agency, and after receiving the consent information feedback from the aforementioned user or agency, the relevant information is acquired.

[0029] According to the embodiments of the present application, an embodiment of a simulation test method based on a multi-cascaded filter is provided. It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0030] In an alternative embodiment, a multi-cascaded filter based simulation test system (hereinafter referred to as simulation test system) can be used as the execution subject of the multi-cascaded filter based simulation test method of the present embodiment. The simulation test system can be a software system or a combination of software and hardware embedded system. It should be noted that, in addition to using the simulation test system as the execution subject of the method of the present embodiment, other forms of subjects such as devices and apparatuses can also be used to execute the method steps of the present embodiment. Those skilled in the art should know that the present embodiment does not particularly limit the specific type of the execution subject of the method.

[0031] For the convenience of description, the method steps will be described below with the simulation test system as the execution subject.

[0032] Figure 1 is a flowchart of an alternative multi-cascaded filter based simulation test method according to the present embodiment, as shown in Figure 1 , the method comprises the following steps:

[0033] Step S101, extracting the voltage gain value and phase angle of each frequency point from the signal transfer function data.

[0034] Optionally, the signal transfer function data can be saved in a target curve file. By selecting the path of importing the target curve file, the simulation test system can automatically identify the name of each document in the target curve file and determine the single or multiple sets of signal transfer function data in the target curve file.

[0035] Optionally, based on each set of signal transfer function data in the target curve file, the simulation test system can extract at least the following three signal paths:

[0036] System characteristic reference path ;

[0037] Noise control path ;

[0038] Feedforward path .

[0039] Optionally, the simulation test system can also extract the voltage gain value and phase angle of each frequency point from each set of signal transfer function data.

[0040] Step S102, determining the target response function according to the voltage gain value and the phase angle, wherein the target response function is used to eliminate the inherent characteristic influence factor in the simulation system.

[0041] Optionally, the target response function represents the frequency response characteristics that the ANC system is expected to achieve, including the gain and phase changes of the signal at different frequencies. The target response function construction process in this invention aims to eliminate the inherent characteristic influence factors introduced by hardware characteristics, measurement errors or algorithm biases in the simulation system, ensuring that the final simulation results can more truly reflect the performance of the ANC system.

[0042] Step S103, determining a multi-cascade filter combination according to the target response function, wherein the multi-cascade filter combination includes at least one filter.

[0043] Optionally, in the context of ANC (Active Noise Cancellation) system simulation and design, the target response function serves as a blueprint that bridges the ideal performance and actual implementation. Based on in-depth analysis of the target ANC performance, the target response function converts voltage gain values and phase angles into complex representations of frequency response to define the expected behavior of the ANC system in the frequency domain. Once the target response function is determined, the next key step is to determine a multi-cascade filter combination to achieve this target response function as accurately as possible in the digital domain. This process involves filter selection, parameter setting and optimization of cascade mode, aiming to simulate and approximate the target response function through a combination of a series of filters, thereby obtaining the required signal processing characteristics.

[0044] Step S104, determining the overall signal transfer function of the multi-cascade filter combination according to the coefficients of each filter in the multi-cascade filter combination.

[0045] Wherein, the determination of the multi-cascade filter combination is an iterative and optimization process, including the following core steps:

[0046] Filter type selection: based on the frequency response requirements in the target response function, select appropriate filters from a variety of filter types, such as peak notch filters, low shelf filters, high shelf filters, low pass filters and high pass filters. Each filter provides different gain and phase responses in a specific frequency range, so selecting the appropriate filter type for the target function requirements is the basis for achieving accurate response.

[0047] Filter parameter setting: for each filter, parameters such as center frequency, gain, quality factor (Q value) need to be set to ensure that the filter can process the signal according to the requirements of the target response function. The selection of these parameters needs to be fine and accurate, as they directly affect the frequency response shape and performance of the filter.

[0048] Filter cascade combination: The complex frequency response in ANC systems cannot be achieved by a single filter, so multiple filters need to be cascaded to form a filter combination. By appropriate cascading, the characteristics of different filters can be combined to achieve a wider and more complex target frequency response. When cascading filters, an important factor is to ensure that the overall frequency response after cascading is closest to the target response function, while maintaining the stability and computational efficiency of the system.

[0049] Construction of overall signal transfer function: The transfer function of the cascaded filters is obtained by multiplying the transfer functions of each filter. This means that the output of each filter serves as the input of the next filter, forming a complex signal processing chain as a whole. By cascading SOS (Second-Order Sections) form filters, the overall signal transfer function can be constructed, which defines the response characteristics of the ANC system to the input signal in the frequency domain.

[0050] It should be noted that according to the requirements of the target response function, the filter combination can be flexibly selected and configured to customize the filter parameters and cascading method for specific ANC scenarios and requirements, thereby improving the flexibility and adaptability of the simulation test process.

[0051] Secondly, the multi-cascaded filter combination can approximate the complex target frequency response shape, and through fine-tuning of filter parameters and cascading strategies, it can achieve fine control of ANC system performance and improve the accuracy and reliability of simulation testing.

[0052] In addition, the design method of multi-cascaded filters supports real-time parameter adjustment and feedback, allowing engineers to quickly iterate in the simulation environment and optimize the filter combination to meet the performance goals of the ANC system, thereby significantly shortening the debugging cycle and improving development efficiency.

[0053] In summary, the multi-cascaded filter combination design in this invention is a key step to achieve the target response function of the ANC system, which not only provides fine frequency response control but also brings higher adaptability and optimization potential to ANC system design. Through this method, the performance of the ANC system can be more effectively designed and tested, accelerating the product development process and improving the noise reduction effect and user experience of the final product.

[0054] Step S105, after gain bias adjustment and phase compensation of the overall signal transfer function, the input signal is simulated and tested through the cascaded filter combination.

[0055] Optionally, gain bias adjustment aims to fine-tune the magnitude response of the overall transfer function to eliminate or compensate for gain deviations occurring across the entire frequency spectrum or specific frequency bands. Such deviations can be caused by inaccuracies in the signal source, measurement equipment, or system losses that were not fully considered during the filter design process. Through gain bias adjustment, it is ensured that the gain response of the simulation result aligns with the target response function, thereby avoiding potential volume imbalances or excessive / insufficient noise reduction effects in practical applications.

[0056] Optionally, phase compensation is intended to correct the phase differences in the transfer function relative to the target response function. In ANC systems, precise phase control is crucial for the cancellation of noise signals. Any deviation in phase will affect the effectiveness of the system's noise reduction, especially when the signal phase crosses the ±180-degree boundary. Through the implementation of phase compensation, phase jumps caused by signal path delays, filter design errors, and other factors can be eliminated or minimized, ensuring that the ANC system can achieve optimal noise cancellation across the entire frequency band.

[0057] It should be noted that the process of adjusting the overall signal transfer function is an integrated application of the above-mentioned gain bias adjustment and phase compensation. By making necessary amplitude and phase modifications at the output of the transfer function, the system can better adapt to the target response function and provide more accurate ANC effects.

[0058] After completing the adjustment of the overall signal transfer function, the next step is to perform simulation testing on the input signal through the combination of cascaded filters. In this phase, the simulation system will pass the input signal through the designed filter cascade, process the signal according to the adjusted overall signal transfer function, and simulate the working state of the ANC system. By comparing the processed signal (original noise signal and noise-reduced signal), the noise reduction effect of the ANC system can be directly compared and evaluated for performance in various noise environments, and necessary parameter adjustments and optimizations can be made until the design target is achieved.

[0059] In an optional embodiment, the target response function is determined according to the voltage gain value and the phase angle, including: the simulation test system first converts the voltage gain value into a linear domain voltage value and converts the phase angle into a radian format. Then, the simulation test system determines a frequency response function according to the linear domain voltage value and the radian format phase angle; determines system characteristic reference path information and noise control path information feedforward path information according to the frequency response function, respectively. Finally, the simulation test system determines the target response function according to the system characteristic reference path data and the noise control path data feedforward path data.

[0060] Optionally, in order to determine the target response function, the simulation test system first performs voltage gain standardization processing, converts the voltage gain value in the logarithmic domain to a voltage value in the linear domain , and the conversion formula can refer to formula (1):

[0061]

[0062] The simulation test system also converts the phase angle to radians , and the conversion formula refers to formula (2):

[0063] (2)

[0064] Optionally, based on the above formula (1) and formula (2), the complex expression form of the frequency response function is determined, for example, referring to formula (3):

[0065] (3)

[0066] Optionally, in formula (3), j refers to the imaginary unit in the complex function, and formula (3) realizes the conversion from polar coordinates to rectangular coordinates.

[0067] Optionally, based on the determined frequency response function, the simulation test system can extract at least the following three signal path information from the signal transfer function data:

[0068] system characteristic reference path ;

[0069] noise control path ;

[0070] feedforward path .

[0071] Optionally, the simulation test system will determine the target response function according to the system characteristic reference path data, the noise control path data and the feedforward path data.

[0072] It is necessary to convert the voltage gain value from the logarithmic domain (such as dB units) to the linear domain, and convert the phase angle from degrees to radians. This conversion ensures the accuracy of subsequent mathematical operations, avoids simulation distortion caused by unit mismatch or scale conversion errors, and achieves more accurate frequency response modeling. By extracting and determining the data information of the system characteristic reference path, the noise control path, and the feedforward path respectively, the application can analyze the performance characteristics of each signal processing link in the ANC system in detail. The integrated analysis of this multi-path information provides a comprehensive understanding of the internal signal flow and processing characteristics of the ANC system, which helps to fine-tune each link and ensure the optimization of overall performance.

[0073] In addition, based on the previous frequency response function analysis and multi-path data refinement, the application can construct a highly accurate target response function. This function not only considers the noise suppression requirements of the ANC system, but also fully considers the characteristics of the system itself and the interaction between each path, providing a clear and quantifiable performance target for the simulation test of the ANC system. Through continuous comparison and debugging with this target response function, it can be ensured that the ANC system can accurately achieve the predetermined noise reduction effect in actual deployment.

[0074] In an optional embodiment, according to the system characteristic reference path data, the noise control path data The feedforward path data determines the target response function, including: the simulation test system can calculate the difference between the noise control path data and the system characteristic reference path data to obtain a first function; calculate the difference between the feedforward path data and the system characteristic reference path data to obtain a second function; calculate the difference between the second function and the first function to obtain a third function; calculate the ratio of the first function and the third function to obtain the target response function.

[0075] Optionally, the first function can be represented by the following formula (4):

[0076] (4)

[0077] Optionally, the second function can be represented by the following formula (5):

[0078] (5)

[0079] Optionally, the target response function is represented by the following formula (6):

[0080] (6)

[0081] Optionally, the first function is calculated based on the difference between the noise control path data and the system characteristic reference path data. The system characteristic reference path data typically reflects the frequency response characteristics of the ANC system hardware platform in the absence of noise input, while the noise control path data contains the response information of the system when processing noise signals. By calculating the difference between the two path data, the effective control response part of the noise control response due to the intervention of the ANC algorithm is essentially extracted. This difference, i.e. the first function, can determine the suppression effect of the ANC system on the noise signal, without being affected by the system hardware characteristics itself.

[0082] Similar to the first function, the second function is determined by calculating the difference between the feedforward path data and the system characteristic reference path data. The feedforward path is a signal processing path in the ANC system used to predict noise signals and compensate in advance. Unlike the first function, the second function focuses on the net effect of the feedforward path signal processing, which also needs to be separated from the effect of the system characteristic reference path to evaluate the pure effect of the feedforward control.

[0083] The calculation of the third function is achieved by comparing the difference between the second function and the first function. This step aims to further refine the difference between the noise control and the feedforward path in the ANC system, especially focusing on the relative difference between the noise control path and the feedforward path processing effect. This difference analysis is crucial for understanding the overall performance of the ANC system, as it reflects the synergy or potential conflict of the system in processing signals in terms of noise suppression and feedforward compensation.

[0084] Finally, by calculating the ratio of the first function and the third function, the target response function can be determined. The target response function takes into account the effects of noise suppression and signal compensation in the ANC system, reflecting the ideal frequency response characteristics of the system in processing noise and signals. This function not only defines the gain and phase response targets of the ANC system at different frequencies, but also provides clear indicators for subsequent filter design and system debugging.

[0085] In an optional embodiment, after determining the target response function according to the voltage gain value and the phase angle, the simulation test system can determine a first curve and a second curve according to the target response function, wherein the first curve is used to represent the amplitude-frequency information in the target response function, and the second curve is used to represent the phase-frequency information in the target response function, and the second curve is a curve after periodic jump elimination processing; the first curve and the second curve are rendered and displayed.

[0086] Optionally, after determining the target response function Afterwards, the simulation test bear can decompose the target response function into a magnitude frequency characteristic function (corresponding to the function expressed by the first curve described above) and a phase frequency characteristic function (corresponding to the function expressed by the second curve described above).

[0087] Optionally, the magnitude frequency characteristic function can be expressed by formula (7):

[0088] (7)

[0089] Optionally, the phase frequency characteristic function can be expressed by formula (8):

[0090] (8)

[0091] wherein, is a kind of winding function for phase unwrapping algorithm to eliminate period jump.

[0092] In an optional embodiment, before determining the overall signal transfer function of the multi-cascaded filter combination according to the coefficients of each filter in the multi-cascaded filter combination, the simulation test system can determine the sampling frequency, center frequency, quality factor and target gain of each filter in the multi-cascaded filter combination, wherein the sampling frequency is used to control the frequency response range of the filter, the center frequency is used to determine the key frequency point of the filter response, the quality factor is used to control the relationship between the bandwidth and the center frequency of the filter, and the target gain is used to adjust the amplitude enhancement or attenuation of the frequency band. Then, the simulation test system can determine the coefficients of each filter according to the sampling frequency, center frequency, quality factor and target gain of each filter.

[0093] Optionally, the sampling frequency can be expressed by the symbol , with the unit of Hz, wherein the sampling frequency is used to define the discretization time base of the digital system, and the sampling frequency can determine the frequency response range (0 to ) of the filter.

[0094] Optionally, the center frequency, also known as the cutoff frequency, can be expressed by the symbol , with the unit of Hz, wherein the center frequency can be used to determine the key frequency point (such as the peak frequency, the cutoff frequency) of the filter response.

[0095] Optionally, the quality factor Q is used to describe the relationship between the bandwidth and the center frequency of the filter. The quality factor can be used to control the selectivity of the filter, and the higher the Q value, the narrower the bandwidth.

[0096] Optionally, the gain G (in decibel form) of the filter can be converted into the target gain A (in linear form), and the conversion formula is formula (9):

[0097] (9)

[0098] Wherein, the target gain can be used to adjust the amplitude enhancement or attenuation of a specific frequency band.

[0099] In an alternative embodiment, the coefficients of each filter are determined according to the sampling frequency, the center frequency, the quality factor and the target gain of the filter, including: the simulation test system can determine the digital angular frequency of each filter according to the sampling frequency and the center frequency of the filter, wherein the digital angular frequency is used to map the analog frequency to the digital domain; the damping coefficient of each filter is determined according to the digital angular frequency and the quality factor of the filter, wherein the damping coefficient is used to control the bandwidth and resonance characteristics of the filter. When any one of the filters in the multi-cascaded filter combination belongs to a parametric equalization filter, the simulation test system can determine the coefficients of the filter according to the damping coefficient, the digital angular frequency and the target gain of the filter; when any one of the filters in the multi-cascaded filter combination belongs to a frequency selective filter, the simulation test system can determine the coefficients of the filter according to the damping coefficient and the digital angular frequency of the filter.

[0100] Optionally, at least five kinds of filters can be provided in the present application for combination to obtain a multi-cascaded filter combination, including:

[0101] a peak notch filter;

[0102] a low shelf filter;

[0103] a high shelf filter;

[0104] a low pass filter;

[0105] a high pass filter.

[0106] The above five kinds of filters can be freely selected and combined, and a maximum of 15 filters can be supported. The filter coefficients are calculated using standard design formulas (including parameters: center frequency, gain, Q value). The filter coefficients are cascaded through IIR Cascaded Second-Order Sections (SOS) Form I convolution operation to form the overall signal transfer function.

[0107] Optionally, among the above five kinds of filters, the peak filter, the notch filter, the low shelf filter and the high shelf filter can be classified as parametric equalization filters. The low pass filter and the high pass filter can be classified as frequency selective filters.

[0108] It should be noted that for the peak filter, the notch filter, the low shelf filter and the high shelf filter, the coefficients of the filter can be determined according to the damping coefficient, the digital angular frequency and the target gain of the filter.

[0109] For example:

[0110] For the peak / notch filter, its transfer function is referred to formula (10):

[0111] (10)

[0112] The design formula is as follows:

[0113]

[0114]

[0115]

[0116]

[0117] Wherein, : peak enhancement; : notch attenuation.

[0118] For the low shelf filter, its transfer function is referred to formula (11):

[0119] (11)

[0120] The design formula is as follows:

[0121]

[0122]

[0123]

[0124]

[0125]

[0126]

[0127]

[0128] Wherein, the characteristics of the low shelf filter include: low frequency band gain adjustment, used to enhance or attenuate signals below .

[0129] Optionally, the transfer function of the high shelf filter can be referred to formula (12):

[0130] (12)

[0131] The design formula is as follows:

[0132]

[0133]

[0134]

[0135]

[0136]

[0137]

[0138] The characteristics of the high shelf filter include: high frequency gain adjustment, which is used to enhance or attenuate signals higher than .

[0139] In an alternative embodiment, it is also necessary to note that for low pass filter and high pass filter, the coefficients of the filter can be determined according to the damping coefficient and the digital angular frequency of each filter.

[0140] Optionally, the transfer function of the low pass filter can refer to formula (13):

[0141] (13)

[0142] The design formula is as follows:

[0143]

[0144]

[0145]

[0146] The characteristics of the low pass filter include: suppressing high frequency signals and retaining frequency components lower than .

[0147] Optionally, the transfer function of the high pass filter can refer to formula (14):

[0148] (14)

[0149] The design formula is as follows:

[0150]

[0151]

[0152]

[0153] The characteristics of the high pass filter include: suppressing low frequency signals and retaining frequency components higher than .

[0154] The key parameters involved in the above are explained as follows:

[0155] Digital angular frequency , calculation formula: , function: map the analog frequency to the digital domain, ensure the frequency response within the Nyquist range (effective frequency range defined by the Nyquist sampling theorem).

[0156] Damping coefficient , calculation formula: , function: control the bandwidth and resonance characteristics of the filter, inversely proportional to the Q value.

[0157] Linear gain A, calculation formula: , used to convert decibel gain to linear scale (40 denominator corresponds to voltage amplitude).

[0158] From the above, in the process of selecting the filter, first, parameter input: specify . Then frequency conversion: calculate the digital angular frequency . Then coefficient calculation: according to the filter type selection formula, calculate the numerator and denominator polynomial coefficients. Finally, the normalization processing of the coefficients: all coefficients divided by , ensure .

[0159] From the above, for the parameter equalization filter, the present application can determine its coefficients according to the damping coefficient, digital angular frequency and target gain. The parameter equalization filter is used in ANC and audio processing to fine-tune the gain of the signal in a specific frequency range to compensate for the inherent frequency response of the system or noise sensitive points. Through the technology of the present application, the coefficients of the parameter equalization filter can be accurately set in the simulation test stage, realizing the accurate approximation of the target frequency response function, thereby improving the overall sound quality and noise reduction performance of the ANC system.

[0160] In addition, frequency selection filters such as low-pass, high-pass, band-pass filters are mainly used for frequency division of signals to ensure that the ANC system only processes noise signals in a specific frequency range. The present application can directly determine the coefficients of the frequency selection filter through the damping coefficient and the digital angular frequency, which simplifies the complexity of filter design and ensures the high precision of filter performance. The accurate design and implementation of the frequency selection filter is crucial for the ANC system to avoid processing noise in useless frequency bands and focus on the noise reduction effect of key frequency bands.

[0161] Therefore, by accurately calculating the digital angular frequency and the damping coefficient, the application can ensure that the filter is stable and accurately realizes the design intention in the digital domain, whether it is the fine gain adjustment of the parameter equalization filter or the signal segmentation function of the frequency selection filter, which can be effectively supported. This series of technical optimization not only improves the accuracy and reliability of the simulation test of the ANC system, but also greatly simplifies the filter design process, reduces the debugging and verification cost, and speeds up the process from design to productization of the ANC system.

[0162] In an optional embodiment, the overall signal transfer function of the multi-cascaded filter combination is determined according to the coefficients of each filter in the multi-cascaded filter combination, comprising: the simulation test system can determine the signal transfer function of each filter according to the coefficients of each filter, and then multiply the signal transfer functions of each filter to obtain the overall signal transfer function.

[0163] Optionally, the high-order transfer function of the IR filter can be realized by cascading a plurality of second-order sections (SOS). Each SOS corresponds to a biquad filter, and the transfer function thereof can refer to formula (15):

[0164] (15)

[0165] In formula (15), i represents the i-th filter, i is an integer greater than or equal to 1. The coefficient transfer function is usually expressed in the form of domain, in the domain is a tool variable that describes the relationship between input and output. represents how the i-th filter processes the input signal (described in the form of a function).

[0166] represents a delay of one sampling point, that is, the data of the previous time point.

[0167] Optionally, the overall signal transfer function of the multi-cascaded filter combination is the product of each SOS, which can refer to formula (16):

[0168] (16)

[0169] In formula (16), N is the number of filters included in the multi-cascaded filter combination.

[0170] It should be noted that in the application, the second-order section structure of the direct I type (Direct Form I) is as follows:

[0171] Difference equation: .

[0172] where the state variables include: input delay and output delay .

[0173] In an alternative embodiment, gain bias adjustment and phase compensation are performed on the overall signal transfer function, including: the simulation test system receives a gain bias value and a phase bias value input by a user through an interactive interface; the overall signal transfer function is adjusted in gain bias according to the gain bias value; the overall signal transfer function is compensated in phase according to the phase bias value.

[0174] Optionally, in actual audio system measurement, there may be an overall high or low offset in the frequency response, especially when multiple measurement devices or reference curves are used for comparison. To ensure consistency, gain bias adjustment is needed. For example, if the original gain response is (unit: dBv), the gain offset is a constant , then the adjusted gain response is: .

[0175] In addition, in the process of audio system measurement, the measured phase response usually has a jump phenomenon, especially at the frequency point across ±180°. At this time, the phase response will suddenly jump from +180° to -180° (or vice versa), causing the phase diagram to deviate from the target by 180° multiples, affecting subsequent processing. To solve this problem, phase compensation adjustment is needed.

[0176] Suppose the original phase response is (unit: degrees), and the phase compensation value is , then the compensated phase response is: .

[0177] According to another aspect of the present application, there is also provided a simulation test system based on a multi-cascaded filter, comprising: a data import module configured to import single or multiple sets of signal transfer function data and extract voltage gain values and phase angles of each frequency point from the signal transfer function data; a target response calculation module connected to the data import module and configured to receive and process the signal transfer function data and determine a target response function according to the voltage gain values and the phase angles, wherein the target response function is configured to eliminate inherent characteristic influence factors in the simulation system; a second-order filter module connected to the target response calculation module and configured to determine a multi-cascaded filter combination according to the target response function and determine an overall signal transfer function of the multi-cascaded filter combination according to coefficients of each filter in the multi-cascaded filter combination, wherein the multi-cascaded filter combination comprises at least one filter; and a data compensation module connected to the second-order filter module and configured to perform gain bias adjustment and phase compensation on the overall signal transfer function and perform simulation test on an input signal through the cascaded filter combination.

[0178] Optionally, Figure 2 is an optional architecture diagram of a simulation test system according to an embodiment of the present application, as shown in Figure 2 The data import module is configured to import single or multiple sets of signal transfer function data, for example, the module can support Excel file parsing, extract frequency, gain, and phase data, and automatically align the horizontal and vertical coordinates. Different data is distinguished by different colors (for example, the target curve is red and the single-stage response is blue). The module can also support double-axis display: for example, one graph is used to display the gain-frequency curve and the other graph is used to display the phase-frequency curve. The module can also support logarithmic frequency axis and custom scale (input range through text box).

[0179] Optionally, as shown in Figure 2 The simulation test system further comprises a data storage module configured to save filter parameters in a specific format, such as filter type, Q value, and enabled state. The simulation test system further comprises a second-order filter module (also referred to as a filter design module), a target response calculation module (including a frequency response calculation module and a cascaded response module), and a visualization module. The compensation result output by the cascaded response module can be displayed through the visualization module.

[0180] As can be seen from the above, by deeply analyzing the voltage gain values and phase angles of the frequency points in the signal transfer function data, the present application can accurately determine the target response function, which can effectively eliminate the inherent characteristic influence factors in the simulation system, ensuring that the simulation result is closer to the performance of the actual ANC system.

[0181] Secondly, based on the target response function, the application can adaptively and flexibly select and combine at least one filter, such as but not limited to a peak notch filter, a low shelf filter, a high shelf filter, a low pass filter and a high pass filter. The ability to dynamically adjust the filter combination enables the simulation test process to better meet the actual needs of the ANC system, so that the type, parameters and cascading manner of the filter can be freely set according to the specific noise reduction scene, greatly improving the pertinence and efficiency of the test.

[0182] In addition, the application calculates the coefficients of each filter in the multi-cascaded filter combination to determine the overall signal transfer function in real time. This means that each adjustment of the filter parameters can be immediately reflected in the final simulation results without the need to re-run the entire simulation process, saving a lot of debugging time and improving the test experience of engineers. In the final stage of the simulation test, the application provides gain bias adjustment and phase compensation functions to ensure that the overall signal transfer function and the target response function are maximally matched in amplitude and phase, thereby eliminating the accumulation of errors in the test and further improving the accuracy and reliability of the simulation results.

[0183] Through the above technical related steps, the application realizes adaptive and flexible adjustment of the combination of filters in the simulation test, effectively solving the problem of low test efficiency in the prior art. This method not only simplifies the debugging process of ANC system design, but also improves the consistency of simulation results and actual system response.

[0184] According to another aspect of the application, a computer readable storage medium is also provided, which stores a computer program, wherein the computer program, when executed, causes the device in which the computer readable storage medium is located to perform the simulation test method based on the multi-cascaded filter described above.

[0185] According to another aspect of the application, an electronic device is also provided, which includes one or more processors and a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the simulation test method based on the multi-cascaded filter described above.

[0186] The above-mentioned application embodiment serial numbers are only for description, not representing the pros and cons of the embodiments.

[0187] In the above-mentioned embodiments of the application, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0188] In several embodiments provided by the present application, it should be understood that the disclosed technology can be implemented in other manners. For example, the described unit embodiments can be divided into other ways, for example, the units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections can be implemented by using some interfaces, and the indirect couplings or communication connections can be implemented in electronic, mechanical, or other forms.

[0189] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, can be located in one place, or can be distributed on multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0190] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically, or two or more units can be integrated into one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0191] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the present application, essentially or the part that contributes to the prior art, or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various program codes that can be stored in the medium.

[0192] The above description is only the preferred embodiment of the present application, and it should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. A method for simulation test based on multi-cascaded filter, characterized in that, The simulation test method based on the multi-cascaded filter is applied to a simulation test system based on a multi-cascaded filter, and the simulation test method based on the multi-cascaded filter comprises: After importing single-group or multi-group signal transfer function data into the simulation test system, the simulation test system extracts voltage gain values and phase angles of each frequency point from the signal transfer function data; determining a target response function according to the voltage gain values and the phase angles, wherein the target response function is used to eliminate inherent characteristic influence factors in a simulation system; determining a multi-cascaded filter combination according to the target response function, wherein the multi-cascaded filter combination comprises at least one filter; determining an overall signal transfer function of the multi-cascaded filter combination according to coefficients of each filter in the multi-cascaded filter combination; After gain bias adjustment and phase compensation are performed on the overall signal transfer function, performing simulation test on an input signal through the cascaded filter combination.

2. The method of claim 1, wherein, determining a target response function according to the voltage gain values and the phase angles, comprising: converting the voltage gain values into linear domain voltage values and converting the phase angles into radian format; determining a frequency response function according to the linear domain voltage values and the phase angles in radian format; determining system characteristic reference path information, noise control path information and feedforward path information according to the frequency response function, respectively; determining the target response function according to the system characteristic reference path data, noise control path data and feedforward path data.

3. The method of claim 2, wherein, determining the target response function according to the system characteristic reference path data, noise control path data and feedforward path data, comprising: calculating a difference value between the noise control path data and the system characteristic reference path data to obtain a first function; calculating a difference value between the feedforward path data and the system characteristic reference path data to obtain a second function; calculating a difference value between the second function and the first function to obtain a third function; calculating a ratio value between the first function and the third function to obtain the target response function.

4. The method of claim 1, wherein, After determining the target response function according to the voltage gain values and the phase angles, the method further comprises: determining a first curve and a second curve according to the target response function, wherein the first curve is used to represent amplitude-frequency information in the target response function, and the second curve is used to represent phase-frequency information in the target response function, and the second curve is a curve after period jump elimination processing; rendering and displaying the first curve and the second curve.

5. The method of claim 1, wherein, determining the overall signal transfer function of the multi-cascaded filter combination according to the coefficients of each filter in the multi-cascaded filter combination, comprising: determining signal transfer functions of the filters according to the coefficients of the filters; performing product calculation on the signal transfer functions of the filters to obtain the overall signal transfer function.

6. The method of claim 1, wherein, Before determining the overall signal transfer function of the multi-cascaded filter combination according to the coefficients of each filter in the multi-cascaded filter combination, the method further comprises: determining a sampling frequency, a center frequency, a quality factor and a target gain of each filter in the multi-cascaded filter combination, wherein the sampling frequency is used to control a filter frequency response range, the center frequency is used to determine a key frequency point of the filter response, the quality factor is used to control a relationship between a filter bandwidth and the center frequency, and the target gain is used to adjust an amplitude enhancement or attenuation of a frequency band; determining coefficients of each filter according to the sampling frequency, the center frequency, the quality factor and the target gain of the filter.

7. The method of claim 6, wherein, determining coefficients of each filter according to the sampling frequency, the center frequency, the quality factor and the target gain of the filter, including: determining a digital angular frequency of each filter according to the sampling frequency and the center frequency of the filter, wherein the digital angular frequency is used to map an analog frequency to a digital domain; determining a damping coefficient of each filter according to the digital angular frequency and the quality factor of the filter, wherein the damping coefficient is used to control a bandwidth and a resonance characteristic of the filter; when any one filter in the multi-cascaded filter combination belongs to a parametric equalization filter, determining coefficients of the filter according to the damping coefficient, the digital angular frequency and the target gain of the filter; when any one filter in the multi-cascaded filter combination belongs to a frequency selective filter, determining coefficients of the filter according to the damping coefficient and the digital angular frequency of the filter.

8. The method of claim 1, wherein, adjusting a gain bias and compensating a phase of the overall signal transfer function, including: receiving a gain bias value and a phase bias value input by a user through an interactive interface; adjusting a gain bias of the overall signal transfer function according to the gain bias value; compensating a phase of the overall signal transfer function according to the phase bias value.

9. A simulation test system based on a multi-cascaded filter, characterized by, including: a data import module, configured to import single or multiple sets of signal transfer function data, and extract voltage gain values and phase angles of each frequency point from the signal transfer function data; a target response calculation module, connected to the data import module, configured to receive and process the signal transfer function data, and determine a target response function according to the voltage gain values and the phase angles, wherein the target response function is used to eliminate inherent characteristic influence factors in a simulation system; a second-order filter module, connected to the target response calculation module, configured to determine a multi-cascaded filter combination according to the target response function, and determine an overall signal transfer function of the multi-cascaded filter combination according to coefficients of each filter in the multi-cascaded filter combination, wherein the multi-cascaded filter combination includes at least one filter; a data compensation module, connected to the second-order filter module, configured to adjust a gain bias and compensate a phase of the overall signal transfer function, and perform simulation testing on an input signal through the cascaded filter combination.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, wherein when the computer program runs, the computer readable storage medium causes a device where the computer readable storage medium is located to perform the simulation testing method based on the multi-cascaded filter according to any one of claims 1 to 8.

Images