Proximity detection circuit and baseline correction method

Abstract

The present application provides a proximity detection circuit and a baseline correction method. The proximity detection circuit includes a detection circuit, a baseline processing circuit and a proximity sensing circuit. The detection circuit generates a detection data. The proximity sensing circuit generates a proximity signal according to a proximity threshold, the detection data and a baseline data generated by the baseline processing circuit. The baseline processing circuit determines to correct the baseline data by a first correction amount or a second correction amount according to a difference value between the detection data and the baseline data. The second correction amount is greater than the first correction amount. The baseline data is moderately corrected according to different situations, and the accuracy of the proximity sensing can be improved.

Description

Technical Field

[0001] This invention relates to a proximity sensor, and more particularly to a proximity detection circuit and baseline correction method for the proximity sensor, which can avoid misjudging proximity events. Background Technology

[0002] A proximity sensor is a sensor that detects whether a person or object is approaching an electronic device without requiring physical contact. Capacitive proximity sensors are currently widely used in electronic devices. These devices have a sensing electrode, which acts as a capacitor. The effective capacitance of the sensing electrode changes due to the presence or absence of a person or object. By sensing this effective capacitance, the proximity sensor can determine whether a person or object is approaching the electronic device, thus identifying a proximity event. The proximity sensor determines the presence of a proximity event based on the difference between the capacitance of the sensing electrode and a baseline.

[0003] However, environmental factors can affect the capacitance of the sensing electrodes, such as the temperature of the electronic device itself, ambient temperature, or humidity. Without baseline correction, proximity sensors may misjudge whether a proximity event has occurred. Therefore, a proximity sensing technique with baseline correction has been developed to improve the accuracy of proximity sensing.

[0004] However, existing technologies may mistakenly interpret the slow changes in capacitance of sensing electrodes caused by a person or object slowly approaching or moving away from an electronic device as changes in environmental factors. This leads to incorrect baseline compensation, making it impossible to accurately determine whether a proximity event or a moving-away event has occurred. For example, if existing technology determines that a proximity event has occurred, and then the object or person slowly moves away from the electronic device, causing a slow change in capacitance of the sensing electrodes (e.g., a slow decrease), the existing technology may mistakenly interpret this slow change in capacitance as caused by environmental factors, thus lowering the baseline. Therefore, even if the proximity event has ceased to exist (i.e., the person or object has moved away from the electronic device and it is now a moving-away event), the existing technology may still determine that the proximity event persists, resulting in an incorrect judgment.

[0005] In addition to the environmental factors mentioned above affecting the capacitance of the sensing electrode, noise also affects the capacitance of the sensing electrode. Therefore, noise should also be considered to correct the baseline in order to improve the accuracy of proximity sensing.

[0006] In view of the problems of the prior art, the present invention proposes a proximity detection circuit and a baseline correction method, which can distinguish whether the capacitance change of the sensing electrode is caused by environmental factors and / or noise or by an object / human body, so as to appropriately correct the baseline according to different situations, thereby improving the accuracy of proximity sensing. Summary of the Invention

[0007] One objective of this invention is to provide a proximity detection circuit and a baseline correction method, which determines whether the capacitance change of the sensing electrode is caused by environmental factors and / or noise or by an object / human body based on a detection data and a baseline data, so as to appropriately correct the baseline data according to different situations, thereby improving the accuracy of proximity sensing.

[0008] One objective of this invention is to provide a proximity detection circuit and a baseline correction method, which determines whether the capacitance change of the sensing electrode is caused by environmental factors and / or noise or by an object / human body based on a detection data of a sensing channel and a reference data of a reference channel, so as to appropriately correct the baseline data according to different situations, thereby improving the accuracy of proximity sensing.

[0009] The present invention provides a baseline correction method, which detects a sensing electrode to generate detection data, generates baseline data based on the detection data, and determines to correct the baseline data with a first correction amount or a second correction amount based on a difference value between the detection data and the baseline data, wherein the second correction amount is greater than the first correction amount.

[0010] The present invention also provides a proximity detection circuit, which includes a detection circuit, a baseline processing circuit, and a proximity sensing circuit. The detection circuit generates detection data, the baseline processing circuit is coupled to the detection circuit and generates baseline data based on the detection data, and determines to correct the baseline data with a first correction amount or a second correction amount based on a difference value between the detection data and the baseline data, wherein the second correction amount is greater than the first correction amount, and the proximity sensing circuit is coupled to the baseline processing circuit and generates a proximity signal based on the detection data, the baseline data, and a proximity threshold. Attached Figure Description

[0011] Figure 1 This is a block diagram of a proximity detection circuit according to an embodiment of the present invention. Figure 2 This is a flowchart of a baseline correction method according to an embodiment of the present invention; Figure 3 This is a flowchart of a baseline correction method according to another embodiment of the present invention; Figure 4 This is a block diagram of a proximity detection circuit according to another embodiment of the present invention; Figure 5 This is a flowchart of a baseline correction method according to another embodiment of the present invention.

[0012] Explanation of symbols in the attached drawings: 5. Sensing electrodes; 7. Reference electrode; 10. Proximity detection circuit; 21. Sensing circuit; 22. Sensing circuit; 23. Analog-to-digital converter; 24. Analog-to-digital converter; 25. Signal processor; 26. Signal processor; 30. Proximity sensing circuit; 40. Baseline processing circuit; 50. Operational circuit. Detailed Implementation

[0013] To provide a better understanding of the features and effects of the present invention, preferred embodiments and detailed descriptions are provided below: Certain terms are used in the specification and claims to refer to specific elements. However, those skilled in the art will understand that manufacturers may use different names to refer to the same element. Furthermore, this specification and claims do not distinguish elements by differences in name, but rather by differences in the overall technical aspects of the elements. The term "comprising" throughout the specification and claims is an open-ended term and should be interpreted as "comprising but not limited to." Moreover, the term "coupled" here includes any direct and indirect means of connection. Therefore, if a first device is described as coupled to a second device, it means that the first device can be directly connected to the second device, or indirectly connected to the second device through other devices or other means of connection.

[0014] Please see Figure 1 This is a block diagram of a proximity detection circuit according to an embodiment of the present invention. The baseline correction method of the present invention is applied to a proximity detection circuit 10, which can be applied to a proximity sensor, which can be used in smartphones, tablets, or other consumer electronic devices. The proximity detection circuit 10 includes a detection circuit, a proximity sensing circuit 30, and a baseline processing circuit 40. The detection circuit in this embodiment may include a sensing circuit 22, an analog-to-digital converter (ADC) 24, and a signal processor 26.

[0015] In one embodiment of the present invention, the sensing circuit 22 is a capacitive sensing circuit coupled to a sensing electrode 5. The sensing electrode 5 is disposed on an electronic device (not shown) and close to the surface of the electronic device for user operation. The sensing electrode 5 is equivalent to a capacitor, and its equivalent capacitance can be changed by the human body or objects, such as a stylus, and can also be changed by environmental factors and noise. The sensing circuit 22 can transmit a signal to the sensing electrode 5, and the sensing electrode 5 generates an electrical signal, such as voltage or charge, in response to this signal, which is associated with the equivalent capacitance of the sensing electrode 5. The sensing circuit 22 generates a sensing signal VSEN based on the electrical signal of the sensing electrode 5, and the sensing signal VSEN is associated with the equivalent capacitance of the sensing electrode 5. In one embodiment of the present invention, the sensing signal VSEN is an analog signal.

[0016] See also Figure 1 An analog-to-digital converter 24 is coupled to the sensing circuit 22 and converts the sensing signal VSEN from the sensing circuit 22 into a sensing digital signal DSEN. A signal processor 26 is coupled to the analog-to-digital converter 24 and processes the sensing digital signal DSEN to generate detection data Raw, the value of which represents the equivalent capacitance of the sensing electrode 5. The signal processor 26 is coupled to the proximity sensing circuit 30 and the baseline processing circuit 40 to transmit the detection data Raw to both circuits.

[0017] In one embodiment of the present invention, the signal processor 26 may receive several sensing digital signals DSEN and then average them to obtain a single value of the detection data Raw, or it may not average them, and a single sensing digital signal DSEN is simply a single value of the detection data Raw. The baseline processing circuit 40 may generate a baseline data Base based on the detection data Raw and transmit the baseline data Base to the proximity sensing circuit 30. The proximity sensing circuit 30 generates a proximity signal Prox based on the detection data Raw, the baseline data Base, and a proximity threshold. The proximity signal Prox may indicate that a human body or object is approaching the electronic device. In one embodiment of the present invention, a value of 1 for the proximity signal Prox indicates that a human body or object is approaching the electronic device, i.e., a proximity event has occurred, but this is not a limitation; a value of 0 may also indicate that a human body or object is approaching the electronic device. In one embodiment of the present invention, the proximity sensing circuit 30 calculates a difference value between the detection data Raw and the baseline data Base, and compares this difference value with the proximity threshold to generate the proximity signal Prox. For example, if the difference value is greater than the proximity threshold, it is determined that a proximity event has occurred.

[0018] See also Figure 1The proximity detection circuit 10 of the present invention may further include an arithmetic circuit 50, which is coupled to the signal processor 26 and the baseline processing circuit 40. The arithmetic circuit 50 receives detection data Raw and calculates a difference value RawDiff between the current detection data Raw[n] and the previous detection data Raw[n-1]. This difference value RawDiff is referred to as the detection data difference value RawDiff, and can be expressed as RawDiff = Raw[n] - Raw[n-1]. In addition, the arithmetic circuit 50 may further filter the detection data difference value RawDiff to generate a filtered difference value RawDiff. IIR It can be represented as RawDiff IIR [n] = wdiff RawDiff[n] + (1 - wdiff) RawDiff[n-1], where wdiff is a coefficient between 0 and 1, set according to usage requirements, filtering the difference values. IIR The data is transmitted to the baseline processing circuit 40. In one embodiment of the present invention, the arithmetic circuit 50 may be integrated into the signal processor 26. The signal processor 26 may calculate the detection data difference value RawDiff between the current detection data Raw[n] and the previous detection data Raw[n-1], and may further filter the detection data difference value RawDiff to generate a filtered difference value RawDiff. IIR The baseline processing circuit 40 in this embodiment can further filter the difference value RawDiff. IIR Correcting the baseline data (Base). The following example details a baseline correction method according to an embodiment of the present invention.

[0019] Please refer to the following: Figure 2This is a flowchart of a baseline correction method according to an embodiment of the present invention. In this embodiment, the baseline correction method for a state without a proximity event is different from the baseline correction method for a state with a proximity event, so the proximity sensing circuit 30 first determines whether a proximity event has occurred. As shown, the signal processor 26 of the detection circuit executes step S10 to obtain detection data Raw, which is the current detection data Raw[n]. Next, the proximity sensing circuit 30 executes step S12 to determine whether a proximity event has occurred. In one embodiment of the present invention, the proximity sensing circuit 30 calculates a difference value between the detection data Raw[n] and the previous baseline data Base[n-1], and compares this difference value with a proximity threshold to generate a proximity signal Prox to determine whether a proximity event has occurred. In one embodiment of the present invention, the first baseline data Base is equal to the first detection data Raw, so the difference value between the two is zero. The signal processor 26 continues to acquire new detection data Raw as the current detection data Raw[n]. The proximity sensing circuit 30 calculates the difference between the detection data Raw[n] and the previous baseline data Base[n-1] (the first baseline data Base) to determine whether a proximity event has occurred.

[0020] When no proximity event occurs, i.e., the proximity detection circuit 10 is not yet in a proximity state, the baseline processing circuit 40 executes step S20 to determine the filter difference value RawDiff. IIR Whether the absolute value is greater than a threshold noiTHD, filter the difference values ​​RawDiff IIR The meaning is the difference between the current detection data Raw[n] and the previous detection data Raw[n-1]. If the difference is greater than the threshold noiTHD, that is, the change in the detection data Raw is large, it is inferred that most of the capacitance change of the sensing electrode 5 is caused by an object or a human body. Even if the object or human body slowly approaches or moves away from the electronic device, it will still cause a large change in the detection data Raw. Therefore, the baseline processing circuit 40 executes step S30, based on the filtered difference value RawDiff. IIR The baseline data Base is corrected by including only a small proportion of the capacitance change in Base. The corrected baseline data Base can be expressed as Base[n] = Base[n-1] + α RawDiff IIR [n], where α is a coefficient between 0 and 1, set according to usage requirements. This embodiment uses the filter difference value RawDiff. IIR[n] serves as a reference value for judgment and correction, which can improve resistance to environmental factors and noise, thereby enhancing the stability of the output signal, such as the stability of the baseline data Base and the proximity signal Prox. As mentioned above, the proximity detection circuit 10 is not yet in a proximity state, and the baseline processing circuit 40 determines the filtered difference value RawDiff. IIR When the absolute value is greater than the threshold noiTHD, filter the difference value RawDiff. IIR The current baseline data Base[n] is generated by comparing the previous baseline data Base[n-1] with the current baseline data Base[n-1], which is based on the filtered difference value RawDiff. IIR Correcting the baseline data Base. In one embodiment of the present invention, after the signal processor 26 obtains the detection data Raw, it can subsequently generate the detection data difference value RawDiff, and filter the detection data difference value RawDiff to generate the filtered difference value RawDiff. IIR Alternatively, the processing circuit 50 can generate the detection data difference value RawDiff and the filter difference value RawDiff. IIR .

[0021] Following on from the above, filter the difference values ​​RawDiff IIR When the absolute value of the difference between the detected data Raw and the baseline data Base is less than the threshold sigTHD, the baseline processing circuit 40 executes step S22 to determine whether the difference value Delta between the detected data Raw and the baseline data Base is greater than the threshold sigTHD. The baseline processing circuit 40 calculates the difference value Delta between the detected data Raw and the baseline data Base, which can be expressed as Delta[n] = Raw[n] – Base[n-1], that is, the difference value between the current detected data Raw[n] and the previous baseline data Base[n-1]. In another embodiment of the present invention, the baseline processing circuit 40 can calculate the difference value between the current detected data Raw[n] and the current baseline data Base[n] to compare with the threshold sigTHD. If the difference value Delta is greater than the threshold sigTHD, it indicates that the change in the detected data Raw is large, and it is inferred that most of the capacitance change of the sensing electrode 5 is caused by an object or a human body. Even if the object or human body slowly approaches or slowly moves away from the electronic device, it will still cause a large change in the detected data Raw. Therefore, the baseline processing circuit 40 executes step S30 to filter the difference value RawDiff. IIR The baseline data Base is corrected by including only a small percentage of capacitance changes in the baseline data Base. In one embodiment of the invention, only step S20 or step S22 may be performed.

[0022] See also Figure 2 If filtering the difference values ​​RawDiff IIRWhen the absolute value of the difference between the detection data Raw and the baseline data Base is less than the threshold noiTHD, and the difference Delta between the detection data Raw and the baseline data Base is less than the threshold sigTHD, it indicates that the change in the detection data Raw is small, that is, the change in the capacitance of the sensing electrode 5 is small. Therefore, it is inferred that most of the capacitance change of the sensing electrode 5 is caused by environmental factors and / or noise. A larger proportion of the capacitance change is included in the baseline data Base. The baseline processing circuit 40 can execute step S32 to correct the baseline data Base based on the detection data Raw. The corrected baseline data Base can be expressed as Base[n] = Wnorm Raw[n] + (1 - Wnorm) Base[n-1] and Wnorm are correction coefficients, which are between 0 and 1 and are set according to usage requirements. As mentioned above, when the proximity detection circuit 10 is not yet in a proximity state and the change in the detection data Raw is small, the current baseline data Base[n] is generated based on the current detection data Raw[n] and the previous baseline data Base[n-1], that is, the baseline data Base is corrected based on the detection data Raw. When most of the capacitance change of the sensing electrode 5 is caused by environmental factors and / or noise, in step S32, the correction amount of the baseline data Base will be greater than the correction amount in step S30, so the correction coefficient Wnorm will be greater than the correction coefficient α in step S30. The above correction amount can be the difference between the current baseline data Base[n] obtained by correcting the previous baseline data Base[n-1] and the previous baseline data Base[n-1].

[0023] Following the above, the baseline processing circuit 40 can further execute step S24 to determine whether the difference value Delta between the detected data Raw and the baseline data Base is greater than zero. If the difference value Delta is greater than zero, it indicates that the capacitance change of the sensing electrode 5 is positive. This capacitance change may be caused by a human body or an object, so the correction amount for the baseline data Base should be smaller. Therefore, the baseline processing circuit 40 executes step S26, setting the lower-valued first coefficient Wnormp as the correction coefficient Wnorm, and then continues to execute the above step S32. If the difference value Delta is less than zero, the baseline processing circuit 40 executes step S28, setting the higher-valued second coefficient Wnormn as the correction coefficient Wnorm, and then continues to execute the above step S32. Since the second coefficient Wnormn is greater than the first coefficient Wnormp, the correction amount for the baseline data Base obtained by executing step S32 using the second coefficient Wnormn is greater than the correction amount for the baseline data Base obtained by using the first coefficient Wnormp. As can be seen from the above description, the second coefficient Wnormn is greater than the first coefficient Wnormp, and the first coefficient Wnormp is greater than the correction coefficient α in step S30.

[0024] See also Figure 2 When a proximity event occurs, i.e., the proximity detection circuit 10 is in a proximity state, the baseline processing circuit 40 executes step S40 to determine the filter difference value RawDiff. IIR Whether it is greater than a threshold posTHD, in one embodiment of the present invention, the threshold posTHD can be a positive value, filtering the difference value RawDiff. IIR The meaning is the difference between the current detection data Raw[n] and the previous detection data Raw[n-1]. If the difference value RawDiff is filtered... IIR If the value is greater than the threshold posTHD, meaning the variation in the raw detection data is large, it is inferred that most of the capacitance change in sensing electrode 5 is caused by an object or human body. Therefore, the baseline processing circuit 40 executes step S30, based on the filtered difference value RawDiff. IIR The baseline data Base is modified to include only a small percentage of capacitance changes.

[0025] Following on from the above, filter the difference values ​​RawDiff IIR When the value is less than the threshold posTHD, the baseline processing circuit 40 executes step S42 to determine the filter difference value RawDiff. IIR Whether it is less than a threshold negTHD, in one embodiment of the present invention, the threshold negTHD can be negative, if the difference value RawDiff is filtered. IIR If the value is less than the threshold negTHD, meaning the variation in the raw detection data is large, it is inferred that most of the capacitance change in sensing electrode 5 is caused by an object or human body. Therefore, the baseline processing circuit 40 executes step S30, based on the filtered difference value RawDiff. IIR The baseline data Base is corrected by including only a small percentage of capacitance changes in Base. Step S40 is used to determine positive changes in the detection data Raw, such as a person or object moving closer to the electronic device, while step S42 is used to determine negative changes in the detection data Raw, such as a person or object moving away from the electronic device. Executing steps S40 and S42 is equivalent to executing step S20, but accuracy can be improved by setting thresholds posTHD and negTHD. In one embodiment of the invention, step S20 can replace steps S40 and S42. Similarly, steps S40 and S42 can replace step S20.

[0026] See also Figure 2 If filtering the difference values ​​RawDiff IIR Less than the threshold posTHD, and filtering out the difference values ​​RawDiff IIRWhen the value is greater than the threshold negTHD, it indicates that the variation in the detection data Raw is small, meaning that the capacitance change of sensing electrode 5 is small. Therefore, it is inferred that most of the capacitance change of sensing electrode 5 is caused by environmental factors and / or noise. Most of the capacitance change is included in the baseline data Base. The baseline processing circuit 40 can execute step S34, based on the filtered difference value RawDiff. IIR Correcting the baseline data Base. In this embodiment, all capacitance changes are included in the baseline data Base, therefore the corrected baseline data Base can be expressed as Base[n] = Base[n-1] + RawDiff IIR [n]. As can be seen from the above, when the proximity detection circuit 10 is in a proximity state and the change in the detection data Raw is large, step S30 is executed to correct the baseline data Base. When the change in the detection data Raw is small, step S34 is executed to correct the baseline data Base. The amount of correction to the baseline data Base in step S34 is greater than the amount of correction to the baseline data Base in step S30.

[0027] Please refer to the following: Figure 3 This is a flowchart of a baseline correction method according to another embodiment of the present invention. Figure 3 Examples and Figure 2 The embodiments differ only slightly from those in the present invention. Figure 3 In this embodiment, the baseline processing circuit 40 executes step S22. If the difference value Delta between the detected data Raw and the baseline data Base is greater than the threshold sigTHD, it is inferred that most of the capacitance change in the sensing electrode 5 is caused by an object or human body. To enhance the proximity detection circuit 10's resistance to environmental factors and noise, for example, by increasing the resistance of the baseline data Base and the proximity signal Prox to environmental factors and noise, the baseline correction method for the proximity detection circuit 10 in a proximity state is executed, i.e., step S40 and subsequent steps are executed. If the difference value RawDiff is filtered... IIR If the value is greater than the threshold posTHD, the baseline processing circuit 40 executes step S30. If the filtered difference value RawDiff is greater than the threshold... IIR If the value is less than the threshold posTHD, the baseline processing circuit 40 executes step S42 to determine the filter difference value RawDiff. IIR Is it less than the threshold negTHD? If so, filter the difference value RawDiff. IIR If the difference is less than the threshold negTHD, baseline processing circuit 40 executes step S30. If the filtered difference value is RawDiff... IIR Less than the threshold posTHD, and filtering out the difference values ​​RawDiff IIR When the threshold negTHD is greater than the threshold, the baseline processing circuit 40 executes step S34.

[0028] Please see Figure 4 This is a block diagram of a proximity detection circuit according to another embodiment of the present invention. As shown in the figure, the proximity detection circuit 10 of this embodiment includes a sensing circuit 22, an analog-to-digital converter 24, a signal processor 26, a proximity sensing circuit 30, and a baseline processing circuit 40, and further includes a sensing circuit 21, an analog-to-digital converter 23, and a signal processor 25. The operation of the sensing circuit 22, the analog-to-digital converter 24, the signal processor 26, and the proximity sensing circuit 30 in this embodiment is the same as... Figure 1 The explanation will not be elaborated further. The detection data Sns generated by the signal processor 26 is the same as... Figure 1 The detection signal Raw in this embodiment. Sensing circuit 21 is a capacitive sensing circuit, coupled to a reference electrode 7. Reference electrode 7 is disposed on the electronic device (not shown) but away from the operating surface of the electronic device. The equivalent capacitance of reference electrode 7 is affected by environmental factors, such as ambient temperature, humidity, and the temperature of the electronic device itself, but is not affected by the human body or other objects. The sensing principle of sensing circuit 21 and reference electrode 7 is the same. Figure 1 The sensing principle of the sensing circuit 22 and sensing electrode 5 in this embodiment will not be described in detail. The sensing circuit 21 is used to generate a reference signal VREF. Knowing the change in capacitance of the reference electrode 7 due to environmental factors can also be used as a reference value to estimate the change in capacitance of the sensing electrode 5 due to environmental factors. In one embodiment of the present invention, the reference signal VREF is an analog signal.

[0029] See also Figure 4 An analog-to-digital converter 23 is coupled to a sensing circuit 21 and converts the reference signal VREF into a reference digital signal DREF. A signal processor 25 is coupled to the analog-to-digital converter 23 and processes the reference digital signal DREF to generate reference data Ref. The value of the reference data Ref represents the equivalent capacitance of the reference electrode 7. The signal processor 25 is coupled to a baseline processing circuit 40 to transmit the reference data Ref to the baseline processing circuit 40. The baseline processing circuit 40 can generate baseline data Base based on the detection data Sns and transmit the baseline data Base to the proximity sensing circuit 30. In this embodiment, the baseline processing circuit 40 can further distinguish whether the capacitance change of the sensing electrode 5 is caused by environmental factors and / or noise or by an object / human body based on the detection data Sns and the reference data Ref, so as to appropriately correct the baseline data Base according to different situations. The following example details another embodiment of the baseline correction method of the present invention.

[0030] Please refer to the following: Figure 5This is a flowchart of a baseline correction method according to another embodiment of the present invention. In this embodiment, the baseline correction method for a proximity event state is the same as the baseline correction method for a proximity event state. As shown in the figure, initially, the baseline processing circuit 40 executes step S50 to obtain the first detection data Sns[0] and the first reference data Ref[0]. Next, step S52 is executed to set a sensing reference Sns0, a reference reference Ref0, and a baseline reference Base0. In this embodiment, the first detection data Sns[0] is set as the sensing reference Sns0, the first reference data Ref[0] is set as the reference reference Ref0, the first detection data Sns[0] is set as the first baseline data Base[0], and the first baseline data Base[0] is set as the baseline reference Base0. After that, step S54 is executed to obtain new detection data Sns[n] and new reference data Ref[n]. Then, step S56 is executed to obtain a detection data difference value SnsDiff, a sensing cumulative change value SnsDrift, and a reference cumulative change value RefDrift. The baseline processing circuit 40 calculates a difference value SnsDiff between the current detection data Sns[n] and the previous detection data Sns[n-1], which is the detection data difference value SnsDiff, and can be expressed as SnsDiff = Sns[n] - Sns[n-1]. The baseline processing circuit 40 calculates a difference value SnsDrift between the current detection data Sns[n] and the sensing reference Sns0, which is the sensing cumulative change value SnsDrift, and can be expressed as SnsDrift = Sns[n] – Sns0. The baseline processing circuit 40 calculates a difference value RefDrift between the current reference data Ref[n] and the reference reference Ref0, which is the reference cumulative change value RefDrift, and can be expressed as RefDrift = Ref[n] – Ref0.

[0031] See also Figure 5The baseline processing circuit 40 executes step S60, determining whether the absolute value of the sensed cumulative change value SnsDrift is less than a threshold EnvSnsH, and whether the absolute value of the reference cumulative change value RefDrift is greater than a threshold EnvRefL. When the absolute value of the sensed cumulative change value SnsDrift is less than the threshold EnvSnsH, and the absolute value of the reference cumulative change value RefDrift is greater than the threshold EnvRefL, it indicates that the change in the detected data Sns is small, that is, the change in the capacitance of the sensing electrode 5 is small, and the change in the capacitance of the reference electrode 7 is large. Therefore, it is inferred that most of the capacitance change of the sensing electrode 5 is caused by environmental factors and / or noise. Therefore, most of the capacitance change of the sensing electrode 5 is included in the baseline data Base. The baseline processing circuit 40 can execute step S70, generating baseline data Base based on the baseline reference Base0 and the sensed cumulative change value SnsDrift, that is, correcting the baseline data Base based on the baseline reference Base0 and the sensed cumulative change value SnsDrift. In this embodiment, the new baseline data Base[n] after correcting the baseline data Base can be expressed as Base[n] = Base0 + SnsDrift. Next, step S72 is executed, setting the new baseline data Base[n] as the baseline reference Base0, i.e., updating the baseline reference Base0. Following this, step S74 is executed, setting the new detection data Sns[n] as the sensing reference Sns0, i.e., updating the sensing reference Sns0, and setting the new reference data Ref[n] as the reference reference Ref0, i.e., updating the reference reference Ref0. The thresholds EnvSnsH and EnvRefL mentioned above are set according to usage requirements.

[0032] If the judgment condition in step S60 is not met, the baseline processing circuit 40 executes step S62 to determine whether the absolute value of the sensed cumulative change value SnsDrift is greater than a threshold SigSnsL and whether the absolute value of the reference cumulative change value RefDrift is less than a threshold SigRefH. When the absolute value of the sensed cumulative change value SnsDrift is greater than the threshold SigSnsL and the absolute value of the reference cumulative change value RefDrift is less than the threshold SigRefH, it indicates that the change in the detected data Sns is large, that is, the change in the capacitance of the sensing electrode 5 is large, and the change in the capacitance of the reference electrode 7 is small. Therefore, it is inferred that most of the capacitance change of the sensing electrode 5 is caused by an object or a human body. The baseline processing circuit 40 can execute step S76 to set the baseline reference Base0 as the new baseline data Base[n] and then continue to execute step S74. The thresholds SigSnsL and SigRefH are set according to the usage requirements.

[0033] If the judgment condition in step S62 is not met, i.e., it is inferred that most of the capacitance change of the sensing electrode 5 is caused by noise, the baseline processing circuit 40 can execute step S64 to determine whether the absolute value of the detection data difference value SnsDiff is less than the threshold NoiTHD. If the absolute value of the detection data difference value SnsDiff is greater than the threshold NoiTHD, it indicates that the capacitance change of the sensing electrode 5 may be caused by a human body or an object, so the correction amount for the baseline data Base should be small. Therefore, the baseline processing circuit 40 executes step S79 to correct the baseline data Base according to the detection data difference value SnsDiff. The new baseline data Base[n] can be expressed as Base[n] = Base[n-1] + GNK SnsDiff and GNK are correction coefficients, ranging from 0 to 1, set according to usage requirements. If the absolute value of the detected data difference SnsDiff is less than the threshold NoiTHD, it indicates that the capacitance change of the sensing electrode 5 is mostly caused by noise, therefore the correction amount for the baseline data Base should be larger. Therefore, the baseline processing circuit 40 executes step S78 to correct the baseline data Base based on the detected data difference SnsDiff. The new baseline data Base[n] can be expressed as Base[n] = Base[n-1] + GNOI SnsDiff and GNOI are correction coefficients, which are between 0 and 1 and are set according to usage requirements. Since the correction amount in step S78 is greater than that in step S79, the correction coefficient GNOI is greater than the correction coefficient GNK. Furthermore, the correction amount in step S70 is greater than that in step S78.

[0034] However, the above description is only a preferred embodiment of the present invention and is not intended to limit the scope of the present invention. All equivalent changes and modifications made in accordance with the shape, structure, features and spirit described in the claims of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A baseline correction method, characterized in that, Include: A sensing electrode generates detection data; A baseline dataset is generated based on the detection data; and Based on a difference between the detection data and the baseline data, a first correction amount or a second correction amount is determined to correct the baseline data, wherein the second correction amount is greater than the first correction amount.

2. The baseline correction method as described in claim 1, characterized in that, Also includes: The difference value is compared with a threshold to determine whether to correct the baseline data with the first correction amount or the second correction amount.

3. The baseline correction method as described in claim 1, characterized in that, Also includes: Based on the difference value, a first coefficient or a second coefficient is set as a correction coefficient, wherein the second coefficient is greater than the first coefficient; and The second correction amount is generated based on the correction factor and the detection data.

4. The baseline correction method as described in claim 3, characterized in that, Also includes: Compare the difference value with a threshold. If the difference value is greater than the threshold, set the first coefficient as the correction coefficient.

5. A proximity detection circuit, characterized in that, Include: A detection circuit generates detection data; A baseline processing circuit, coupled to the detection circuit, generates baseline data based on the detection data, and determines to correct the baseline data with a first correction amount or a second correction amount based on a difference value between the detection data and the baseline data, wherein the second correction amount is greater than the first correction amount. as well as A proximity sensing circuit is coupled to the baseline processing circuit and generates a proximity signal based on the detection data, the baseline data, and a proximity threshold.

6. The proximity detection circuit as described in claim 5, characterized in that, The baseline processing circuit sets a first coefficient or a second coefficient as a correction coefficient based on the difference value. The second coefficient is greater than the first coefficient, and the second correction amount is generated based on the correction coefficient and the detection data.

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