Simulation test method and system based on multi-cascade filter and electronic equipment

Abstract

The invention discloses a simulation test method and system based on a multi-cascade filter and electronic equipment, and relates to the technical field of communication. The method comprises the following steps: extracting a voltage gain value and a phase angle of each frequency point from signal transfer function data; a target response function is determined according to the voltage gain value and the phase angle, and the target response function is used for eliminating inherent characteristic influence factors in the simulation system; determining a multi-cascade filter combination according to the target response function; determining an overall signal transfer function of the multi-cascade filter combination according to the coefficient of each filter in the multi-cascade filter combination; after gain deviator adjustment and phase compensation are carried out on the overall transfer function, simulation testing is carried out on an input signal through a cascade filter combination. The technical problem that in the prior art, the signal simulation test efficiency is low due to the fact that the combination mode of filters cannot be adjusted adaptively and flexibly in the simulation process is solved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a simulation test method, system and electronic equipment based on a multi-cascade filter. Background Art

[0002] Simulation technology plays a crucial role in the design and optimization of active noise cancellation (ANC) systems. While existing ANC simulation tools and platforms, such as Python-based programming environments and specialized software tools, can assist engineers in verifying and debugging noise cancellation algorithms, these tools have significant technical limitations, particularly in adaptive filtering and flexible parameter adjustment.

[0003] For example, most existing tools only support preset filter types and fixed cascade methods, and cannot dynamically adjust filter combinations based on the specific needs of the ANC system. This means that when faced with complex and changing noise reduction scenarios, engineers often need to repeatedly experiment with multiple preset filter combinations to find the optimal solution, which greatly increases debugging time and complexity.

[0004] In summary, the inability of existing ANC simulation technology to provide flexible filter combinations significantly limits the efficiency and accuracy of signal simulation testing during the design and optimization of complex ANC systems. 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] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0006] The embodiments of the present invention provide a simulation test method, system and electronic device based on multi-cascade filters, so as to at least solve the technical problem in the prior art of low signal simulation test efficiency due to the inability to adaptively and flexibly adjust the combination of filters during the simulation process.

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

[0008] Optionally, determining a target response function based on the voltage gain value and the phase angle includes: converting the voltage gain value into a linear domain voltage value and converting the phase angle into a radian format; determining a frequency response function based on the linear domain voltage value and the phase angle in the radian format; determining system characteristic reference path information, noise control path information, and feedforward path information respectively based on the frequency response function; and determining the target response function based on the system characteristic reference path data, noise control path data, and feedforward path data.

[0009] Optionally, the target response function is determined based on the system characteristic baseline path data, the noise control path data and the feedforward path data, including: calculating the difference between the noise control path data and the system characteristic baseline path data to obtain a first function; calculating the difference between the feedforward path data and the system characteristic baseline path data to obtain a second function; calculating the difference between the second value and the first value to obtain a third function; and calculating the ratio of the first function to the third function to obtain the target response function.

[0010] Optionally, after determining the target response function based on the voltage gain value and the phase angle, a first curve and a second curve are determined based on the target response function, wherein the first curve is used to characterize the amplitude-frequency information in the target response function, the second curve is used to characterize 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.

[0011] Optionally, the overall signal transfer function of the multi-cascade filter combination is determined based on the coefficients of each filter in the multi-cascade filter combination, including: determining the signal transfer function of each filter based on 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 based on the coefficients of each filter in the multi-cascade filter combination, the sampling frequency, center frequency, quality factor and 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 coefficient of each filter is determined based on the sampling frequency, center frequency, quality factor and target gain of each filter.

[0013] Optionally, the coefficient of each filter is determined according to the sampling frequency, center frequency, quality factor and target gain of each filter, including: determining the digital angular frequency of the filter according to the sampling frequency and 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 the filter according to the digital angular frequency and quality factor of each 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-cascade filter combination is a parametric equalization filter, determining the coefficient of the filter according to the damping coefficient, digital angular frequency and target gain of the filter; when any one of the filters in the multi-cascade filter combination is a frequency selective filter, determining the coefficient of the filter according to the damping coefficient and digital angular frequency of the filter.

[0014] Optionally, performing gain offset adjustment and phase compensation on the overall transfer function includes: receiving a gain offset value and a phase offset value input by a user through an interactive interface; performing gain offset adjustment on the overall transfer function according to the gain offset value; and performing phase compensation on the overall transfer function according to the phase offset value.

[0015] According to another aspect of the present invention, a simulation test system based on a multi-cascade filter is also provided, including: a data import module, used to import a single group or multiple groups of signal transfer function data, and extract the voltage gain value and phase angle of each frequency point from the signal transfer function data; a target response calculation module, connected to the data import module, used to receive and process the signal transfer function data, and determine 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 influencing factors in the simulation system; a second-order filter module, connected to the target response calculation module, used to determine the multi-cascade filter combination according to the target response function, and determine the overall signal transfer function of the multi-cascade filter combination according to the coefficients of each filter in the multi-cascade filter combination, wherein the multi-cascade filter combination includes at least one filter; a data compensation module, connected to the second-order filter module, used to perform gain offset adjustment and phase compensation on the overall transfer function, and simulate and test the input signal through the cascade filter combination.

[0016] According to another aspect of the present invention, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program runs, the device where the computer-readable storage medium is located executes the above-mentioned simulation test method based on multi-cascade filters.

[0017] According to another aspect of the present invention, an electronic device is also provided, wherein the electronic device includes one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors execute the above-mentioned simulation test method based on multi-cascade filters.

[0018] The present invention provides a simulation test method based on a multi-cascade filter. The method comprises: first, extracting voltage gain values ​​and phase angles at various frequency points from signal transfer function data; then, determining a target response function based on the voltage gain values ​​and phase angles, wherein the target response function is used to eliminate inherent characteristic influencing factors in the simulation system; then, determining a multi-cascade filter combination based on the target response function, wherein the multi-cascade filter combination includes at least one filter; and determining the overall signal transfer function of the multi-cascade filter combination based on the coefficients of each filter in the multi-cascade filter combination. Finally, after performing gain offset adjustment and phase compensation on the overall transfer function, a simulation test is performed on the input signal using the cascade filter combination.

[0019] As can be seen from the above content, through in-depth analysis of the voltage gain value and phase angle at the mid-frequency point of the signal transfer function data, the present invention can accurately determine the target response function. This function can effectively eliminate the inherent characteristic influencing factors in the simulation system, ensuring that the simulation results are closer to the performance of the actual ANC system.

[0020] Secondly, based on the target response function, the present invention can adaptively and flexibly select and combine at least one filter, including but not limited to peak notch filters, low-shelf filters, high-shelf filters, low-pass filters, and high-pass filters. This ability to dynamically adjust filter combinations allows simulation testing to better align with the actual needs of the ANC system, allowing the filter type, parameters, and cascade method to be freely set according to specific noise reduction scenarios, greatly improving the targetedness and efficiency of testing.

[0021] In addition, the present invention 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 every adjustment to the filter parameters can be immediately reflected in the final simulation results, without the need to rerun the entire simulation process, saving a lot of debugging time and improving the engineer's testing experience. In the final stage of the simulation test, the present invention provides gain offset adjustment and phase compensation functions to ensure that the overall transfer function and the target response function are matched to the greatest extent in amplitude and phase, thereby eliminating error accumulation in the test and further improving the accuracy and reliability of the simulation results.

[0022] Through the above-mentioned technical steps, the present invention achieves adaptive and flexible adjustment of filter combinations during simulation testing, effectively solving the problem of low testing efficiency in existing technologies. This method not only simplifies the debugging process of ANC system design, but also improves the consistency between simulation results and actual system response. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

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

[0025] Figure 2 4 is an architectural diagram of an optional simulation test system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] It should also be noted that the information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) collected by the present invention are information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data comply with the relevant laws, regulations and standards of the relevant regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse. For example, an interface is set up between this system and relevant users or institutions. Before obtaining relevant information, it is necessary to send an acquisition request to the aforementioned user or institution through the interface, and obtain relevant information after receiving the consent information fed back by the aforementioned user or institution.

[0029] According to an embodiment of the present invention, an embodiment of a simulation test method based on a multi-cascade filter is provided. It should be noted that the steps shown in the flowchart of the accompanying 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 can be executed in an order different from that shown here.

[0030] In an optional embodiment, a simulation test system based on a multi-cascade filter (hereinafter referred to as the simulation test system) can be used as the execution subject of the simulation test method based on a multi-cascade filter according to an embodiment of the present invention, wherein the simulation test system can be a software system or an embedded system that combines software and hardware. In addition, it should be noted that in addition to using the simulation test system as the execution subject of the method according to an embodiment of the present invention, other forms of subjects can also be used to execute the method steps of the embodiment of the present invention, such as devices, equipment, etc. Those skilled in the art should know that the embodiment of the present invention does not specifically limit the specific type of the method execution subject.

[0031] For the convenience of explanation, the following description of the method steps is based on a simulation test system as the execution subject.

[0032] Figure 1 FIG. 1 is a flow chart of an optional simulation test method based on a multi-cascade filter according to an embodiment of the present invention, Figure 1 As shown, the method includes the following steps:

[0033] Step S101 : extracting the voltage gain value and phase angle at 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 to import the target curve file, the simulation test system can automatically identify the names of each file in the target curve file and determine a single group or multiple groups 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 H char (f);

[0037] Noise control path H PNC (f);

[0038] Feedforward path H FF (f).

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

[0040] Step S102 : determining a 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 influencing factors in the simulation system.

[0041] Optionally, the target response function represents the desired frequency response characteristics of the ANC system, including the gain and phase variations of the signal at different frequencies. The target response function construction process in this invention aims to eliminate inherent characteristic influencing factors introduced by hardware characteristics, measurement errors, or algorithmic biases in the simulation system, ensuring that the final simulation results more realistically 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] Alternatively, in the context of ANC (active noise cancellation) system simulation and design, the target response function (TRF) serves as a blueprint that bridges ideal performance with actual implementation. Based on an in-depth analysis of the target ANC performance, the TRF converts voltage gain values ​​and phase angles into a complex representation of the frequency response, thereby defining the desired behavior of the ANC system in the frequency domain. Once the TRF is determined, the next key step is to determine a multi-cascade filter combination to achieve this TRF as accurately as possible in the digital domain. This process involves filter selection, parameter setting, and optimization of the cascade method. The goal is to simulate and approximate the TRF through a series of filter combinations to obtain the desired 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] Among them, 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 of the target response function, select the appropriate filter from a variety of filter types, such as notch filters, low-shelf filters, high-shelf filters, low-pass filters, and high-pass filters. Each filter provides different gain and phase responses within a specific frequency range. Therefore, selecting the filter type that meets the requirements of the target function is essential for achieving an accurate response.

[0047] Filter parameter setting: For each filter, you need to set parameters such as center frequency, gain, and quality factor (Q value) to ensure that the filter can process the signal according to the requirements of the target response function. These parameters must be selected carefully and accurately because they directly affect the filter's frequency response shape and performance.

[0048] Filter Cascade Combinations: Complex frequency responses in ANC systems often cannot be achieved with a single filter, so multiple filters are cascaded to form a filter combination. By using appropriate cascading methods, the characteristics of different filters can be combined to achieve a wider and more complex target frequency response. When cascading filters, a key consideration is ensuring that the overall frequency response closely matches the target response function while maintaining system stability and computational efficiency.

[0049] Construction of the overall transfer function: The transfer function of a cascaded filter is obtained by multiplying the transfer functions of the individual filters. This means that the output of each filter serves as the input to the next, forming a complex signal processing chain. By cascading filters in the SOS (Second-Order Section) format, an overall 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 by flexibly selecting and configuring filter combinations according to the requirements of the target response function, it is possible to customize the filter parameters and cascade methods for specific ANC scenarios and requirements, thereby improving the flexibility and adaptability of the simulation test process.

[0051] Secondly, the combination of multiple cascaded filters can approximate the complex target frequency response shape. By fine-tuning the filter parameters and cascade strategy, it can achieve refined control of the ANC system performance and improve the accuracy and reliability of the simulation test.

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

[0053] In summary, the multi-cascade filter combination design proposed in this invention is a key step in achieving the target response function of the ANC system. It not only provides precise frequency response control but also brings greater adaptability and optimization potential to ANC system design. This approach allows for more efficient design and testing of ANC system performance, accelerating the product development process and improving the noise reduction effect and user experience of the final product.

[0054] Step S105 : After performing gain offset adjustment and phase compensation on the overall transfer function, a simulation test is performed on the input signal through the cascade filter combination.

[0055] Optionally, gain offset adjustment fine-tunes the amplitude response of the overall transfer function to eliminate or compensate for gain shifts across the entire spectrum or in specific frequency bands. Such shifts can be caused by inaccuracies in the signal source or measurement equipment, or system losses not fully accounted for during filter design. Gain offset adjustment ensures that the gain response of the simulation results aligns with the target response function, thus avoiding potential volume imbalances or over- or under-noise reduction in real-world applications.

[0056] Optionally, phase compensation corrects for phase differences in the transfer function relative to the target response function. In ANC systems, precise phase control is crucial for noise cancellation. Any phase deviation will affect the effectiveness of the system's noise reduction, especially when the signal phase crosses the ±180-degree boundary. Implementing phase compensation eliminates or minimizes phase jumps caused by factors such as signal path delays and filter design errors, ensuring that the ANC system achieves optimal noise cancellation across the entire frequency band.

[0057] It's important to note that adjusting the overall transfer function is an integrated application of the aforementioned gain offset adjustment and phase compensation. By making the necessary amplitude and phase modifications at the transfer function's output, the system can better adapt to the target response function and provide a more precise ANC effect.

[0058] After adjusting the overall transfer function, the next step is to simulate the input signal using a cascaded filter combination. In this stage, the simulation system passes the input signal through the designed filter cascade and processes it according to the adjusted overall transfer function, simulating the ANC system's operating state. By comparing the signals before and after processing (the original noise signal and the noise-reduced signal), the noise reduction effect of the ANC system can be visually compared, its performance in various noise environments can be evaluated, and necessary parameter adjustments and optimizations can be made until the design goals are achieved.

[0059] In an optional embodiment, determining a target response function based on a voltage gain value and a phase angle includes: a simulation test system first converting the voltage gain value into a linear domain voltage value and converting the phase angle into radians. The simulation test system then determines a frequency response function based on the linear domain voltage value and the radian phase angle; and determines system characteristic reference path information, noise control path information, and feedforward path information based on the frequency response function. Finally, the simulation test system determines the target response function based on the system characteristic reference path data, noise control path data, and feedforward path data.

[0060] Optionally, in order to determine the target response function, the simulation test system first performs voltage gain normalization processing, and the voltage gain value G in the logarithmic domain is normalized. dBV Converted to linear voltage value V liner , the conversion formula can refer to formula (1):

[0061]

[0062] The simulation test system also calculates the phase angle φ deg Convert to radians φ rad , the conversion formula refers to formula (2):

[0063]

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

[0065]

[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 may extract at least the following three pieces of signal path information from the signal transfer function data:

[0068] System characteristic reference path H char (f);

[0069] Noise control path H PNC (f);

[0070] Feedforward path H FF (f).

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

[0072] It should be noted that the voltage gain value is converted from the logarithmic domain (such as dB units) to the linear domain, and the phase angle is converted from the degree system to the radian system. This conversion ensures the accuracy of subsequent mathematical operations and avoids simulation distortion caused by unit mismatch or scale conversion errors, thereby achieving more accurate frequency response modeling. By extracting and determining the data information of the system characteristic reference path, noise control path and feedforward path respectively, the present invention can carefully analyze the performance characteristics of each signal processing link in the ANC system. This integrated analysis of multi-path information provides the ANC system with a comprehensive perspective on the signal flow and processing characteristics within the system, which helps to fine-tune each link to ensure the optimization of overall performance.

[0073] Furthermore, based on the previous analysis of the frequency response function and refinement of multipath data, the present invention constructs a highly accurate target response function. This function not only takes into account the ANC system's noise suppression requirements, but also fully considers the system's inherent characteristics and the interactions between various paths, providing a clear and quantifiable performance target for ANC system simulation testing. By continuously comparing and debugging with this target response function, it is possible to ensure that the ANC system accurately achieves the intended noise reduction effect in actual deployment.

[0074] In an optional embodiment, the target response function is determined based on the system characteristic reference path data, the noise control path data and the feedforward path data, 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 value and the first value to obtain a third function; calculate the ratio of the first function to the third function to obtain the target response function.

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

[0076] ΔH PNC (f) = H PNC (f)-H char (f) (4)

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

[0078] ΔH FF (f) = H FF (f)-H char (f) (5)

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

[0080]

[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 information about the system's response when processing noise signals. Calculating the difference between the two path data essentially extracts the effective control response portion of the noise control response resulting from the intervention of the ANC algorithm. This difference, or the first function, can determine the ANC system's noise suppression effectiveness without being affected by the system hardware characteristics.

[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 the signal processing path used in the ANC system to predict noise signals and compensate for them in advance. Unlike the first function, the second function focuses on the net effect of the feedforward path signal processing. This effect also needs to be separated from the influence of the system characteristic reference path to evaluate the pure effect of the feedforward control.

[0083] The third function is calculated by comparing the difference between the second and first functions. This step aims to further refine the differences between the noise control and feedforward paths in the ANC system, focusing specifically on the relative differences in the processing effects of the noise control path and the feedforward path. This difference analysis is crucial for understanding the overall performance of the ANC system because it reveals the synergy or potential conflict between the system's noise suppression and feedforward compensation signal processing.

[0084] Finally, by calculating the ratio of the first and third functions, the target response function (TRF) can be determined. This TRF comprehensively considers the effectiveness of noise suppression and signal compensation in the ANC system, reflecting the system's ideal frequency response characteristics when processing both noise and signals. This function not only defines the gain and phase response targets for 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 based on the voltage gain value and the phase angle, the simulation test system can determine a first curve and a second curve based on the target response function, wherein the first curve is used to characterize the amplitude-frequency information in the target response function, and the second curve is used to characterize 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, when determining the target response function H target (f) Afterwards, the simulation test bear can decompose the target response function into an amplitude-frequency characteristic function (corresponding to the function expressed by the first curve above) and a phase-frequency characteristic function (corresponding to the function expressed by the second curve above).

[0087] Alternatively, the amplitude-frequency characteristic function can be expressed by formula (7):

[0088] G target (f) = 20log 10 |H target (f)| (7)

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

[0090]

[0091] Among them, unwrap is a wrapping function used in the phase unwrapping algorithm to eliminate cycle jumps.

[0092] In an optional embodiment, before determining the overall signal transfer function of the multi-cascade filter combination based on the coefficients of each filter in the multi-cascade filter combination, the simulation test system can determine the sampling frequency, center frequency, quality factor, and target gain of each filter in the multi-cascade filter combination, 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 filter bandwidth and the center frequency, 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 based on the sampling frequency, center frequency, quality factor, and target gain of each filter.

[0093] Alternatively, the sampling frequency can be expressed as f s Indicates that the unit is Hz, where the sampling frequency f s Used to define the discrete time base of the digital system. The sampling frequency can determine the frequency response range of the filter (0 to f s / 2).

[0094] Alternatively, the center frequency is also called the cutoff frequency and can be represented by the symbol f c The unit is Hz, where the center frequency can be used to determine the key frequency points of the filter response (such as peak frequency, cutoff frequency).

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

[0096] Optionally, the filter gain G (in decibel form) can be converted to the target gain A (in linear form) using the formula (9):

[0097]

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

[0099] In an optional embodiment, the coefficients of each filter are determined based on the sampling frequency, center frequency, quality factor, and target gain of each filter, including: the simulation test system can determine the digital angular frequency of each filter based on the sampling frequency and 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 based on the digital angular frequency and 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-cascade filter combination is a parametric equalization filter, the simulation test system can determine the coefficients of the filter based on the damping coefficient, digital angular frequency, and target gain of the filter; when any one of the filters in the multi-cascade filter combination is a frequency selective filter, the simulation test system can determine the coefficients of the filter based on the damping coefficient and digital angular frequency of the filter.

[0100] Optionally, the present invention may provide at least five filters for combining to obtain a multi-cascade filter combination, including:

[0101] Peak notch filter;

[0102] low-shelf filter;

[0103] High-shelf filter;

[0104] Low-pass filter;

[0105] High-pass filter.

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

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

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

[0109] Here are some examples:

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

[0111]

[0112] The design formula is as follows:

[0113]

[0114] b0=1+αA, b1=-2cosω0, b2=1-αA

[0115] a1=-2cosω0,

[0116] Among them, A>1: peak enhancement; A<1: notch attenuation.

[0117] For the low-shelf filter, its transfer function refers to formula (11):

[0118]

[0119] The design formula is as follows:

[0120]

[0121] b1=2A[(A-1)-(A+1)cosω0+

[0122]

[0123] a1=-2[(A-1)+(A+1)cosω0+

[0124]

[0125] Among them, the characteristics of the low-shelf filter include: low-frequency gain adjustment, which is used to enhance or attenuate the frequency below f c Alternatively, the transfer function of the high-shelf filter can refer to formula (12):

[0126]

[0127] The design formula is as follows:

[0128]

[0129] b1=-2A[(A-1)+(A+1)cosω0+

[0130]

[0131] a1=2[(A-1)-(A+1)cosω0+

[0132]

[0133] Among them, the characteristics of the high-shelf filter include: high-frequency gain adjustment, used to enhance or attenuate higher than f c signal.

[0134] In an optional embodiment, it should also be noted that, for the low-pass filter and the high-pass filter, the coefficients of the filter can be determined according to the damping coefficient and digital angular frequency of each filter.

[0135] Alternatively, the transfer function of the low-pass filter can refer to formula (13):

[0136]

[0137] The design formula is as follows:

[0138]

[0139] b1=1-cosω0,b2=b0

[0140] a0=1+α, a1=-2cosω0, a2=1-α

[0141] Among them, the characteristics of the low-pass filter include: suppressing high-frequency signals and retaining signals below f c frequency components.

[0142] Alternatively, the transfer function of the high-pass filter can refer to formula (14):

[0143]

[0144] The design formula is as follows:

[0145]

[0146] b1=-(1+cosω0),b2=b0

[0147] a0=1+α, a1=-2cosω0, a2=1-α

[0148] Among them, the characteristics of the high-pass filter include: suppressing low-frequency signals and retaining signals above f c frequency components.

[0149] The key parameters mentioned above are described as follows:

[0150] Digital angular frequency ω0, calculation formula: ω0=2πf c / f s , function: Map the analog frequency to the digital domain to ensure that the frequency response is within the Nyquist range (the effective frequency range defined by the Nyquist sampling theorem).

[0151] Damping coefficient α, calculation formula: α = sinω0 / (2Q), function: controls the bandwidth and resonance characteristics of the filter, and is inversely proportional to the Q value.

[0152] Linear gain A, calculation formula: Used to convert decibel gain to a linear scale (40 denominator corresponds to voltage amplitude).

[0153] From the above content, we can know that in the process of selecting the filter, the parameters are first input: specify f s 、f c , Q, and G. Frequency conversion is then performed: the digital angular frequency ω0 is calculated. Coefficient calculation follows: the numerator (b0, b1, b2) and denominator (a0, a1, a2) polynomial coefficients are calculated according to the filter type selection formula. Finally, the coefficients are normalized: all coefficients are divided by a0 to ensure a0 = 1.

[0154] As can be seen from the above, the present invention can determine the coefficients of parametric equalization filters based on the damping coefficient, digital angular frequency, and target gain. Parametric equalization filters are used in ANC and audio processing to fine-tune the gain of the signal within a specific frequency range to compensate for the system's inherent uneven frequency response or noise-sensitive points. Through the technology of the present invention, the coefficients of the parametric equalization filter can be accurately set during the simulation test phase, achieving a precise approximation of the target frequency response function, thereby improving the overall sound quality and noise reduction performance of the ANC system.

[0155] In addition, frequency-selective filters, such as low-pass, high-pass, and band-pass filters, are primarily used for signal frequency segmentation, ensuring that the ANC system processes only noise signals within a specific frequency range. The present invention directly determines the coefficients of the frequency-selective filter using the damping coefficient and digital angular frequency. This process simplifies the complexity of filter design while ensuring high-precision filter performance. Accurate design and implementation of frequency-selective filters are crucial for ANC systems to avoid processing noise in unused frequency bands and focus on noise reduction in critical frequency bands.

[0156] This demonstrates that by precisely calculating the digital angular frequency and damping coefficient, the present invention ensures that the filter achieves its design intent stably and accurately within the digital domain. This effectively supports both the fine gain adjustment of parametric equalization filters and the signal segmentation function of frequency-selective filters. This series of technical optimizations not only improves the accuracy and reliability of ANC system simulation testing but also greatly simplifies the filter design process, reduces debugging and verification costs, and accelerates the transition from ANC system design to commercialization.

[0157] In an optional embodiment, the overall signal transfer function of the multi-cascade filter combination is determined based on the coefficients of each filter in the multi-cascade filter combination, including: the simulation test system can determine the signal transfer function of each filter based on the coefficients of each filter, and then perform product calculation on the signal transfer functions of each filter to obtain the overall signal transfer function.

[0158] Alternatively, the high-order transfer function of the IR filter can be realized by decomposing it into a cascade of multiple second-order sections (SOS). Each SOS corresponds to a biquad filter, and its transfer function can be referred to formula (15):

[0159]

[0160] Wherein, in formula (15), i represents the i-th filter, and i is an integer greater than or equal to 1. The coefficient transfer function is usually expressed in the form of z domain, In the domain It is used to describe the relationship between input and output and can be understood as an instrumental variable. Indicates how the i-th filter processes the input signal (described by functional form).

[0161] Represents a delay of one collection point, that is, the data at the previous time point.

[0162] Optionally, the overall signal transfer function of the multi-cascade filter combination is the product of each SOS, which can be referred to formula (16):

[0163]

[0164] Wherein, in formula (16), N is the number of filters included in the multi-cascade filter combination.

[0165] It should be noted that, in the present invention, the second-order link structure of Direct Form I is as follows:

[0166] Difference equation: y[n]=b0x[n]+b1x[n-1]+b2x[n-2]-a1y[n-1]-a2y[n-2].

[0167] The state variables include: input delay (x[n-1], x[n-2]) and output delay (y[n-1], y[n-2]).

[0168] In an optional embodiment, gain offset adjustment and phase compensation are performed on the overall transfer function, including: the simulation test system receives the gain offset value and phase offset value input by the user through the interactive interface; gain offset adjustment is performed on the overall transfer function according to the gain offset value; and phase compensation is performed on the overall transfer function according to the phase offset value.

[0169] Optionally, in actual audio system measurements, the frequency response may have an overall high or low offset, especially when using multiple measurement devices or reference curves for comparison. To ensure consistency, a gain offset adjustment is required. For example, if the original gain response is G(f) (unit: dBv) and the gain offset is a constant ΔG, the adjusted gain response is: G corrected (f) = G(f) - ΔG.

[0170] Furthermore, when measuring audio systems, the measured phase response often exhibits jumps, particularly at frequencies that span ±180°. In these cases, the phase response can abruptly jump from +180° to -180° (or vice versa), causing the phase graph to deviate from the target by multiples of 180°, impacting subsequent processing. To address this issue, phase compensation adjustment is required.

[0171] Assuming the original phase response is φ(f) (unit: degrees) and the phase compensation value is Δφ, the compensated phase response is: corrected (f) = φ(f) - Δφ*180.

[0172] According to another aspect of the present invention, a simulation test system based on a multi-cascade filter is also provided, including: a data import module, used to import a single group or multiple groups of signal transfer function data, and extract the voltage gain value and phase angle of each frequency point from the signal transfer function data; a target response calculation module, connected to the data import module, used to receive and process the signal transfer function data, and determine 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 influencing factors in the simulation system; a second-order filter module, connected to the target response calculation module, used to determine the multi-cascade filter combination according to the target response function, and determine the overall signal transfer function of the multi-cascade filter combination according to the coefficients of each filter in the multi-cascade filter combination, wherein the multi-cascade filter combination includes at least one filter; a data compensation module, connected to the second-order filter module, used to perform gain offset adjustment and phase compensation on the overall transfer function, and simulate and test the input signal through the cascade filter combination.

[0173] Optionally, Figure 2 is an architecture diagram of an optional simulation test system according to an embodiment of the present invention, such as Figure 2As shown, the data import module is used to import single or multiple sets of signal transfer function data. For example, the module can support the parsing of Excel files, extract frequency, gain, and phase data, and automatically align horizontal and vertical coordinates. Different data are distinguished by different colors (such as the target curve is red and the single-stage response is blue). It can also support dual-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 also supports logarithmic frequency axes and custom scales (by entering the range in the text box).

[0174] Alternatively, as Figure 2 As shown, the simulation test system also includes a data storage module for storing filter parameters such as filter type, Q value, and enabled state in a specific format. The simulation test system also includes a second-order filter module (also known as a filter design module), a target response calculation module (including a frequency response calculation module and a cascade response module), and a visualization module. The compensation results output by the cascade response module can be displayed using the visualization module.

[0175] As can be seen from the above content, through in-depth analysis of the voltage gain value and phase angle at the mid-frequency point of the signal transfer function data, the present invention can accurately determine the target response function. This function can effectively eliminate the inherent characteristic influencing factors in the simulation system, ensuring that the simulation results are closer to the performance of the actual ANC system.

[0176] Secondly, based on the target response function, the present invention can adaptively and flexibly select and combine at least one filter, including but not limited to peak notch filters, low-shelf filters, high-shelf filters, low-pass filters, and high-pass filters. This ability to dynamically adjust filter combinations allows simulation testing to better align with the actual needs of the ANC system, allowing the filter type, parameters, and cascade method to be freely set according to specific noise reduction scenarios, greatly improving the targetedness and efficiency of testing.

[0177] In addition, the present invention 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 every adjustment to the filter parameters can be immediately reflected in the final simulation results, without the need to rerun the entire simulation process, saving a lot of debugging time and improving the engineer's testing experience. In the final stage of the simulation test, the present invention provides gain offset adjustment and phase compensation functions to ensure that the overall transfer function and the target response function are matched to the greatest extent in amplitude and phase, thereby eliminating error accumulation in the test and further improving the accuracy and reliability of the simulation results.

[0178] Through the above-mentioned technical steps, the present invention achieves adaptive and flexible adjustment of filter combinations during simulation testing, effectively solving the problem of low testing efficiency in existing technologies. This method not only simplifies the debugging process of ANC system design, but also improves the consistency between simulation results and actual system response.

[0179] According to another aspect of the present invention, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program is executed, the device where the computer-readable storage medium is located executes the above-mentioned simulation test method based on multi-cascade filters.

[0180] According to another aspect of the present invention, an electronic device is also provided, wherein the electronic device includes one or more processors and a memory, and the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the above-mentioned simulation test method based on multi-cascade filters.

[0181] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0182] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0183] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are merely illustrative. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, and can be electrical or other forms.

[0184] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0185] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0186] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution 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 enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0187] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A simulation test method based on multi-cascade filters, characterized in that: include: Extract the voltage gain value and phase angle at each frequency point from the signal transfer function data; Determining a target response function according to the voltage gain value and the phase angle, wherein the target response function is used to eliminate inherent characteristic influencing factors in the simulation system; Determining a multi-cascade filter combination according to the target response function, wherein the multi-cascade filter combination includes at least one filter; determining an overall signal transfer function of the multi-cascade filter combination based on coefficients of each filter in the multi-cascade filter combination; After performing gain offset adjustment and phase compensation on the overall transfer function, a simulation test is performed on the input signal through the cascade filter combination.

2. The method according to claim 1, characterized in that Determining a target response function according to the voltage gain value and the phase angle includes: Converting the voltage gain value into a linear domain voltage value and converting the phase angle into a radian format; determining a frequency response function based on the linear domain voltage value and the phase angle in the radian format; determining system characteristic reference path information, noise control path information, and feedforward path information respectively according to the frequency response function; The target response function is determined according to the system characteristic reference path data, the noise control path data, and the feedforward path data.

3. The method according to claim 2, characterized in that Determining the target response function according to the system characteristic reference path data, the noise control path data, and the feedforward path data includes: 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 the difference between the second value and the first value to obtain a third function; The ratio of the first function to the third function is calculated to obtain the target response function.

4. The method according to claim 1, wherein After determining a target response function according to the voltage gain value and the phase angle, the method further includes: Determining 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, the second curve is used to represent the phase-frequency information in the target response function, and the second curve is a curve after period jump elimination processing; The first curve and the second curve are rendered and displayed.

5. The method according to claim 1, wherein Determining an overall signal transfer function of the multi-cascade filter combination based on coefficients of each filter in the multi-cascade filter combination comprises: determining a signal transfer function of each filter according to the coefficients of each filter; The signal transfer functions of the individual filters are multiplied to obtain the overall signal transfer function.

6. The method according to claim 1, characterized in that Before determining the overall signal transfer function of the multi-cascade filter combination based on the coefficients of each filter in the multi-cascade filter combination, the method further includes: Determining a sampling frequency, a center frequency, a quality factor, and a target gain for each filter in the multi-cascade filter combination, 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 filter bandwidth and the center frequency, 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.

7. The method according to claim 6, characterized in that Determining the coefficients of each filter according to the sampling frequency, center frequency, quality factor, and target gain of each filter includes: 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 the analog frequency to the digital domain; Determining a damping coefficient of each filter according to the digital angular frequency and quality factor of the 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 is a parametric equalization filter, determining a coefficient of the filter according to a damping coefficient, a digital angular frequency, and a target gain of the filter; When any one filter in the multi-cascade filter combination is a frequency selective filter, the coefficient of the filter is determined according to the damping coefficient and the digital angular frequency of the filter.

8. The method according to claim 1, characterized in that Performing gain offset adjustment and phase compensation on the overall transfer function, including: receiving a gain offset value and a phase offset value input by a user through an interactive interface; performing a gain offset adjustment on the overall transfer function according to the gain offset value; Phase compensation is performed on the overall transfer function according to the phase offset value.

9. A simulation test system based on multi-cascade filters, characterized in that: include: A data import module is used to import a single set or multiple sets of signal transfer function data, and extract the voltage gain value and phase angle 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 value and the phase angle, wherein the target response function is used to eliminate inherent characteristic influencing factors in the simulation system; a second-order filter module, connected to the target response calculation module, configured to determine a multi-cascade filter combination according to the target response function, and determine an overall signal transfer function of the multi-cascade filter combination according to coefficients of each filter in the multi-cascade filter combination, wherein the multi-cascade filter combination includes at least one filter; A data compensation module is connected to the second-order filter module and is used to perform gain offset adjustment and phase compensation on the overall transfer function, and to perform simulation testing on the input signal through the cascade 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 is executed, the device where the computer-readable storage medium is located executes the simulation test method based on the multi-cascade filter according to any one of claims 1 to 8.

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