Touch chip and electronic device

Abstract

The embodiment of the present application provides a touch chip and an electronic device, the touch chip comprises at least one analog front-end processing unit, each analog front-end processing unit comprises: an encoding module, configured to perform linear encoding on detection signals from a plurality of sensing electrodes based on a preset encoding matrix, to generate a plurality of encoded detection signals of the plurality of sensing electrodes; a plurality of analog front-end circuits, respectively configured to process the plurality of encoded detection signals of the plurality of sensing electrodes, to generate a plurality of encoded digital signals of the plurality of sensing electrodes; and a decoding module, configured to perform linear decoding on the encoded digital signals of the plurality of sensing electrodes based on a preset decoding matrix, to generate a digital detection signal of each sensing electrode in the plurality of sensing electrodes; wherein the product of the preset encoding matrix and the preset decoding matrix is a unit matrix, and the maximum value of diagonal elements in the covariance matrix of the preset decoding matrix is less than 1.

Description

Technical Field

[0001] This application relates to the field of touch screens, and more particularly to a touch chip and an electronic device. Background Technology

[0002] Today, an increasing number of electronic devices offer touch interfaces. In solutions using touch panels to provide these interfaces, the touch panel senses touch events to generate touch detection signals. The analog front-end circuitry of the touch chip samples and quantizes these signals, processing them into digital detection signals so that a digital signal processor (DSP) can perform subsequent processing based on them. Random noise, also known as the noise floor of the analog front-end circuitry, is introduced during the processing of the touch detection signals in the analog front-end circuitry, leading to a decrease in the signal-to-noise ratio of the touch detection. Summary of the Invention

[0003] In view of this, one of the technical problems solved by the embodiments of this application is to provide a touch chip and electronic device for reducing the background noise of analog front-end circuit and improving the signal-to-noise ratio of touch detection.

[0004] In a first aspect, a touch chip is provided, including at least one analog front-end processing unit, each analog front-end processing unit corresponding to multiple sensing electrodes of a touch panel, and each analog front-end processing unit including: an encoding module, multiple analog front-end circuits corresponding to the multiple sensing electrodes, and a decoding module.

[0005] The encoding module is used to linearly encode the detection signals from the plurality of sensing electrodes based on a preset encoding matrix to generate a plurality of coded detection signals from the plurality of sensing electrodes.

[0006] The plurality of analog front-end circuits are respectively used to process the plurality of coded detection signals of the plurality of sensing electrodes to generate the plurality of coded digital signals of the plurality of sensing electrodes.

[0007] The decoding module is used to linearly decode the encoded digital signals of the plurality of sensing electrodes based on a preset decoding matrix to generate a digital detection signal for each of the plurality of sensing electrodes.

[0008] Wherein, the product of the preset encoding matrix and the preset decoding matrix is ​​an identity matrix, and the maximum value of the diagonal elements in the covariance matrix of the preset decoding matrix is ​​less than 1.

[0009] Based on the above technical solution, since the product of the preset encoding matrix used during encoding and the preset decoding matrix used during decoding is an identity matrix, the detection signals of multiple sensing electrodes can be completely restored during decoding. Furthermore, when processing the encoded detection signals of the sensing electrodes using analog front-end circuits, random noise (also known as the noise floor of the analog front-end circuit) is introduced. This random noise typically follows a Gaussian distribution; therefore, the random noise introduced by multiple analog front-end circuits constitutes a Gaussian random vector. After linear decoding of the encoded digital signal using the preset decoding matrix, the Gaussian random vector becomes the vector obtained by multiplying the preset decoding matrix by the Gaussian random vector. Since the maximum value of the diagonal elements in the covariance matrix of the preset decoding matrix is ​​less than 1, the standard deviation of each element in the vector obtained by multiplying the preset decoding matrix by the Gaussian random vector is smaller than the standard deviation of each element in the Gaussian random vector, thus reducing the standard deviation of the noise floor of the analog front-end circuit. This improves the signal-to-noise ratio. With the signal change caused by pressing remaining constant, the smaller the standard deviation of AFE noise, the larger the SNR. Therefore, this solution improves the signal-to-noise ratio of touch detection.

[0010] In a second aspect, an electronic device is provided, comprising: a touch panel; and a touch chip according to claim 1. Attached Figure Description

[0011] The following sections will describe some specific embodiments of the present application in a detailed manner by way of example and not limitation, with reference to the accompanying drawings. The same reference numerals in the drawings denote the same or similar parts or components. Those skilled in the art should understand that these drawings are not necessarily drawn to scale. In the drawings:

[0012] Figure 1 This provides an architecture for an analog front-end circuit in related technologies;

[0013] Figure 2 This provides an architecture for an analog front-end circuit in related technologies;

[0014] Figure 3 This provides an architecture for an analog front-end circuit in related technologies;

[0015] Figure 4 Provided for the embodiments of this application Figures 1 to 3 The data format obtained from the provided analog front-end circuit architecture;

[0016] Figure 5 This is a schematic diagram of the structure of a touch chip provided in an embodiment of this application;

[0017] Figure 6 This is a schematic diagram of the structure of a touch chip provided in an embodiment of this application. Detailed Implementation

[0018] To enable those skilled in the art to better understand the technical solutions in the embodiments of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art should fall within the protection scope of the embodiments of this application.

[0019] More and more electronic devices now use touchscreens. A touchscreen can include a touch panel and a display panel, with the display panel typically located above the touch panel. The touch panel can be a self-capacitance touch panel or a mutual-capacitance touch panel. A self-capacitance touch panel typically includes detection electrodes (RX electrodes) arranged in a specific pattern. During touch detection, a drive signal can be applied to the detection electrodes (RX electrodes) of the touch panel, and a touch detection signal corresponding to the drive signal is acquired from the same detection electrode. This touch detection signal changes with the touch or proximity of an object such as a finger or pen, thereby allowing the detection of touch coordinates and the presence / absence of a touch based on the changes in the touch detection signal. A mutual-capacitance touch panel typically includes multiple drive electrodes (TX electrodes) arranged along a first direction and multiple sensing electrodes (RX electrodes) arranged along a second direction perpendicular to the first direction. During touch detection, a drive signal can be applied to the TX electrodes in the touch panel, and a touch detection signal corresponding to the drive signal is acquired through the RX electrodes intersecting the TX electrodes. This touch detection signal changes with the touch or proximity of an object such as a finger or pen, thereby allowing the detection of touch coordinates and the presence / absence of a touch based on the changes in the touch detection signal.

[0020] For both self-capacitance and mutual-capacitance touch panels, the operation of acquiring touch detection signals is typically performed by the analog front-end (AFE) circuitry of the touch chip. For example, ... Figure 1 As shown, each RX electrode is configured with an AFE circuit, also known as an AFE channel. For example, there are n RX electrodes RX0 to RX10. n-1 Accordingly, configure n AFE channels CH0 to CH n-1Each AFE channel contains a Programmable Gain Amplifier (PGA), an Anti-aliasing Filter (AAF), and an Analog-Digital Converter (ADC). The PGA is used for signal extraction and amplification of the analog detection signal output from the RX electrode. The AAF is used for filtering the amplified signal, and the ADC is used for analog-to-digital conversion of the filtered signal to obtain the digital detection signal corresponding to the analog detection signal. It should be understood that... Figure 1 Only the architecture of the analog front-end circuit is shown. In actual circuit implementation, the components in the analog front-end circuit also need to be configured with corresponding reference voltages, power supply voltages, etc. For example, in addition to the input terminal connected to the RX electrode to receive the analog detection signal output by the RX electrode, the PGA also includes another input terminal for receiving the reference voltage.

[0021] Each AFE channel performs sampling and quantization operations on the touch detection signal output by the corresponding single RX electrode. For example, AFE channel CH0 samples the touch detection signal output by electrode RX0, AFE channel CH1 samples the touch detection signal output by electrode RX1, and so on. n-1 The touch detection signal output from electrode RXn-1 is sampled. That is, for the i-th AFE channel CH i (i is an integer less than n-1), the collected signal is: CH i =RX i . Figure 1 The architecture shown, which samples the touch detection signal output from only a single RX electrode, is also known as a single-ended architecture. The data obtained by the single-ended architecture is as follows: Figure 4 (a) in the middle. Figure 1 In the AFE architecture, each AFE channel processes the touch detection signal into a digital detection signal, enabling the digital signal processor to perform subsequent processing based on the digital detection signal. However, the AFE channel introduces random noise (also known as the AFE noise floor) during the processing of the touch detection signal, resulting in a decrease in the signal-to-noise ratio of touch detection.

[0022] Furthermore, the touch detection signal output from the RX electrode typically contains a large fixed component, also known as the base signal. Additionally, the touch detection signal output from the RX electrode is usually affected by display noise, which is largely common-mode noise. The presence of these two components limits the gain of the AFE circuit from being set too high, otherwise there is a risk of saturation distortion. To allow for a higher gain in the AFE circuit, related technologies employ differential methods on the touch detection signals output from adjacent RX electrodes or by subtracting the average of all touch detection signals output from the RX electrodes to eliminate these two components. This amplifies the noise floor of the AFE, resulting in a lower signal-to-noise ratio for touch detection.

[0023] For example, refer to Figure 2 The AFE architecture shown eliminates the aforementioned base signal and display noise by differentially processing the touch detection signals output from adjacent RX electrodes. For example, AFE channel CH0 samples the difference between the touch detection signal output from the corresponding electrode RX0 and the touch detection signal from electrode RX1 (indicated by the arrow); AFE channel CH1 samples the difference between the touch detection signal output from the corresponding electrode RX1 and the touch detection signal from electrode RX2 (indicated by the arrow); and so on, with AFE channel CHn-2 sampling the difference between the touch detection signal output from the corresponding electrode RXn-2 and the touch detection signal from electrode RXn-1 (indicated by the arrow). That is, for the i-th AFE channel CH... i (i is an integer less than n-1), the collected signal is:

[0024] CH i =RX i –RX i+1 ;

[0025] exist Figure 2 In the architecture shown, the signal input to the i-th AFE channel is RX. i The touch detection signal of the electrode and RX i+1 The differential signal between the touch detection signals of the electrodes. The data obtained by this architecture is as follows: Figure 4 As shown in (b). Due to Figure 4 The data format shown in (b) is relative to Figure 4 The data format shown in (a) lacks offset information, which may lead to incorrect calculation of some touch position coordinates in subsequent touch position coordinate calculations. Therefore, at a certain stage of subsequent data processing, it is necessary to acquire the single-ended signal of the corresponding RX electrode from one of the AFE channels CH0 to CHn-1, and based on the single-ended signal of this RX electrode, the... Figure 4The differential signal shown in (b) is restored to a single-ended signal. To avoid saturation distortion of the AFE channel (hereinafter referred to as the single-ended channel) that acquires the single-ended signal from the RX electrode, the gain of the AFE channel will be less than [value missing]. Figure 2 The gain of the AFE channel (hereinafter referred to as the differential channel) that acquires the differential signal, for example, its magnitude is usually related to... Figure 1 The AFE channel gains are the same in the single-ended architecture shown. In the process of restoring the differential signal to a single-ended signal, it is necessary to ensure that the signal gains of the differential channel and the single-ended channel are consistent. Therefore, the data acquired by the single-ended channel needs to be amplified by a factor of K, where K = differential channel gain / single-ended channel gain. This means that the AFE noise floor of the single-ended channel is also amplified by a factor of K. Figure 2 In the architecture shown, restoring the differential signal acquired by the differential channel to a single-ended signal is essentially adding the data acquired by the single-ended channel back to the differential channel. This is done via the AFE channel CH. n-1 RX acquisition n-1 The single-ended signal of the electrode (i.e., the AFE channel CH) n-1 Taking the example of using it as a single-ended channel, in order to make the AFE channel CH n-2 To convert the acquired differential signal back to a single-ended signal, the AFE channel CH needs to be... n-1 Collected R n-1 The single-ended signal from the electrode is amplified by a factor of K and then compared with the AFE channel CH. n-2 The acquired differential signals are added together to obtain the AFE channel CH. n-2 The single-ended signal. Because the AFE channel CH... n-1 Collected R n-1 The single-ended signal of the electrode is amplified by K times, which means that the AFE channel CH n-1 The noise floor is also amplified by a factor of K. Therefore, the restored AFE channel CH n-2 The single-ended signal includes the AFE channel CH. n-2 The noise floor also includes the AFE channel CH, which is amplified by a factor of K. n-1 The background noise. And Figure 1 Compared to the single-end architecture shown, Figure 2 The noise level in the final reconstructed data from the differential channel in the differential architecture shown will be higher than that in the differential architecture. Figure 1 The noise level in the single-ended channel data of the single-ended architecture shown is more than K times greater, however, Figure 2 In the differential architecture shown, the effective signal in the data ultimately recovered from the differential channel is relative to... Figure 1 In the single-ended architecture shown, the effective signal of the single-ended channel is only amplified by a factor of K. Therefore, in subsequent processing stages, without additional methods (such as fitting) to... Figure 2 The noise in the restored data in the differential architecture shown is processed. Figure 2The signal-to-noise ratio (SNR) under the differential architecture shown is... Figure 1 The single-end architecture shown is even lower.

[0026] For example, refer to Figure 3 The AFE architecture shown eliminates the aforementioned base signal and display noise by subtracting the average of the touch detection signals output from all RX electrodes. For example, AFE channel CH0 samples the difference between the touch detection signal output from the corresponding electrode RX0 and the average of the touch detection signals from all RX electrodes (indicated by the arrow). AFE channel CH1 samples the difference between the touch detection signal output from the corresponding electrode RX1 and the average of the touch detection signals from all RX electrodes (indicated by the arrow), and so on. AFE channel CHn-1 samples the difference between the touch detection signal output from the corresponding electrode RXn-1 and the average of the touch detection signals from all RX electrodes (indicated by the arrow). That is, for the i-th AFE channel CH... i (i is an integer less than n-1), the collected signal is:

[0027]

[0028] In this architecture, the signal input to the i-th AFE channel is RX. i The differential signal is obtained by subtracting the average of the touch detection signals from all RX electrodes from the touch detection signal of the first electrode. The data obtained from this architecture is in the form of... Figure 4 As shown in (c). Because Figure 4 The data format shown in (c) is relative to Figure 4 The data format shown in (a) lacks offset information, which may lead to incorrect calculation of some touch position coordinates in subsequent touch position coordinate calculations. Therefore, at some stage of subsequent data processing, it is necessary to use an AFE channel CH... n The average value of the touch detection signals from all RX electrodes is acquired to channel AFE from CH0 to CH0. n-1 The acquired differential signal is restored to a single-ended signal. To avoid acquiring the average value of touch detection signals from all RX electrodes, the AFE channel CH... n (It is a single-ended channel) saturation distortion, AFE channel CH n The gain will be less than Figure 3 The AFE channel (hereinafter referred to as the differential channel) that acquires the difference signal in the middle is usually the same as the size of the AFE channel (hereinafter referred to as the differential channel). Figure 1 The AFE channel gain is the same in the single-ended architecture shown. During the process of restoring the differential signal to a single-ended signal, it is necessary to ensure that the differential channel and the AFE channel (which is used as a single-ended channel) have the same gain. nThe signal gain is consistent, therefore the AFE channel CH needs to be adjusted. n The acquired data is amplified by a factor of K, where K = differential channel gain / AFE channel CH. n The gain, which means the AFE channel CH n The AFE noise floor was also amplified by a factor of K. Figure 3 In the architecture shown, restoring the differential signal acquired by the differential channel to a single-ended signal is essentially the same as converting the AFE channel CH... n The acquired data is added back to the differential channel data. Taking the restoration of the differential signal acquired by AFE channel CH0 to a single-ended signal as an example, it is necessary to add the data from AFE channel CH0 back to the differential channel. n The average value of the touch detection signals from all the RX electrodes is amplified by a factor of K and then added to the differential signal acquired by the AFE channel CH0 to obtain the single-ended signal of the AFE channel CH0. Since the average value of the touch detection signals from all the RX electrodes acquired by the AFE channel CH0 is amplified by a factor of K, this means that the noise floor of the AFE channel CH0 is also amplified by a factor of K. Therefore, the reconstructed single-ended signal of the AFE channel CH0 contains both the noise floor of the AFE channel CH0 and the amplified (by a factor of K) AFE channel CH0 signal. n The background noise. And Figure 1 Compared to the single-end architecture shown, Figure 3 In the architecture shown, the noise level in the data ultimately reconstructed by the differential channel will be higher than... Figure 1 The noise level in the single-ended channel data of the single-ended architecture shown is more than K times greater, however, Figure 2 In the differential architecture shown, the effective signal in the data ultimately recovered from the differential channel is relative to... Figure 1 In the single-ended architecture shown, the effective signal of the single-ended channel is only amplified by a factor of K. Therefore, in subsequent processing stages, without additional methods (such as fitting) to... Figure 3 The noise in the restored data in the architecture shown is processed. Figure 3 The signal-to-noise ratio (SNR) under the architecture shown is also higher than... Figure 1 The single-end architecture shown is even lower.

[0029] In fact, Figure 2 and Figure 3 In the architecture shown, the method of differentially processing the touch detection signal from the RX electrode and inputting it to the corresponding AFE channel can be considered a special linear encoding method. The method of subsequently restoring the differential signal output from the AFE channel to a single-ended signal can be considered a special linear decoding method. However, since the encoding matrices used in these two linear encoding methods are designed to eliminate both the fundamental signal and display noise components in the touch detection signal to facilitate a larger AFE gain, they are not suitable for suppressing noise in the AFE channel.

[0030] To address this, this application provides a touch chip that suppresses the background noise of the analog front-end circuit and improves the signal-to-noise ratio of touch detection by setting appropriate preset encoding matrices and preset decoding matrices in the encoding module and decoding module, respectively.

[0031] The following is combined Figure 5 and Figure 6 The touch chip provided in the embodiments of this application will be described in detail. For example... Figure 5 As shown, the touch chip 10 provided in this embodiment includes at least one analog front-end processing unit 100. Each analog front-end processing unit 100 corresponds to a set of sensing electrodes on the touch panel, the set of sensing electrodes including multiple sensing electrodes RX_0 to RX_n-1. Each analog front-end processing unit 100 includes: an encoding module 110, multiple analog front-end circuits 120_0 to 120_n-1 corresponding to the multiple sensing electrodes RX_0 to RX_n-1 in the touch panel, and a decoding module 130.

[0032] The encoding module 110 is used to linearly encode the detection signals from multiple sensing electrodes RX_0 to RX_n-1 based on a preset encoding matrix, and generate multiple encoded detection signals from multiple sensing electrodes.

[0033] Multiple analog front-end circuits 120_0 to 120_n-1 are used to process the encoded detection signals of multiple sensing electrodes RX_0 to RX_n-1 respectively, and generate multiple encoded digital signals of multiple sensing electrodes.

[0034] The decoding module 130 is used to linearly decode the encoded digital signals of multiple sensing electrodes based on a preset decoding matrix to generate a digital detection signal for each of the multiple sensing electrodes.

[0035] The product of the preset encoding matrix and the preset decoding matrix is ​​an identity matrix, and the maximum value of the diagonal elements in the covariance matrix of the preset decoding matrix is ​​less than 1.

[0036] In this embodiment, the detection signals of the multiple sensing electrodes RX_0 to RX_n-1 are analog signals obtained from the multiple sensing electrodes RX_0 to RX_n-1. For ease of subsequent description of the encoding process, the detection signals of the multiple sensing electrodes RX_0 to RX_n-1 can be mathematically represented as a signal vector Xn, for example: x0, x1, ..., x n-1 These represent the detection signals of the n sensing electrodes RX_0 to RX_n-1, respectively.

[0037] The number of columns in the preset encoding matrix used by encoding module 110 depends on the number of multiple sensing electrodes RX_0 to RX_n-1 corresponding to encoding module 110. Specifically, the number of columns in the encoding matrix is ​​equal to the dimension of the signal vector Xn. The number of rows in the preset encoding matrix 110 can be greater than or equal to the number of columns in the preset encoding matrix 110 to ensure that the preset encoding matrix 110 has an inverse matrix. For ease of explanation, the following description uses the example where the number of rows in the preset encoding matrix 110 is equal to its number of columns. The described preset encoding matrix can be represented as an n×n preset encoding matrix Dn, for example: The elements in each row of the preset encoding matrix, for example, d 0，0 d 0，1 、....、d 0，n-1 , where is the weight to be applied to the detection signals of the n sensing electrodes RX_0 to RX_n-1 when performing linear encoding on the detection signals of the n sensing electrodes RX_0 to RX_n-1 respectively.

[0038] Therefore, each of the n encoded detection signals of n sensing electrodes RX_0 to RX_n-1 obtained by linearly encoding the detection signals from multiple sensing electrodes RX_0 to RX_n-1 based on a preset encoding matrix is ​​a linear weighted sum of the detection signals of the n sensing electrodes RX_0 to RX_n-1. Specifically, the encoded detection signals of the n sensing electrodes RX_0 to RX_n-1 are represented by a signal vector Yn in mathematical form. Signal vector Yn = Dn·Xn.

[0039] y0, y2, ..., y n-1 These represent the coded detection signals of the n sensing electrodes RX_0 to RX_n-1, respectively.

[0040] The number of analog front-end circuits 120_0 to 120_n-1 corresponds to the number of sensing electrodes RX_0 to RX_n-1. Therefore, n analog front-end circuits 120_0 to 120_n-1 are connected to the output of the encoding module 110 to receive the encoded detection signals of n sensing electrodes RX_0 to RX_n-1, and to sample and quantize the encoded detection signals of n sensing electrodes RX_0 to RX_n-1 to generate encoded digital signals of n sensing electrodes RX_0 to RX_n-1.

[0041] In one implementation, each analog front-end circuit includes a gain amplifier and an analog-to-digital converter. The gain amplifier is connected to the output of the encoding module and is used to amplify the encoded detection signal output by the encoding module. The analog-to-digital converter is used to convert the amplified encoded detection signal into an analog signal to generate the corresponding encoded digital signal.

[0042] In another implementation, each analog front-end circuit also includes an anti-aliasing filter connected between the output of the gain amplifier and the input of the analog-to-digital converter (ADC) to filter the amplified coded detection signal. Correspondingly, the ADC performs analog-to-digital conversion on the filtered coded detection signal to generate the corresponding coded digital signal.

[0043] In this embodiment, the coded digital signals of the n sensing electrodes RX_0 to RX_n-1 can be represented by a mathematical signal vector Yn1, for example: These represent the coded digital signals generated by n analog front-end circuits from 120_0 to 120_n-1, respectively.

[0044] Since the analog front-end circuits 120_0 to 120_n-1 introduce noise when processing the encoded detection signal, the encoded digital signal contains the noise introduced by the corresponding analog front-end circuits, also known as the noise floor of the analog front-end circuits. The noise introduced by the analog front-end circuits is usually thermal noise, conforming to a Gaussian distribution, and the noise introduced by different analog front-end circuits 120_0 to 120_n-1 is independent of each other. The noise floor of the n analog front-end circuits 120_0 to 120_n-1 can be represented mathematically as a noise vector Nn, for example: n1, n1, ..., n n-1 These represent the noise floor of n analog front-end circuits from 120_0 to 120_n-1, respectively.

[0045] Furthermore, since the coded digital signal obtained by the analog front-end circuits 120_0 to 120_n-1 after processing the coded detection signal is used to indicate the magnitude of the coded detection signal when the analog front-end circuits 120_0 to 120_n-1 do not cause noise, for ease of analysis, it is assumed that the coded digital signal obtained by the analog front-end circuits 120_0 to 120_n-1 after processing the coded detection signal is still represented by the signal vector Yn. Therefore, when the analog front-end circuits 120_0 to 120_n-1 cause noise, the signal vector containing noise Yn1 = Yn + Nn, which can be expressed as...

[0046]

[0047] Decoding module 130 is connected to n analog front-end circuits 120_0 to 120_n-1 to decode the encoded digital signals output by the n analog front-end circuits 120_0 to 120_n-1 based on a preset decoding matrix, thereby generating digital detection signals for n sensing electrodes RX_0 to RX_n-1. The preset decoding matrix Rn and the preset encoding matrix Dn satisfy: Rn·Dn=I, where I is the identity matrix. That is, the preset decoding matrix Rn is the inverse of the preset encoding matrix. Specifically, when the number of rows in the preset encoding matrix is ​​greater than the number of columns, the preset decoding matrix is ​​the left inverse of the preset encoding matrix. The preset decoding matrix can be represented as...

[0048] The elements in each row of the preset decoding matrix, for example r 0，0 r 0，1 ... r 0，n-1 , which is the weight to be applied to the encoded digital signals of the n sensing electrodes RX_0 to RX_n-1 when performing linear decoding on the encoded digital signals of the n sensing electrodes RX_0 to RX_n-1.

[0049] Each of the n digital detection signals obtained by linearly decoding the coded digital signals of the n sensing electrodes RX_0 to RX_n-1 based on a preset decoding matrix Rn is a linear weighted sum of the coded digital signals of the n sensing electrodes RX_0 to RX_n-1. The coded digital signals of the n sensing electrodes RX_0 to RX_n-1 are represented by a signal vector Zn in mathematical form, Zn = Rn·Yn1. Specifically,

[0050] z0, z1, ..., z n-1 These represent n digital detection signals.

[0051] As described above, signal vector Yn1 = signal vector Yn + noise vector Nn, signal vector Yn = Dn·Xn, therefore, signal vector Zn = Rn·Yn1 = Rn·(Yn+Nn) = Rn·Dn·Xn + Rn·Nn.

[0052] Since the product of the preset decoding matrix and the preset encoding matrix equals the identity matrix, i.e., Rn·Dn=I, the signal vector Zn=Xn+Rn·Nn. According to the above derivation, the signal part remains unchanged before and after encoding and decoding, but the noise introduced by the front-end analog circuit changes from noise vector Nn to noise vector Rn·Nn. Since the diagonal elements of the covariance matrix of an n-dimensional random variable represent the variance of the i-th element in that random variable, for the noise vector Rn·Nn, its covariance matrix is ​​Rn·Nn·(Rn·Nn). TThe diagonal elements represent the variance of the i-th element in the noise vector Rn·Nn. As mentioned above, the noise introduced by the analog front-end circuit is usually thermal noise, which follows a Gaussian distribution, specifically a normal distribution with a mean of 0 and a standard deviation of σ. Therefore, for the noise vector Nn introduced by the analog front-end circuit, Nn·Nn T＝ σ 2 Correspondingly, the covariance matrix of the noise vector Rn·Nn is Rn·Nn·(Rn·Nn). T =Rn·Nn·Nn T ·Rn T =Rn·Rn T ·σ 2 Because the covariance matrix of the preset decoding matrix Rn is Rn·Rn T Since all diagonal elements are less than 1, the variance of each element in the vector Rn·Nn obtained by multiplying the preset decoding matrix Rn by the noise vector Nn is less than the variance σ of the corresponding element in the noise vector Nn. 2 Correspondingly, the standard deviation of each element in the vector Rn·Nn obtained by multiplying the preset decoding matrix Rn by the noise vector Nn is smaller than the standard deviation of the corresponding element in the noise vector Nn. That is, compared to the standard deviation of the noise introduced by AFE, the standard deviation of the AFE noise in the decoded digital detection signal is reduced. Due to the signal-to-noise ratio... With a constant signal change caused by pressing, a smaller standard deviation of AFE noise results in a larger SNR; therefore, this scheme improves the signal-to-noise ratio of touch detection. (Using a preset encoding matrix...) For example, its preset decoding matrix Covariance matrix of the preset decoding matrix The standard deviation of the noise vector in the digital detection signal obtained after encoding and decoding using the aforementioned preset encoding and decoding matrices is: Compared to the standard deviation σ of the noise vector introduced by AFE, the standard deviation is only 0.707 of the original standard deviation, and correspondingly, the signal-to-noise ratio is improved by about 1.4 times.

[0053] In one implementation of this application, the encoding module is implemented using hardware circuitry.

[0054] In one implementation of this application, the decoding module can be implemented using hardware circuitry or software. For example, the decoding module can be implemented using a dedicated digital circuit module or using software implementation with a general-purpose processor.

[0055] In the embodiments of this application, the number of columns and rows of the encoding matrix used by the encoding module can be determined according to the number of sensing electrodes corresponding to the encoding module. The encoding matrix and decoding matrix that satisfy the following conditions can be found by traversal as the preset encoding matrix and preset decoding matrix. The conditions are: the product of the encoding matrix and the decoding matrix is ​​an identity matrix, and the maximum value of the diagonal elements in the covariance matrix of the decoding matrix is ​​less than 1.

[0056] The more sensing electrodes a coding module has, the more coding and decoding matrices that meet the above conditions can be used. In other words, a wider range of coding and decoding matrices are available. Selecting appropriate coding and decoding matrices from these for linear encoding and decoding can minimize the standard deviation of AFE noise in the final digital detection signal, thereby maximizing the signal-to-noise ratio. However, a larger number of sensing electrodes also leads to higher hardware overhead and more complex wiring when configuring the coding module.

[0057] To reduce hardware overhead and wiring complexity, in one embodiment of this application, such as Figure 6 As shown, the touch panel's sensing electrodes are divided into N groups, meaning the touch panel includes N groups of sensing electrodes, each group including at least three sensing electrodes. The touch chip includes N analog front-end processing units that correspond one-to-one with the N groups of sensing electrodes, where N is an integer greater than or equal to 2.

[0058] like Figure 6 As shown, the m sensing electrodes of the touch panel are divided into N groups of sensing electrodes, each group comprising n sensing electrodes, where n is an integer greater than or equal to 3. For example, the first group of sensing electrodes includes RX_0 to RX_n-1, and the nth group includes RX_m-n to RX_m-1. Correspondingly, the touch chip includes the first to the nth analog front-end processing units. The structure and working principle of each analog front-end processing unit are the same as those in the aforementioned embodiments, and will not be repeated here.

[0059] The larger the number of groups of sensing electrodes (N), the more analog front-end processing units (AFEs) the touch chip includes. Correspondingly, the fewer sensing electrodes corresponding to the preset encoding and decoding modules in each AFE, the lower the hardware overhead and wiring complexity of designing these modules. Conversely, the smaller the number of groups of sensing electrodes (N), the fewer AFEs the touch chip includes. Correspondingly, the more sensing electrodes corresponding to the preset encoding and decoding modules in each AFE, the more preset encoding and decoding matrices can be selected. Choosing appropriate preset encoding and decoding matrices for linear encoding and decoding from these matrices can minimize the standard deviation of AFE noise in the final digital detection signal, thereby maximizing the signal-to-noise ratio.

[0060] It should be understood that Figure 6 This is just one example. In practical applications, the number of sensing electrodes in any two different groups of N sensing electrodes can be different to accommodate situations where the sensing electrodes cannot be uniformly grouped.

[0061] This application also provides an electronic device, which includes a touch panel and the touch chip described in any of the above embodiments.

[0062] By way of example and not limitation, the electronic devices in the embodiments of this application may be portable or mobile computing devices such as terminal devices, mobile phones, tablets, laptops, desktop computers, gaming devices, in-vehicle electronic devices or wearable smart devices, as well as other electronic devices such as electronic databases, automobiles, and bank automated teller machines (ATMs).

[0063] The terminal devices in this application embodiment exist in various forms, including but not limited to:

[0064] (1) Mobile communication devices: These devices are characterized by their mobile communication capabilities and primarily aim to provide voice and data communication. These terminals include: smartphones (e.g., iPhones), multimedia phones, feature phones, and low-end phones, etc.

[0065] (2) Ultra-mobile personal computer devices: These devices fall under the category of personal computers, possessing computing and processing capabilities, and generally also have mobile internet access features. These terminals include PDAs, MIDs, and UMPCs, such as the iPad.

[0066] (3) Portable entertainment devices: These devices can display and play multimedia content. This category includes audio and video players (such as iPods), handheld game consoles, e-book readers, as well as smart toys and portable car navigation devices.

[0067] (4) Server: A device that provides computing services. The components of a server include a processor 810, hard disk, memory, system bus, etc. Servers are similar to general computer architectures, but because they need to provide highly reliable services, they have higher requirements in terms of processing power, stability, reliability, security, scalability, and manageability.

[0068] (5) Other electronic devices with data interaction functions.

[0069] Specific embodiments of the subject matter have now been described. Other embodiments are within the scope of the appended claims. In some cases, the actions described in the claims can be performed in a different order and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing can be advantageous.

[0070] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0071] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A touch chip, comprising at least one analog front-end processing unit, each analog front-end processing unit corresponding to a set of sensing electrodes of a touch panel, the set of sensing electrodes comprising a plurality of sensing electrodes, each analog front-end processing unit comprising: An encoding module, multiple analog front-end circuits corresponding to the multiple sensing electrodes, and a decoding module. The encoding module is used to linearly encode the detection signals from the plurality of sensing electrodes based on a preset encoding matrix to generate a plurality of coded detection signals from the plurality of sensing electrodes. The plurality of analog front-end circuits are respectively used to process the plurality of coded detection signals of the plurality of sensing electrodes to generate the plurality of coded digital signals of the plurality of sensing electrodes. The decoding module is used to linearly decode the encoded digital signals of the plurality of sensing electrodes based on a preset decoding matrix to generate a digital detection signal for each of the plurality of sensing electrodes. Wherein, the product of the preset encoding matrix and the preset decoding matrix is ​​an identity matrix, and the maximum value of the diagonal elements in the covariance matrix of the preset decoding matrix is ​​less than 1; the elements in each row of the preset encoding matrix are the weights to be applied to the detection signals of the plurality of sensing electrodes when linearly encoding the detection signals of the plurality of sensing electrodes, and each of the plurality of encoded detection signals is a linear weighted sum of the detection signals of the plurality of sensing electrodes; the elements in each row of the preset decoding matrix are the weights to be applied to the encoded digital signals of the plurality of sensing electrodes when linearly decoding the encoded digital signals of the plurality of sensing electrodes, and the digital detection signal of each of the plurality of sensing electrodes is a linear weighted sum of the encoded digital signals of the plurality of sensing electrodes.

2. The touch chip according to claim 1, wherein, The number of columns in the preset encoding matrix is ​​equal to the number of the plurality of sensing electrodes.

3. The touch chip according to claim 2, wherein, The number of rows in the preset encoding matrix is ​​greater than or equal to the number of columns in the preset encoding matrix.

4. The touch chip according to claim 1, wherein, The preset decoding matrix is ​​the left inverse of the preset encoding matrix.

5. The touch chip according to claim 1, wherein, The touch panel's sensing electrodes are divided into N groups, each group including at least three sensing electrodes. The touch chip includes N analog front-end processing units that correspond one-to-one with the N groups of sensing electrodes, where N is an integer greater than or equal to 2.

6. The touch chip according to claim 1, wherein, The preset encoding matrix is ​​implemented through hardware circuitry.

7. The touch chip according to claim 1, wherein, The preset decoding matrix is ​​implemented through hardware circuits or software modules.

8. The touch chip according to claim 1, wherein, Each of the analog front-end circuits includes a gain amplifier and an analog-to-digital converter. The gain amplifier is connected to the output of the encoding module and is used to amplify the encoded detection signal output by the encoding module. The analog-to-digital converter is used to perform analog-to-digital conversion on the amplified coded detection signal.

9. The touch chip according to claim 8, wherein, Each of the analog front-end circuits further includes an anti-aliasing filter connected between the output of the gain amplifier and the input of the analog-to-digital converter, for filtering the amplified coded detection signal.

10. An electronic device, comprising: Touch panel; as well as The touch chip according to any one of claims 1 to 9.

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