Partitioned reference distributed anti-interference projection capacitive touch method and system

Abstract

The application discloses a partition reference distributed anti-interference projection capacitance touch method and system, and relates to the technical field of data processing. In the method, a static capacitance reference value and a background noise sample sequence are acquired, and the reference value is divided into an edge region, a center region and a transition region. Noise frequency domain features are extracted to construct a filter for filtering the reference values of the regions, and pre-compensation enhancement is performed when the edge noise exceeds a standard. A distributed reference capacitance matrix is constructed based on the processed reference values. Dynamic capacitance induction values are acquired, and signal matching deviation values and response difference ratio values of the regions are calculated in combination with the reference matrix. The response difference ratio values and the matching deviation values are used to identify interference types and interference regions, respectively. Deviation correction coefficients are calculated according to the interference types and the regions to compensate the dynamic capacitance induction values, and the coefficients are locked as touch consistency configuration parameters when compensation reaches a preset global balanced state. The technical scheme provided by the application can improve the touch recognition accuracy of different regions.

Description

Technical Field

[0001] This invention belongs to the field of data processing technology, specifically a partitioned reference distributed anti-interference projected capacitive touch method and system. Background Technology

[0002] With the deepening development of intelligent manufacturing and industrial automation, touch-based human-machine interaction technology has been widely applied in industrial control software, intelligent terminal equipment, and automotive display systems. As a key component for realizing human-machine information interaction, the performance of projected capacitive touchscreens directly affects the operational accuracy and user experience of the entire control system. Among these, the consistency of touch response and anti-interference capability are core indicators characterizing the reliability of touch systems, and their quality has a decisive impact on the overall system performance.

[0003] Currently, touch recognition in projected capacitive touch systems primarily relies on acquiring a capacitance reference value in the non-touch state, measuring the capacitance sensing value in real time when a touch occurs, and comparing the difference between the two with a preset globally unified judgment threshold. This method identifies touch events by setting a unified touch judgment standard, is relatively simple to operate, and has been widely used in consumer electronics and industrial control fields.

[0004] However, as the demand for touch technology in complex industrial environments and high-reliability scenarios continues to increase, the limitations of existing methods are becoming increasingly apparent. In practical applications, due to the lack of an effective adjustment mechanism for spatial response differences in the touch area, coupled with the continuous influence of external electromagnetic interference, environmental noise, and other factors, the capacitive response characteristics of different locations within the touch area often exhibit significant differences. This response difference makes it difficult to accurately reflect the actual touch state of each area using a globally unified benchmark and threshold, reducing the accuracy of touch recognition and failing to meet the precise operational requirements of industrial control scenarios. Summary of the Invention

[0005] To address the above problems, this invention provides a partitioned reference distributed anti-interference projected capacitive touch method and system, which solves the problem of insufficient touch recognition accuracy caused by the lack of an effective adjustment mechanism for spatial response differences in touch areas in existing touch technologies. This method can improve the touch recognition accuracy in different areas and meet the precise operation requirements of industrial control application scenarios.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: Obtain the static capacitance reference value and background noise sample sequence of the touch area under static reference state, and divide the static capacitance reference value into reference values ​​corresponding to multiple regions according to the touch position. The regions include edge regions, center regions and transition regions. The frequency domain features of the background noise sample sequence are extracted to construct a target frequency band filter. The filter is used to filter the reference values ​​of each region. When the noise in the edge region exceeds the standard, the reference values ​​of the filtered edge region are pre-compensated and enhanced. Based on the reference values ​​of each region after filtering and enhancement, capacitance distribution characteristic parameters are calculated, and a distributed reference capacitance matrix that transitions continuously from the edge region to the center region is constructed according to the capacitance distribution characteristic parameters. The dynamic capacitive sensing value of the touch area under dynamic sensing state is obtained, and the signal matching deviation value and response difference ratio of each area are calculated by combining the distributed reference capacitance matrix with the dynamic capacitive sensing value. Based on the response difference ratio, the type of interference is identified, and based on the signal matching deviation value, the interference region is identified. The deviation correction coefficients for each region are calculated based on the interference type and the interference region. The dynamic capacitive sensing value is compensated using the deviation correction coefficients. When the compensated touch area reaches a preset global equilibrium state, the deviation correction coefficients are locked as touch consistency configuration parameters.

[0007] By employing the above technical solution, the touch area is divided into edge, center, and transition regions according to spatial location characteristics, and the static capacitance reference value of each region under static reference conditions is obtained. Based on this, a target frequency band filter is constructed by extracting the frequency domain features of the background noise sample sequence, which can specifically filter out frequency domain interference components in the reference values ​​of each region. Furthermore, based on the filtered and enhanced reference values ​​of each region, capacitance distribution characteristic parameters are calculated, and a distributed reference capacitance matrix that continuously transitions from the edge to the center region is constructed. This distributed reference mechanism fully considers the differences in capacitance response characteristics at different locations within the touch area, overcoming the limitation of traditional globally unified references that cannot accurately reflect the actual touch state of each region. When a touch occurs, by combining the distributed reference capacitance matrix with dynamic capacitance sensing values ​​to calculate the signal matching deviation and response difference ratio of each region, the degree of response deviation in each region can be accurately quantified, and the type and region of interference can be identified, achieving precise localization of interference factors. Based on this, a deviation correction coefficient is calculated for each region according to the identified interference type and interference area. This coefficient is then used to specifically compensate for the dynamic capacitive sensing value. When the compensated touch area reaches a preset global equilibrium state, the deviation correction coefficient is locked as a touch consistency configuration parameter, thus establishing a complete zoned adaptive adjustment mechanism. This mechanism eliminates the impact of spatial response differences in touch areas on recognition accuracy by implementing differentiated benchmark adjustments and deviation compensation for different regions, improving the consistency and anti-interference capability of touch response, and enabling the touch system to meet the precise operation requirements of industrial control applications.

[0008] Optionally, in a static reference state without touch input, the initial capacitance value of each touch node within the touch area is obtained as a static capacitance reference value; in the static reference state, a sequence containing capacitance value fluctuation data is continuously collected as the background noise sample sequence; the shortest distance from each touch node to the boundary of the touch area and the distance to the geometric center are calculated; based on the shortest distance and the distance to the geometric center, a distance boundary threshold is determined according to a preset ratio, and the static capacitance reference value is divided into a reference value for the edge region, a reference value for the center region, and a reference value for the transition region according to the distance boundary threshold.

[0009] Optionally, the background noise sample sequence is decomposed in the frequency domain to extract the dominant noise frequency and noise energy density distribution as the frequency domain features; the filter stopband range is determined based on the frequency domain features, and a target frequency band filter corresponding to the filter stopband range is constructed; the target frequency band filter is used to filter the reference values ​​of the edge region, the center region, and the transition region respectively; the noise intensity index of the edge region is calculated, and when the noise intensity index is greater than a preset edge noise threshold, the noise in the edge region is determined to be excessive, and the reference value of the filtered edge region is amplified and enhanced using a noise pre-compensation enhancement coefficient.

[0010] Optionally, the mean capacitance and standard deviation of the reference values ​​of the filtered and enhanced edge regions and the center region are calculated, and the mean capacitance and standard deviation of the capacitance are used as capacitance distribution feature parameters; based on the first distance from the touch node in the transition region to the nearest edge region touch node and the second distance to the center point, a position weight coefficient is calculated; combining the position weight coefficient and the capacitance distribution feature parameters, a reference capacitance value of the touch node in the transition region is calculated; the mean capacitance of the edge region and the center region and the reference capacitance value of the transition region are matrix-mapped according to the spatial position of the touch node to construct the distributed reference capacitance matrix.

[0011] Optionally, in a dynamic sensing state with touch input, the dynamic capacitance sensing value of the touch node in the touch area is acquired; the difference between the dynamic capacitance sensing value and the reference value of the corresponding node in the distributed reference capacitance matrix is ​​calculated to obtain the actual capacitance change of each region; the average response value of the edge region and the average response value of the center region are calculated in the dynamic sensing state, and the ratio of the average response value of the edge region to the average response value of the center region is calculated to obtain the response difference ratio; the absolute deviation between the actual capacitance change of the transition region and the expected response corresponding to the distributed reference capacitance matrix is ​​calculated to obtain the signal matching deviation value.

[0012] Optionally, the initial difference ratio between the edge region and the center region under static reference conditions is obtained; the deviation of the difference ratio between the response difference ratio and the initial difference ratio is calculated; when the deviation of the difference ratio is greater than a preset deviation judgment threshold, if the response difference ratio is less than the initial difference ratio, the interference type is determined to be center region signal superposition interference; if the response difference ratio is greater than or equal to the initial difference ratio, the interference type is determined to be edge region signal attenuation interference; based on the interference type and the signal matching deviation value, the spatial distribution characteristics of the interference are obtained using a spatial distribution characterization method; the weighted deviation value of the signal matching difference in the spatial distribution characteristics of the interference is extracted, target touch nodes whose weighted deviation value exceeds a preset signal deviation threshold are screened out, and the connected regions containing the target touch nodes are identified as the key interference regions.

[0013] Optionally, the signal matching deviation values ​​of the touch nodes in each region are mapped into a two-dimensional deviation matrix according to the spatial coordinates of the touch nodes; the spatial weight matrix corresponding to the interference type is matched, and the two-dimensional deviation matrix and the spatial weight matrix are weighted to obtain a weighted deviation matrix as the spatial distribution feature of the interference.

[0014] Optionally, when the interference type is a signal superposition interference in the central region, the ratio of the expected capacitance change to the actual capacitance change in the central region is calculated as a deviation correction coefficient to suppress excessive response in the central region; when the interference type is a signal attenuation interference in the edge region, the ratio of the expected capacitance change to the actual capacitance change in the edge region is calculated as a deviation correction coefficient to enhance insufficient response in the edge region; the maximum deviation within the interference region is extracted as a global deviation correction intensity index; based on the noise intensity index of the edge region, a corresponding dynamic threshold is matched in the database; when the global deviation correction intensity index is greater than the dynamic threshold, it is determined that the actual capacitance change needs to be proportionally scaled, and a corresponding proportional scaling coefficient is generated as a deviation correction coefficient for the transition region.

[0015] Optionally, the response difference ratio is recalculated based on the actual capacitance change after compensation, and the balance evaluation index between the recalculated response difference ratio and the initial difference ratio is calculated; the proportion of unbalanced nodes with excessive deviation after compensation in the transition area is statistically analyzed; when both the balance evaluation index and the proportion of unbalanced nodes are lower than the preset balance judgment threshold, it is determined that the compensated touch area has reached the preset global balance state; when the preset global balance state is reached, the deviation correction coefficient of each area is locked as the touch consistency configuration parameter.

[0016] In a second aspect, embodiments of this application provide a partition-referenced distributed anti-interference projected capacitive touch system, the partition-referenced distributed anti-interference projected capacitive touch system comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors calling the computer instructions to cause the partition-referenced distributed anti-interference projected capacitive touch system to perform the method described in the first aspect and any possible implementation thereof.

[0017] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: By employing the above technical solution, the touch area is divided into edge, center, and transition regions according to spatial location characteristics, and the static capacitance reference value of each region under static reference conditions is obtained. Based on this, a target frequency band filter is constructed by extracting the frequency domain features of the background noise sample sequence, which can specifically filter out frequency domain interference components in the reference values ​​of each region. Furthermore, based on the filtered and enhanced reference values ​​of each region, capacitance distribution characteristic parameters are calculated, and a distributed reference capacitance matrix that continuously transitions from the edge to the center region is constructed. This distributed reference mechanism fully considers the differences in capacitance response characteristics at different locations within the touch area, overcoming the limitation of traditional globally unified references that cannot accurately reflect the actual touch state of each region. When a touch occurs, by combining the distributed reference capacitance matrix with dynamic capacitance sensing values ​​to calculate the signal matching deviation and response difference ratio of each region, the degree of response deviation in each region can be accurately quantified, and the type and region of interference can be identified, achieving precise localization of interference factors. Based on this, a deviation correction coefficient is calculated for each region according to the identified interference type and interference area. This coefficient is then used to specifically compensate for the dynamic capacitive sensing value. When the compensated touch area reaches a preset global equilibrium state, the deviation correction coefficient is locked as a touch consistency configuration parameter, thus establishing a complete zoned adaptive adjustment mechanism. This mechanism eliminates the impact of spatial response differences in touch areas on recognition accuracy by implementing differentiated benchmark adjustments and deviation compensation for different regions, improving the consistency and anti-interference capability of touch response, and enabling the touch system to meet the precise operation requirements of industrial control applications. Attached Figure Description

[0018] Figure 1 This is a schematic flowchart of a partitioned reference distributed anti-interference projected capacitive touch method disclosed in an embodiment of this application; Figure 2 This is another schematic flowchart of a partitioned reference distributed anti-interference projected capacitive touch method disclosed in an embodiment of this application; Figure 3This is a schematic diagram of the structure of a system provided in an embodiment of this application.

[0019] In the diagram: 301, Central Processing Unit; 302, Read-Only Memory; 303, Random Access Memory; 304, Bus; 305, Input / Output Interface; 306, Input Section; 307, Output Section; 308, Storage Section; 309, Communication Section; 310, Driver; 311, Removable Media. Detailed Implementation

[0020] To enable those skilled in the art to better understand the technical solution, the present invention will be described in detail below with reference to embodiments. The description in this part is only exemplary and explanatory, and should not be used to limit the scope of protection of the present invention in any way.

[0021] It should be noted that, in this document, the terms "comprising," "including," and any other variations are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Specific examples have been used in this document to illustrate the principles and implementation methods of the present invention. These examples are merely for the purpose of helping to understand the method and core ideas of the present invention. The above are only preferred embodiments of the present invention. It should be pointed out that, due to the limitations of written expression and the objective existence of infinite specific structures, those skilled in the art can make several improvements, modifications, or variations without departing from the principles of the present invention, and can also combine the above technical features in an appropriate manner. These improvements, modifications, variations, or combinations, or the direct application of the concept and technical solution of the present invention to other situations without modification, should all be considered within the scope of protection of the present invention.

[0022] This application provides a partitioned reference distributed anti-interference projected capacitive touch method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating a partitioned reference distributed anti-interference projected capacitive touch method provided in an embodiment of this application. The method is applied to a system, which refers to a hardware and software integrated platform capable of executing a partitioned reference distributed anti-interference projected capacitive touch program. The system can execute a partitioned reference distributed anti-interference projected capacitive touch program, and the method includes steps 101 to 106, as follows: Step 101: Obtain the static capacitance reference value and background noise sample sequence of the touch area under static reference state, and divide the static capacitance reference value into reference values ​​corresponding to multiple regions according to the touch position. The regions include edge regions, center regions and transition regions.

[0023] In the embodiments of this application, the static capacitance reference value refers to the initial capacitance value measured by each sensing node when no external touch object touches or approaches the touch panel. It is used to represent the inherent capacitance properties of the system under ideal no-load conditions, such as the basic capacitance readings fed back by each pixel of the screen when the device is powered on and no one is operating it.

[0024] Specifically, during the initial period without any touch events, capacitance data of all sensing nodes within the touch area and electromagnetic noise data from the environment are continuously collected to form static capacitance reference values ​​and background noise sample sequences. Based on the physical coordinate space of the touch area, the collected static capacitance reference values ​​are spatially divided according to their position coordinates. Nodes within a set distance from the physical boundary of the touch area are designated as edge regions, nodes within a set radius of the geometric center of the touch area are designated as central regions, and the remaining nodes between the edge and central regions are designated as transition regions, thus obtaining reference values ​​for multiple regions.

[0025] In one possible implementation, the static capacitance reference value and background noise sample sequence of the touch area under static reference state are obtained, and the static capacitance reference value is divided into reference values ​​corresponding to multiple regions according to the touch position. The regions include edge regions, center regions, and transition regions. Specifically, steps 1011-1013 are included, as follows: Step 1011: In the static reference state without touch input, obtain the initial capacitance value of each touch node in the touch area as the static capacitance reference value; in the static reference state, continuously collect a sequence containing capacitance value fluctuation data as the background noise sample sequence.

[0026] In this application embodiment, the static reference state refers to the system's default working environment when no conductive object is in contact with or hovering near the touch panel surface. It is used to represent the pure underlying physical state of the touch system when it is not disturbed by external touch operations, such as the state when the device is just turned on and the screen surface is completely clean and free of foreign objects.

[0027] Specifically, after confirming that the touch area is in a static baseline state with no touch input, a capacitance scanning program is initiated. The initial capacitance value of each touch node within the touch area is read row by row and column by column. All read initial capacitance values ​​are collected and summarized to obtain the initial capacitance value of each touch node within the touch area as the static capacitance baseline value. Simultaneously, while maintaining the static baseline state, multiple repeated samplings are performed within a continuous time window at a preset sampling frequency. The capacitance value of each touch node at each sampling moment is recorded. These time-varying capacitance data are arranged and combined in chronological order to continuously collect a sequence containing capacitance value fluctuation data as a background noise sample sequence.

[0028] Step 1012: Calculate the shortest distance from each touch node to the boundary of the touch area and the distance to the geometric center.

[0029] In the embodiments of this application, a touch node refers to an independent capacitance sensing unit formed by the overlapping of driving electrodes and receiving electrodes inside the touch panel. It is used to represent the smallest physical coordinate point that can independently sense local capacitance changes and output corresponding electrical signals, such as a specific row and column intersection sensing point in the touch screen grid circuit.

[0030] Specifically, the physical boundary dimensions of the touch area and the two-dimensional coordinate data of each touch node are obtained. For each touch node, the vertical distance from its coordinate position to the four physical boundaries of the touch area (top, bottom, left, and right) is calculated. These four vertical distances are compared, and the minimum value is extracted as the shortest distance from each touch node to the boundary of the touch area. Simultaneously, the absolute coordinates of the geometric center are calculated based on the overall length and width dimensions of the touch area. Using the distance calculation logic between two points, the linear spatial distance between the coordinates of each touch node and the coordinates of the geometric center is calculated, and this linear spatial distance is taken as the distance from each touch node to the geometric center.

[0031] Step 1013: Determine the distance boundary threshold based on the shortest distance and the distance to the geometric center according to a preset ratio, and divide the static capacitance reference value into the reference value of the edge region, the reference value of the center region, and the reference value of the transition region according to the distance boundary threshold.

[0032] In this embodiment of the application, the distance boundary threshold refers to a numerical limit set according to the physical size and node position characteristics of the touch panel, which is used to represent the spatial distance judgment standard for distinguishing the edge, center and transition zone, such as setting a numerical boundary of one centimeter from the edge of the screen or three centimeters from the center.

[0033] Specifically, the maximum value of the shortest distance and the maximum value of the distance to the geometric center of all touch nodes are extracted. The maximum value of the shortest distance is multiplied by a preset first ratio value to obtain a first boundary value; the maximum value of the distance to the geometric center is multiplied by a preset second ratio value to obtain a second boundary value. The first and second boundary values ​​are used together to determine the distance boundary threshold. All touch nodes are traversed, and the shortest distance of each touch node is compared with the first boundary value. If it is less than the first boundary value, the static capacitance reference value corresponding to that node is classified as the reference value of the edge region. The distance of each touch node to the geometric center is compared with the second boundary value. If it is less than the second boundary value, the static capacitance reference value corresponding to that node is classified as the reference value of the center region. The static capacitance reference values ​​corresponding to the remaining touch nodes that do not meet the above two conditions are classified as the reference values ​​of the transition region.

[0034] Step 102: Extract the frequency domain features of the background noise sample sequence to construct the target frequency band filter, use the filter to filter the reference value of each region, and pre-compensate and enhance the reference value of the filtered edge region when the noise in the edge region exceeds the standard.

[0035] In the embodiments of this application, the target frequency band filter refers to a data filtering model specifically designed based on the frequency distribution characteristics of environmental noise. It is used to represent an algorithm component that can allow a specific effective signal frequency band to pass through and attenuate the noise frequency band, such as a low-pass or band-pass digital filter program built for specific high-frequency motor interference.

[0036] Specifically, the acquired background noise sample sequence undergoes a time-domain to frequency-domain transformation to extract the amplitude distribution characteristics of the noise signal at different frequencies. The cutoff frequency is determined based on the frequency range of the amplitude concentration, and a target frequency band filter is constructed accordingly. Reference values ​​for the edge region, center region, and transition region are input into this filter for signal smoothing. The difference between the noise amplitude in the edge region and a preset noise threshold is calculated during the filtering process. When the noise amplitude in the edge region is determined to be greater than the preset noise threshold, the reference value and the compensation value of the filtered edge region are added according to a preset compensation step size to complete the pre-compensation enhancement of the reference value of the filtered edge region.

[0037] In one possible implementation, frequency domain features of the background noise sample sequence are extracted to construct a target frequency band filter. The filter is used to filter the reference values ​​of each region, and when the noise in the edge region exceeds the standard, the reference values ​​of the filtered edge region are pre-compensated and enhanced. Specifically, steps 1021-1023 are included, as follows: Step 1021: Perform frequency domain decomposition on the background noise sample sequence and extract the dominant noise frequency and noise energy density distribution as frequency domain features.

[0038] In the embodiments of this application, frequency domain characteristics refer to the composition and distribution characteristics of a signal in the frequency domain, used to represent the amplitude and energy state of a time-domain signal at different frequency points after mathematical transformation, such as a set of spectral data containing specific high-frequency interference peaks.

[0039] Specifically, a background noise sample sequence is acquired, and a Discrete Fourier Transform (DFT) is performed on the time-dimensional capacitance fluctuation data in the sequence to convert the time-dimensional signal data into frequency-dimensional spectral data, completing frequency domain decomposition. In the obtained spectral data, the frequency point with the largest amplitude is identified, and the frequency value corresponding to this point is extracted as the dominant noise frequency. Simultaneously, the squared amplitude values ​​within each frequency interval of the spectral data are calculated, and the squared amplitude values ​​of each frequency interval are arranged in ascending order of frequency to obtain the noise energy density distribution. The extracted dominant noise frequency and the noise energy density distribution are combined as the frequency domain features.

[0040] Step 1022: Determine the filter stopband range based on frequency domain characteristics, and construct a target frequency band filter corresponding to the filter stopband range.

[0041] In the embodiments of this application, the filter stopband range refers to the frequency range that is set to be attenuated or completely blocked during signal processing. It is used to represent the frequency boundary setting for specific interference noise in filter design, such as the power frequency interference frequency range from 50 Hz to 60 Hz.

[0042] Specifically, the dominant noise frequency and noise energy density distribution in the frequency domain are obtained. Within the noise energy density distribution, a continuous frequency range with energy density values ​​greater than a preset energy threshold is identified. Using the dominant noise frequency as a central reference point, and combining the lower and upper limit frequencies of the identified continuous frequency ranges, the lower and upper boundary frequencies to be suppressed are determined. The interval between the lower and upper boundary frequencies is defined as the filter stopband. Based on the determined filter stopband, the cutoff frequency and attenuation coefficient parameters of the digital filter are set, generating the corresponding filter coefficient matrix, thereby constructing a target frequency band filter corresponding to the filter stopband.

[0043] Step 1023: Use the target frequency band filter to filter the reference values ​​of the edge region, center region and transition region respectively; calculate the noise intensity index of the edge region. When the noise intensity index is greater than the preset edge noise threshold, it is determined that the noise of the edge region exceeds the standard, and the noise pre-compensation enhancement coefficient is used to amplify and enhance the reference value of the filtered edge region.

[0044] In the embodiments of this application, the noise intensity index refers to a numerical metric standard for quantifying and assessing the severity of electromagnetic interference in a specific area. It is used to represent the relative relationship between the magnitude of useless signal energy and the normal signal reference in the area. For example, it is a specific value reflecting the severity of interference obtained by calculating the variance of the capacitance fluctuation of edge nodes.

[0045] Specifically, the reference values ​​for the edge region, the center region, and the transition region are convolved with the coefficient matrix of the target frequency band filter, respectively, to output smoothed values, thus completing the filtering process for the reference values ​​of each region. The capacitance fluctuation values ​​of each node in the edge region before filtering are extracted, and the root mean square (RMS) values ​​of these capacitance fluctuation values ​​are calculated. These calculated RMS values ​​are used as the noise intensity index for the edge region. The noise intensity index is compared with a preset edge noise threshold. If the noise intensity index is greater than the edge noise threshold, the noise in the edge region is considered excessive. After determining that the noise exceeds the threshold, a preset noise pre-compensation enhancement coefficient is obtained. The filtered reference value of the edge region is multiplied by the noise pre-compensation enhancement coefficient to obtain a new reference value. This multiplication process is used to amplify and enhance the reference value of the filtered edge region.

[0046] Step 103: Based on the reference values ​​of each region after filtering and enhancement, calculate the capacitance distribution characteristic parameters, and construct a distributed reference capacitance matrix that transitions continuously from the edge region to the center region according to the capacitance distribution characteristic parameters.

[0047] In the embodiments of this application, the distributed reference capacitance matrix refers to a two-dimensional data set containing all nodes of the touch area and whose values ​​exhibit spatial gradient changes. It is used to represent an ideal capacitance reference standard in which each area is smoothly connected in space after calibration, such as a tabular data structure with a high value at the center and decreasing towards the surrounding edges at a specific ratio.

[0048] Specifically, the average value, variance, and numerical gradient at the boundary of adjacent regions are statistically analyzed for the baseline values ​​of each region after filtering and enhancement. These statistical results are used as capacitance distribution characteristic parameters. Starting from the characteristic parameters of the central region and ending at the characteristic parameters of the edge regions, a spatial interpolation algorithm combined with the capacitance distribution characteristic parameters is used to calculate the reference value of each coordinate node within the transition region. The calculated reference values ​​of all nodes are then arranged and combined according to the actual physical row and column coordinates of the touch area to generate a distributed reference capacitance matrix that covers the entire screen and whose values ​​transition continuously from the edge region to the center region.

[0049] In one possible implementation, frequency domain features of the background noise sample sequence are extracted to construct a target frequency band filter. The filter is used to filter the reference values ​​of each region, and when the noise in the edge region exceeds the standard, the reference values ​​of the filtered edge region are pre-compensated and enhanced. Specifically, steps 1031-1033 are included, as follows: Step 1031: Calculate the mean capacitance and standard deviation of the reference values ​​of the edge region and the center region after filtering and enhancement, and use the mean capacitance and standard deviation of the capacitance as characteristic parameters of capacitance distribution.

[0050] In the embodiments of this application, the capacitance distribution characteristic parameter refers to a statistical index that reflects the overall central tendency and dispersion of capacitance values ​​in a specific region. It is used to represent the macroscopic statistical characteristics of the spatial distribution of the processed benchmark capacitance data, such as a set of values ​​including the arithmetic mean of capacitance in a specific region and the degree of deviation from the mean.

[0051] Specifically, the process involves obtaining the baseline value sets for the edge regions after filtering and enhancement, as well as the baseline value set for the center region after filtering. For the baseline value set of the edge regions, the baseline values ​​of all nodes within the set are summed, and the result is divided by the total number of nodes in the edge region to obtain the mean capacitance of the edge region. The square of the difference between the baseline value of each node in the edge region and the mean capacitance is calculated, and all squares are summed and divided by the total number of nodes. The square root of this division result is then taken to obtain the standard deviation of the capacitance in the edge region. The same mathematical logic is applied to the baseline value set of the center region, calculating the mean capacitance and standard deviation for the center region. The calculated mean capacitance and standard deviation for both the edge and center regions are then extracted and used as characteristic parameters of the capacitance distribution.

[0052] Step 1032: Calculate the position weight coefficient based on the first distance from the touch node in the transition area to the nearest edge touch node and the second distance to the center point.

[0053] In this embodiment, the position weight coefficient is a proportional value calculated based on the relative spatial distance to measure the degree of influence of different regions on the current node value. It is used to represent the weight distribution relationship of the transition region node when fusing the features of the two regions. For example, it is a decimal multiplier between zero and one calculated based on the distance.

[0054] Specifically, the process iterates through each touch node within the transition area, acquiring the coordinate data of the current touch node. It calculates the linear spatial distance between the current touch node's coordinates and the coordinates of all edge area touch nodes, extracting the minimum value among these linear spatial distances and using it as the first distance from the touch node within the transition area to the nearest edge area touch node. Simultaneously, it acquires the coordinate data of the touch area's center point, calculates the linear spatial distance between the current touch node's coordinates and the center point's coordinates, and uses this as the second distance. The first and second distances are summed to obtain the total distance. The second distance is divided by the total distance to obtain the first proportional component; the first distance is also divided by the total distance to obtain the second proportional component. The calculated first and second proportional components are combined to calculate the position weight coefficient.

[0055] Step 1033: Combine the position weight coefficient and capacitance distribution characteristic parameters to calculate the reference capacitance value of the touch node in the transition area; map the average capacitance of the edge area and the center area and the reference capacitance value of the transition area according to the spatial position of the touch node to construct a distributed reference capacitance matrix.

[0056] In this embodiment, the distributed reference capacitance matrix refers to a two-dimensional array of reference capacitance values ​​arranged according to the actual physical topology of the touch panel. It is used to represent the standard capacitance reference base map after regionalization and fusion calculation at each discrete coordinate point in the entire touch area, such as a data table with the same number of rows and columns as the touch grid and filled with the reference values ​​of each area.

[0057] Specifically, the mean capacitance of the edge region and the mean capacitance of the center region are obtained from the position weight coefficients and capacitance distribution characteristic parameters. For each touch node in the transition region, the mean capacitance of the edge region is multiplied by the first proportional component corresponding to that node to obtain a first value, and the mean capacitance of the center region is multiplied by the second proportional component corresponding to that node to obtain a second value. The first value and the second value are then summed to calculate the reference capacitance value of the touch node in the transition region. A blank two-dimensional matrix with the same number of rows and columns as the physical nodes in the touch region is created. According to the actual two-dimensional spatial coordinates of each touch node, the mean capacitance of the edge region is filled into the coordinate positions corresponding to the edge nodes in the matrix, the mean capacitance of the center region is filled into the coordinate positions corresponding to the center nodes in the matrix, and the calculated reference capacitance value of the transition region is filled into the coordinate positions corresponding to the transition nodes in the matrix one by one. Through the above numerical filling operation of matrix mapping according to the spatial position of the touch nodes, a distributed reference capacitance matrix is ​​constructed.

[0058] Step 104: Obtain the dynamic capacitance sensing value of the touch area under dynamic sensing state, and calculate the signal matching deviation value and response difference ratio of each area by combining the distributed reference capacitance matrix and the dynamic capacitance sensing value.

[0059] In the embodiments of this application, dynamic capacitance sensing value refers to the current capacitance measurement data of each sensing node collected in real time when the touch device is in working state and there may be touch operation. It is used to represent the transient capacitance state including potential touch signals and real-time environmental changes, such as the real-time capacitance data read by the sensor when the user's finger presses the screen.

[0060] Specifically, during the touch detection cycle, the current capacitance data of all nodes within the touch area is scanned and read in real time as dynamic capacitance sensing values. The dynamic capacitance sensing values ​​are subtracted from the reference values ​​at the corresponding coordinate positions in the distributed reference capacitance matrix, and the absolute value of the difference is calculated as the signal matching deviation value for each region. The calculated signal matching deviation value is then divided by the corresponding reference value in the distributed reference capacitance matrix to obtain the response difference ratio for each region.

[0061] In one possible implementation, the dynamic capacitive sensing value of the touch area under dynamic sensing state is obtained. Combining the distributed reference capacitance matrix with the dynamic capacitive sensing value, the signal matching deviation value and response difference ratio of each area are calculated. Specifically, this includes steps 1041-1043, as follows: Step 1041: In a dynamic sensing state with touch input, obtain the dynamic capacitance sensing value of the touch node in the touch area; calculate the difference between the dynamic capacitance sensing value and the reference value of the corresponding node in the distributed reference capacitance matrix to obtain the actual capacitance change of each area.

[0062] In this embodiment, the actual capacitance change refers to the capacitance fluctuation difference generated when the touch node is subjected to external touch. It is used to represent the degree of deviation between the currently collected capacitance data and the reference data in the non-touch state. For example, it is the specific difference obtained by subtracting the preset reference map value of a certain touch coordinate point from the capacitance value currently measured at that point.

[0063] Specifically, upon detecting an external touch operation that triggers dynamic sensing, all touch nodes within the touch area are traversed, and the real-time capacitance digital conversion result of each touch node is read one by one, with the read result used as the dynamic capacitance sensing value. A pre-constructed distributed reference capacitance matrix is ​​obtained, and the node reference value corresponding to the current two-dimensional spatial row and column coordinates of the touch node is found and extracted from the distributed reference capacitance matrix. The obtained dynamic capacitance sensing value is subtracted from the extracted corresponding node reference value, and the difference data is obtained by performing a subtraction operation. The difference data of each node is classified according to the physical spatial division of the edge region, center region, and transition region to which the touch node belongs, and the calculated difference data of each node is assigned to the corresponding region data set, thereby obtaining the actual capacitance change of each region.

[0064] Step 1042: Calculate the mean response of the edge region and the mean response of the center region under dynamic sensing conditions, and calculate the ratio of the mean response of the edge region to the mean response of the center region to obtain the response difference ratio.

[0065] In the embodiments of this application, the response difference ratio refers to the relative proportion of the sensitivity of different touch areas to touch operation, which is used to represent the multiple relationship between the overall capacitive response intensity of the edge area and the overall capacitive response intensity of the center area. For example, it is a quotient obtained by dividing the average change of all nodes in the edge area by the average change of all nodes in the center area.

[0066] Specifically, the actual capacitance changes of all touch nodes in the edge region under dynamic sensing conditions are obtained. These changes are then summed to obtain the total change value for the edge region. This total change value is divided by the total number of touch nodes in the edge region to calculate the average response value of the edge region under dynamic sensing conditions. Similarly, the actual capacitance changes of all touch nodes in the center region under dynamic sensing conditions are obtained. These changes are then summed to obtain the total change value for the center region. This total change value is divided by the total number of touch nodes in the center region to calculate the average response value of the center region under dynamic sensing conditions. Finally, the average response value of the edge region is used as the dividend, and the average response value of the center region is used as the divisor. The ratio of the average response value of the edge region to the average response value of the center region is calculated, and the result of this division is the response difference ratio.

[0067] Step 1043: Calculate the absolute deviation between the actual capacitance change in the transition region and the expected response corresponding to the distributed reference capacitance matrix to obtain the signal matching deviation value.

[0068] In the embodiments of this application, the signal matching deviation value refers to the absolute value of the difference between the actual detected signal change and the theoretically predicted signal. It is used to represent the degree of inconsistency between the actual capacitance fluctuation in the transition region and the ideal response state derived based on the reference matrix. For example, it is a positive number obtained by subtracting the expected response from the actual measured capacitance change and taking the absolute value.

[0069] Specifically, the actual capacitance change of each touch node within the transition area is obtained. Based on the reference value of the corresponding node in the transition area within the distributed reference capacitance matrix and the preset touch response conversion coefficient, the reference value and the touch response conversion coefficient are multiplied to calculate the expected response corresponding to the distributed reference capacitance matrix. For each touch node within the transition area, the actual capacitance change of that node is subtracted from its corresponding expected response, and the difference is obtained. The absolute value of the calculated difference is then calculated to eliminate the influence of the sign, and the absolute deviation between the actual capacitance change in the transition area and the expected response corresponding to the distributed reference capacitance matrix is ​​calculated. The final absolute value data is extracted to obtain the signal matching deviation value.

[0070] Step 105: Identify the type of interference based on the response difference ratio and identify the interference area based on the signal matching deviation value.

[0071] In the embodiments of this application, the interference type refers to the classification of external influencing factors that cause abnormal changes in the capacitance sensing value. It is used to represent the specific mode of action of electromagnetic interference on the touch signal, such as superposition interference that causes abnormal increase in signal or attenuation interference that causes abnormal decrease in signal.

[0072] Specifically, the response difference ratio of each region is compared with a preset ratio threshold range. If the response difference ratio deviates positively and exceeds the first threshold range, it is determined to be signal superposition interference; if the response difference ratio deviates negatively and exceeds the second threshold range, it is determined to be signal attenuation interference. This completes the identification of the interference type. The signal matching deviation values ​​of each region are traversed, and the coordinate nodes with signal matching deviation values ​​greater than a preset deviation safety threshold are extracted. The physical space range of these nodes is then defined, thereby identifying the interference region.

[0073] Step 106: Calculate the deviation correction coefficient for each region based on the interference type and interference area, and use the deviation correction coefficient to compensate for the dynamic capacitive sensing value. When the compensated touch area reaches the preset global equilibrium state, lock the deviation correction coefficient as the touch consistency configuration parameter.

[0074] In the embodiments of this application, the deviation correction coefficient refers to the dynamic adjustment parameter calculated to eliminate numerical deviations caused by external interference. It is used to represent the multiplier or additive compensation amount that pulls the abnormal capacitance value back to the normal reference level. For example, the value set for a specific interference area is a gain amplification factor of 1.2.

[0075] Specifically, for the identified interference areas, based on the preset adjustment step size corresponding to the interference type, the signal matching deviation value is multiplied by the basic weight to calculate the deviation correction coefficient for each area. The dynamic capacitance sensing value is multiplied or added to the calculated deviation correction coefficient to obtain the compensated capacitance value. The variance of the capacitance value of each area after compensation is calculated, and it is determined whether the variance is less than the preset equalization threshold. If it is less than the threshold, it is determined that the preset global equalization state has been reached. At this point, the coefficient update is stopped, and the current deviation correction coefficient is saved to non-volatile memory and locked as a touch consistency configuration parameter.

[0076] In one specific embodiment, the balance evaluation index is obtained by calculating the percentage of relative deviation between the compensated side-to-middle response ratio and the initial difference ratio. The proportion of unbalanced nodes is obtained by statistically analyzing the ratio of the number of nodes with excessive deviations after compensation within the transition region to the total number of nodes in that region. These two indicators correspond to independent balance judgment thresholds and are not the same parameter.

[0077] The threshold corresponding to the balance evaluation index is determined by collecting edge-to-center response data from no fewer than 50 sets of standard qualified samples under normal usage conditions, using the mean of the natural fluctuation range plus 1.5 times the standard deviation as a reference lower bound. In a specific embodiment, this threshold is preferably 8%, which can be tightened to 3% to 5% for high-reliability scenarios and relaxed to 15% to 20% for industrial scenarios. The threshold corresponding to the proportion of unbalanced nodes is set as twice the natural dispersion rate of nodes in the transition area of ​​the panel process used, preferably 10%.

[0078] The pre-defined global equilibrium state employs a dual-condition judgment logic where two indicators must be met simultaneously. The equilibrium evaluation indicator is a global macro-level quantity, reflecting the overall edge-center equilibrium level, but may mask local anomalies; the proportion of unbalanced nodes is a local micro-level quantity, specifically constraining the spatial continuity of the transition region. The absence of either indicator prevents the global equilibrium state from being deemed achieved, thus preventing situations where macro-level compliance is met but transition region response jumps exist, or where local continuity exists but global systemic deviations remain, leading to misjudgment as acceptable.

[0079] If an equilibrium state is not reached after a preset maximum number of iterations (e.g., 5), the system maintains the configuration parameters that were successfully locked the last time and reports an anomaly flag to the upper application layer to prevent it from falling into an infinite compensation loop under extreme interference conditions.

[0080] In one possible implementation, the deviation correction coefficient for each region is calculated based on the interference type and interference area, specifically including steps 1061-1063, as follows: Step 1061: When the interference type is signal superposition interference in the central region, calculate the ratio of the expected capacitance change to the actual capacitance change in the central region as the deviation correction coefficient used to suppress the excessive response in the central region.

[0081] In the embodiments of this application, the deviation correction coefficient refers to the proportional multiplier used to adjust and calibrate the abnormal capacitance response value during signal processing. It is used to represent the relative ratio between the expected standard signal state and the currently detected abnormal signal state. For example, it is a decimal value used to suppress over-response, calculated by dividing the expected capacitance change by the actual capacitance change.

[0082] Specifically, the system obtains the interference type determination result corresponding to the current touch operation. When the interference type is determined to be signal superposition interference in the central region, the system obtains the expected capacitance change and the corresponding actual capacitance change of each touch node in the central region. For each touch node in the central region, the system performs a division operation, using the obtained expected capacitance change as the dividend and the corresponding actual capacitance change as the divisor, to calculate the ratio of the expected capacitance change to the actual capacitance change in the central region. The ratio obtained from this division operation is extracted and used as a deviation correction coefficient to suppress excessive response in the central region.

[0083] Step 1062: When the interference type is edge region signal attenuation type interference, calculate the ratio of the expected capacitance change to the actual capacitance change in the edge region as the deviation correction coefficient used to enhance the insufficient response in the edge region.

[0084] In the embodiments of this application, the deviation correction coefficient refers to the compensation parameter that amplifies the numerical value for insufficient response of the touch node. It is used to represent the quotient between the standard capacitance change value under ideal conditions and the actual capacitance change value after interference attenuation. For example, it is a multiplier greater than one obtained by dividing the expected change amount of the edge region by the actual change amount to enhance the signal.

[0085] Specifically, the system reads the status flag of the currently identified interference type. When the interference type is identified as edge region signal attenuation interference, the system extracts the pre-set expected capacitance change and the real-time actual capacitance change of the touch node within the edge region. A division logic operation is performed with the expected capacitance change in the edge region as the dividend and the actual capacitance change as the divisor to calculate the ratio of the expected capacitance change to the actual capacitance change in the edge region. The numerical result obtained after the above division operation is then directly used as a deviation correction coefficient to enhance the insufficient response in the edge region.

[0086] Step 1063: Extract the maximum deviation within the interference area as the global deviation correction intensity index; based on the noise intensity index of the edge region, match the corresponding dynamic threshold in the database. When the global deviation correction intensity index is greater than the dynamic threshold, determine that the actual capacitance change needs to be scaled and adjusted proportionally, and generate the corresponding scaling factor as the deviation correction factor for the transition region.

[0087] In this embodiment of the application, the global deviation correction intensity index refers to a quantitative value that measures the most severe deviation of the capacitance signal from the normal reference in the entire interference area. It is used to represent the maximum extreme value of the difference between the actual detected signal and the expected signal under the current interference environment, such as the deviation value with the largest absolute value selected from the deviation data of all interference nodes.

[0088] Specifically, the process iterates through all touch nodes within the interference area, obtaining the deviation between the actual capacitance change and the expected response for each node. These deviation values ​​are compared to find the maximum deviation within the interference area, which is then used as the global deviation correction strength index. A pre-calculated noise intensity index for the edge region is obtained and used as a query keyword in a pre-defined database to match the corresponding dynamic threshold. The global deviation correction strength index is compared with the matched dynamic threshold. If the global deviation correction strength index is greater than the dynamic threshold, a scaling adjustment of the actual capacitance change is required. A scaling factor is calculated based on the relationship between the global deviation correction strength index and the dynamic threshold, and this scaling factor is used as the deviation correction factor for the transition region.

[0089] In one possible implementation, once the compensated touch area reaches a preset global equilibrium state, the deviation correction coefficient is locked as a touch consistency configuration parameter, specifically including steps 1064-1066, as follows: Step 1064: Recalculate the response difference ratio based on the actual capacitance change after compensation, and calculate the balance evaluation index between the recalculated response difference ratio and the initial difference ratio.

[0090] In this embodiment of the application, the balance evaluation index refers to a quantitative value that measures the degree of change in the response difference of the touch area before and after compensation adjustment. It is used to represent the closeness or deviation between the recalculated response difference ratio and the initial difference ratio when it was not compensated. For example, it is a decimal that reflects the balance improvement by subtracting the recalculated response difference ratio from the initial difference ratio, taking the absolute value, and then normalizing it.

[0091] Specifically, the actual capacitance change of each touch node after compensation is obtained. The actual capacitance changes after compensation are summed and averaged to obtain the average response values ​​of the edge and center regions after compensation. The average response value of the edge regions is used as the dividend, and the average response value of the center regions is used as the divisor to perform a division operation, recalculating the response difference ratio based on the actual capacitance changes after compensation. The initial difference ratio recorded before compensation is obtained. The recalculated response difference ratio is then compared with the initial difference ratio. The absolute value of the difference is taken as a measure of the degree of difference between the two, thus calculating the balance evaluation index between the recalculated and initial response difference ratios.

[0092] Step 1065: Calculate the percentage of unbalanced nodes with excessive deviations after compensation processing within the transition area.

[0093] In this embodiment of the application, the unbalanced node ratio refers to the ratio of the number of nodes whose capacitance deviation still exceeds the specified range after compensation processing in a specific area to the total number of nodes in that area. It is used to represent the overall share of abnormal touch points in the transition area whose compensation effect has not met the standard. For example, it is a percentage value obtained by dividing the number of nodes with excessive deviation by the total number of nodes in the transition area.

[0094] Specifically, the process iterates through each touch node within the transition area, obtaining the actual capacitance change and corresponding expected response value after compensation. The actual capacitance change is subtracted from the expected response value, and the absolute value is taken to calculate the post-compensation deviation for each touch node. This post-compensation deviation is then compared to a pre-set upper limit for allowable deviation. If the post-compensation deviation of a touch node exceeds this upper limit, it is marked as an unbalanced node with excessive deviation. Each marked unbalanced node is counted to obtain the total number of unbalanced nodes. The total number of touch nodes within the transition area is then calculated. Using the total number of unbalanced nodes as the dividend and the total number of touch nodes within the transition area as the divisor, a division operation is performed to determine the percentage of unbalanced nodes with excessive deviation after compensation within the transition area.

[0095] Step 1066: When both the balance evaluation index and the proportion of unbalanced nodes are lower than the preset balance judgment threshold, the compensated touch area is judged to have reached the preset global balance state; when the preset global balance state is reached, the deviation correction coefficient of each area is locked as the touch consistency configuration parameter.

[0096] In this application embodiment, the touch consistency configuration parameter refers to the baseline setting value used to standardize the response characteristics of each touch area after the system reaches the global balance judgment condition. It is used to represent the set of optimal deviation correction coefficients for each area that are finally determined after multiple rounds of calculation and verification. For example, it is a set of fixed configuration data that includes the corresponding multipliers of the edge area, the center area and the transition area and is written into the system's read-only storage space.

[0097] Specifically, the system obtains a pre-set balance judgment threshold, along with the currently calculated balance evaluation index and the statistically derived percentage of unbalanced nodes. The balance evaluation index is compared to the balance judgment threshold, and the percentage of unbalanced nodes is also compared to the balance judgment threshold. When both the balance evaluation index and the percentage of unbalanced nodes are below the balance judgment threshold (i.e., both are below the preset balance judgment threshold), the compensated touch area is determined to have reached a preset global balance state. If the determination result indicates that the preset global balance state has been reached, the deviation correction coefficients corresponding to each touch area are extracted and locked as touch consistency configuration parameters, i.e., these deviation correction coefficients are saved as unchangeable fixed values.

[0098] In the above embodiments, the quantification and preliminary evaluation of the basic capacitance change in the touch area are achieved by acquiring the dynamic capacitance sensing value and calculating the difference in the basic response. To further improve the anti-interference capability of the touch system in complex interference environments and establish a mechanism for accurate identification of interference types and location of key areas, this application also provides a partitioned reference distributed anti-interference projected capacitive touch method. This method determines the interference type by analyzing the deviation of the difference ratio between the static reference and the dynamic sensing state, constructs a mapping relationship of a two-dimensional weighted deviation matrix by combining the spatial weight matrix, and performs connected region screening of the target touch node, enabling the touch system to more accurately identify interference characteristics in complex environments and lock key interference areas. The following is a combination of... Figure 2 Another partition-referenced distributed anti-interference projected capacitive touch method in the embodiments of this application is described below: Please see Figure 2 This is a flowchart illustrating another partitioned reference distributed anti-interference projected capacitive touch method in an embodiment of this application.

[0099] Step 201: Obtain the initial difference ratio between the edge region and the center region under static baseline conditions; calculate the deviation of the difference ratio between the response difference ratio and the initial difference ratio.

[0100] In this embodiment of the application, the difference ratio deviation refers to the quantitative difference between the response difference ratio in dynamic sensing state and the initial difference ratio in static reference state. It is used to indicate the severity of the deviation of the internal and external response ratio of the current touch area from the initial normal ratio after being affected by external factors. For example, it is a value that reflects the magnitude of the deviation by subtracting the pre-recorded initial difference ratio from the currently calculated response difference ratio and taking the absolute value.

[0101] Specifically, the initial difference ratio between the edge region and the center region under the static baseline state, pre-stored in memory, is read. The response difference ratio calculated under the current dynamic sensing state is obtained. The obtained response difference ratio is subtracted from the initial difference ratio; that is, the response difference ratio is used as the minuend, and the initial difference ratio is used as the subtrahend, to calculate the difference. The absolute value of the difference obtained from the above subtraction operation is performed to eliminate the influence of the positive and negative signs, thereby calculating the deviation of the response difference ratio from the initial difference ratio.

[0102] Step 202: When the deviation of the difference ratio is greater than the preset deviation judgment threshold, if the response difference ratio is less than the initial difference ratio, the interference type is determined to be signal superposition interference in the central area; if the response difference ratio is greater than or equal to the initial difference ratio, the interference type is determined to be signal attenuation interference in the edge area.

[0103] In this application embodiment, the central area signal superposition type interference refers to the phenomenon that the capacitance value of the central area of ​​the touch panel is abnormally increased due to the influence of external environmental noise or stray capacitance. It is used to indicate that the actual response intensity of the central area has an abnormally high ratio relative to the edge area. For example, the capacitance change measured in the central area due to water droplet adhesion is much greater than the change that should occur during normal touch.

[0104] Specifically, a pre-set deviation threshold is obtained, and the calculated deviation ratio is compared with the deviation threshold. When the deviation ratio is greater than the pre-set threshold, the response deviation ratio is further compared with the initial deviation ratio. If the response deviation ratio is less than the initial deviation ratio, the interference type is determined to be central region signal superposition interference. If the response deviation ratio is greater than or equal to the initial deviation ratio, the interference type is determined to be edge region signal attenuation interference.

[0105] Step 203: Based on the interference type and signal matching deviation value, obtain the spatial distribution characteristics of the interference using a spatial distribution characterization method.

[0106] In this embodiment, the interference spatial distribution feature refers to a data set that reflects the intensity arrangement and aggregation state of abnormal interference signals at various positions on the two-dimensional physical plane of the touch panel. It is used to represent the spatial topology and distribution pattern of different touch nodes under interference. For example, it is a set of feature vectors that record the magnitude of the signal matching deviation value at each touch coordinate point and the gradient change of the deviation between adjacent nodes in the form of a matrix.

[0107] Specifically, the interference type is determined, and the signal matching deviation value corresponding to each touch node is extracted. Based on the interference type, a corresponding spatial distribution representation method is determined, which includes constructing a two-dimensional coordinate mapping matrix. The position coordinates of all touch nodes within the touch area are used as the row and column indices of the matrix, and the signal matching deviation value corresponding to each touch node is filled into the corresponding position in the two-dimensional coordinate mapping matrix according to its position coordinates. Based on the interference type and signal matching deviation value, using the aforementioned spatial distribution representation method of constructing a matrix and filling in values, the matrix data after filling in the values ​​is extracted and integrated to obtain the spatial distribution characteristics of the interference.

[0108] In one possible implementation, based on the interference type and signal matching deviation value, the spatial distribution characteristics of the interference are obtained using a spatial distribution characterization method, specifically including steps 2031-2032, as follows: Step 2031: Map the signal matching deviation values ​​of the touch nodes in each region into a two-dimensional deviation matrix according to the spatial coordinates of the touch nodes.

[0109] In this embodiment, the two-dimensional deviation matrix refers to a planar array data containing the signal deviation values ​​of each node, constructed according to the row and column arrangement rules of the physical touch points on the touch panel. It is used to represent the spatial distribution of signal matching deviation values ​​at different spatial locations within the touch area. For example, it is a two-dimensional data table with the same number of rows and columns as the touch sensor grid, and each element records the signal matching deviation value of the corresponding coordinate point.

[0110] Specifically, the signal matching deviation value of each touch node in each region is obtained, along with the corresponding horizontal and vertical coordinates of each touch node on the touch panel. An initial two-dimensional matrix structure is created in memory, using the horizontal coordinates as column indices and the vertical coordinates as row indices. All touch nodes in each region are traversed, and the signal matching deviation value of each node is filled into the corresponding position in the two-dimensional matrix structure according to its row and column indices. Through this coordinate mapping and value filling operation, the signal matching deviation values ​​of the touch nodes in each region are mapped into a two-dimensional deviation matrix based on the spatial coordinates of the touch nodes.

[0111] Step 2032: Match the corresponding spatial weight matrix according to the interference type, and perform weighted calculation on the two-dimensional deviation matrix and the spatial weight matrix to obtain the weighted deviation matrix as the spatial distribution feature of the interference.

[0112] In this embodiment, the spatial weight matrix refers to a two-dimensional proportional coefficient array that is pre-set for different types of interference to adjust the influence of the deviation values ​​of each touch node. It is used to represent the distribution of weights allocated to each spatial position in the touch area under a specific interference mode. For example, under signal superposition interference in the central area, the values ​​of the elements at the center position are larger and the values ​​of the elements at the edge position are smaller.

[0113] Specifically, the pre-determined interference type is obtained, and a search is performed in a pre-stored database of the correspondence between interference type and weight matrix to extract the spatial weight matrix corresponding to the current interference type, thus matching the corresponding spatial weight matrix according to the interference type. The two-dimensional deviation matrix constructed in the previous steps is obtained. Each element in the two-dimensional deviation matrix is ​​used as the multiplicand, and the elements in the same row and column of the spatial weight matrix are used as the multipliers. A term-by-term multiplication operation is performed on the elements in the same position. All the product values ​​obtained after the term-by-term multiplication operation are rearranged and combined according to their original row and column coordinates to generate a new matrix structure. The two-dimensional deviation matrix and the spatial weight matrix are then weighted to obtain the weighted deviation matrix. The overall data structure of this weighted deviation matrix is ​​extracted, and the weighted deviation matrix is ​​used as the spatial distribution feature of the interference for subsequent processing.

[0114] Step 204: Extract the weighted deviation value of the signal matching difference in the spatial distribution features of the interference, screen out the target touch nodes whose weighted deviation value exceeds the preset signal deviation threshold, and identify the connected regions containing the target touch nodes as key interference regions.

[0115] In the embodiments of this application, the key interference area refers to a specific physical block on the touch panel that is most severely affected by external noise and exhibits a continuous and patchy distribution characteristic. It is used to represent an abnormal response set area composed of multiple target touch nodes whose weighted deviation values ​​exceed the standard and are spatially adjacent to each other. For example, in the touch grid, it is an irregular polygonal interference range composed of five adjacent nodes with severely excessive deviations.

[0116] Specifically, from the acquired spatial distribution features of interference, the weighted deviation value of the signal matching difference corresponding to each touch node is extracted. A pre-set signal deviation threshold is obtained, and the weighted deviation value of each extracted touch node is compared with the pre-set signal deviation threshold. Among all touch nodes, nodes with weighted deviation values ​​greater than the pre-set signal deviation threshold are found and selected as target touch nodes. The two-dimensional spatial coordinates of the target touch nodes in the touch area are obtained. Based on the spatial adjacency relationship, physically adjacent target touch nodes are merged to form one or more continuous regions. The connected regions containing the target touch nodes are identified as key interference regions.

[0117] The following describes a partitioned reference distributed anti-interference projected capacitive touch system according to an embodiment of the present invention from the perspective of hardware processing. Please refer to [link to relevant documentation]. Figure 3 This is a schematic diagram of the structure of a partitioned reference distributed anti-interference projected capacitive touch system in an embodiment of this application.

[0118] It should be noted that, Figure 3 The structure of the partitioned reference distributed anti-interference projected capacitive touch system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0119] like Figure 3 As shown, a partitioned reference distributed anti-interference projected capacitive touch system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 302 or a program loaded from storage portion 308 into random access memory (RAM) 303, such as performing the methods in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0120] The following components are connected to I / O interface 305: input section 306 including audio input devices, push-button switches, etc.; output section 307 including a liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card, modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

Claims

1. A partitioned reference distributed anti-interference projected capacitive touch method, characterized in that, The method includes: Obtain the static capacitance reference value and background noise sample sequence of the touch area under static reference state, and divide the static capacitance reference value into reference values ​​corresponding to multiple regions according to the touch position. The regions include edge regions, center regions and transition regions. The frequency domain features of the background noise sample sequence are extracted to construct a target frequency band filter. The filter is used to filter the reference values ​​of each region. When the noise in the edge region exceeds the standard, the reference values ​​of the filtered edge region are pre-compensated and enhanced. Based on the reference values ​​of each region after filtering and enhancement, capacitance distribution characteristic parameters are calculated, and a distributed reference capacitance matrix that transitions continuously from the edge region to the center region is constructed according to the capacitance distribution characteristic parameters. The dynamic capacitive sensing value of the touch area under dynamic sensing state is obtained, and the signal matching deviation value and response difference ratio of each area are calculated by combining the distributed reference capacitance matrix with the dynamic capacitive sensing value. Based on the response difference ratio, the type of interference is identified, and based on the signal matching deviation value, the interference region is identified. The deviation correction coefficients for each region are calculated based on the interference type and the interference region. The dynamic capacitive sensing value is compensated using the deviation correction coefficients. When the compensated touch area reaches a preset global equilibrium state, the deviation correction coefficients are locked as touch consistency configuration parameters.

2. The partitioned reference distributed anti-interference projected capacitive touch method according to claim 1, characterized in that, The process involves acquiring the static capacitance reference value and background noise sample sequence of the touch area under a static reference state, and dividing the static capacitance reference value into multiple reference values ​​corresponding to different touch positions. These regions include edge regions, center regions, and transition regions. In a static reference state without touch input, the initial capacitance value of each touch node in the touch area is obtained as the static capacitance reference value. Under the static reference state, a sequence containing capacitance value fluctuation data is continuously collected as the background noise sample sequence; Calculate the shortest distance from each touch node to the boundary of the touch area and the distance to the geometric center; Based on the shortest distance and the distance to the geometric center, a distance boundary threshold is determined according to a preset ratio, and the static capacitance reference value is divided into a reference value for the edge region, a reference value for the center region, and a reference value for the transition region according to the distance boundary threshold.

3. The partitioned reference distributed anti-interference projected capacitive touch method according to claim 1, characterized in that, The step of extracting the frequency domain features of the background noise sample sequence to construct a target frequency band filter, using the filter to filter the reference values ​​of each region, and pre-compensating and enhancing the reference values ​​of the filtered edge regions when the noise in the edge regions exceeds the standard includes: The background noise sample sequence is decomposed in the frequency domain to extract the dominant noise frequency and noise energy density distribution as the frequency domain features; Based on the frequency domain characteristics, the filter stopband range is determined, and a target frequency band filter corresponding to the filter stopband range is constructed. The target frequency band filter is used to filter the reference values ​​of the edge region, the center region, and the transition region respectively. The noise intensity index of the edge region is calculated. When the noise intensity index is greater than the preset edge noise threshold, the noise of the edge region is determined to be excessive. The reference value of the filtered edge region is then amplified and enhanced using a noise pre-compensation enhancement coefficient.

4. The partitioned reference distributed anti-interference projected capacitive touch method according to claim 1, characterized in that, Based on the reference values ​​of each region after filtering and enhancement, capacitance distribution characteristic parameters are calculated, and a distributed reference capacitance matrix that continuously transitions from the edge region to the center region is constructed according to the capacitance distribution characteristic parameters, including: Calculate the mean capacitance and standard deviation of the reference values ​​of the edge region and the center region after filtering and enhancement, and use the mean capacitance and standard deviation of the capacitance as capacitance distribution characteristic parameters; Based on the first distance from the touch node in the transition area to the nearest edge touch node and the second distance to the center point, the position weight coefficient is calculated; By combining the position weighting coefficient and the capacitance distribution characteristic parameters, the reference capacitance value of the touch node in the transition area is calculated; The average capacitance values ​​of the edge region and the center region, as well as the reference capacitance value of the transition region, are mapped according to the spatial location of the touch node to construct the distributed reference capacitance matrix.

5. The partitioned reference distributed anti-interference projected capacitive touch method according to claim 4, characterized in that, The step of acquiring the dynamic capacitance sensing value of the touch area under dynamic sensing state, and combining the distributed reference capacitance matrix with the dynamic capacitance sensing value to calculate the signal matching deviation value and response difference ratio of each area includes: In a dynamic sensing state with touch input, the dynamic capacitance sensing value of the touch node in the touch area is obtained; The difference between the dynamic capacitance sensing value and the reference value of the corresponding node in the distributed reference capacitance matrix is ​​calculated to obtain the actual capacitance change of each region. Calculate the mean response of the edge region and the mean response of the center region under dynamic sensing conditions, and calculate the ratio of the mean response of the edge region to the mean response of the center region to obtain the response difference ratio. The signal matching deviation value is obtained by calculating the absolute deviation between the actual capacitance change in the transition region and the expected response corresponding to the distributed reference capacitance matrix.

6. The partitioned reference distributed anti-interference projected capacitive touch method according to claim 1, characterized in that, The process of identifying the interference type based on the response difference ratio and identifying key interference regions based on the signal matching deviation value includes: Obtain the initial difference ratio between the edge region and the center region under static baseline conditions; Calculate the deviation of the response difference ratio from the initial difference ratio; When the deviation of the difference ratio is greater than the preset deviation judgment threshold, if the response difference ratio is less than the initial difference ratio, the interference type is determined to be central region signal superposition interference; if the response difference ratio is greater than or equal to the initial difference ratio, the interference type is determined to be edge region signal attenuation interference. Based on the interference type and the signal matching deviation value, the spatial distribution characteristics of the interference are obtained using a spatial distribution characterization method. The weighted deviation value of the signal matching difference in the spatial distribution characteristics of the interference is extracted, the target touch nodes whose weighted deviation value exceeds the preset signal deviation threshold are screened out, and the connected regions containing the target touch nodes are identified as the key interference regions.

7. The partitioned reference distributed anti-interference projected capacitive touch method according to claim 6, characterized in that, The step of extracting spatial distribution features of interference based on the interference type and the signal matching deviation value using a spatial distribution characterization method includes: The signal matching deviation values ​​of the touch nodes in each of the aforementioned regions are mapped into a two-dimensional deviation matrix according to the spatial coordinates of the touch nodes; Based on the spatial weight matrix corresponding to the interference type, the two-dimensional deviation matrix and the spatial weight matrix are weighted and calculated to obtain a weighted deviation matrix as the spatial distribution feature of the interference.

8. The partitioned reference distributed anti-interference projected capacitive touch method according to claim 1, characterized in that, The step of calculating the deviation correction coefficient for each region based on the interference type and the interference region includes: When the interference type is a signal superposition interference in the central region, the ratio of the expected capacitance change to the actual capacitance change in the central region is calculated as a deviation correction coefficient used to suppress excessive response in the central region. When the interference type is edge region signal attenuation type interference, the ratio of the expected capacitance change to the actual capacitance change in the edge region is calculated as a deviation correction coefficient to enhance the insufficient response in the edge region. The maximum deviation within the interference area is extracted as a global deviation correction strength index; Based on the noise intensity index of the edge region, a corresponding dynamic threshold is matched in the database. When the global deviation correction intensity index is greater than the dynamic threshold, it is determined that the actual capacitance change needs to be scaled and adjusted proportionally, and a corresponding scaling factor is generated as the deviation correction factor for the transition region.

9. The partitioned reference distributed anti-interference projected capacitive touch method according to claim 6, characterized in that, Once the compensated touch area reaches a preset global equilibrium state, the deviation correction coefficient is locked as a touch consistency configuration parameter, including: The response difference ratio is recalculated based on the actual capacitance change after compensation, and the balance evaluation index between the recalculated response difference ratio and the initial difference ratio is calculated. The percentage of unbalanced nodes with excessive deviations after compensation processing within the transition area is statistically analyzed. When both the balance evaluation index and the proportion of unbalanced nodes are lower than the preset balance judgment threshold, the compensated touch area is determined to have reached the preset global balance state. When the preset global equilibrium state is reached, the deviation correction coefficient of each region is locked as the touch consistency configuration parameter.

10. A partitioned reference distributed anti-interference projected capacitive touch system, characterized in that, The partitioned reference distributed anti-interference projected capacitive touch system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the partitioned reference distributed anti-interference projected capacitive touch system to perform the method as described in any one of claims 1-9.

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