CN111707295B

CN111707295B - Method and device for treating temperature drift

Info

Publication number: CN111707295B
Application number: CN202010827873.5A
Authority: CN
Inventors: 艾娟
Original assignee: Shenzhen Goodix Technology Co Ltd
Current assignee: Shenzhen Goodix Technology Co Ltd
Priority date: 2020-08-17
Filing date: 2020-08-17
Publication date: 2020-12-11
Anticipated expiration: 2040-08-17
Also published as: CN111707295A

Abstract

The embodiment of the application provides a method and a device for processing temperature drift, wherein the method is applied to a proximity sensing device and comprises the following steps: determining filtering data corresponding to the N frame of original capacitance data according to the (N-M + 1) frame of original capacitance data to the N frame of original capacitance data output by the proximity sensing device; determining a first variation corresponding to the N frame of original capacitance data according to the filtering data corresponding to the (N-K + 1) th frame of original capacitance data to the filtering data corresponding to the N frame of original capacitance data, wherein the first variation is used for indicating the fluctuation of the capacitance variation of the sensing capacitor in the proximity sensing device; and determining a reference value corresponding to the N frame of original capacitance data according to the first variation corresponding to the N frame of original capacitance data, wherein the reference value is used for indicating the capacitance variation of the sensing capacitor caused by the environmental temperature variation. The method and the device are used for obtaining more accurate capacitance signals.

Description

Method and device for treating temperature drift

Technical Field

The embodiment of the application relates to the field of sensors, and more particularly relates to a method and a device for processing temperature drift.

Background

The proximity sensing device is a device capable of recognizing whether a person approaches. Fig. 1 shows a typical proximity sensing apparatus, which respectively includes sensors (sensors) for detecting a capacitance change amount ac of a sensing capacitor and a capacitance C of a fixed capacitor of the sensor when a person approaches_x(ii) a An operational Amplifier (AMP) for amplifying the detected capacitance signal, and performing Analog-to-Digital conversion by an Analog Digital Converter (ADC) to generate original capacitance data RawData. Whether a human body approaches can be identified through the magnitude relation between the difference Diff between the original capacitance data RawData and the reference value Out output by the reference unit and the set threshold value, the difference Diff is a value fluctuating around 0 when no human body approaches, the value of the difference Diff is larger when a human body approaches, and the reference value Out output by the reference unit is a fixed value set by experience.

However, in practical applications, such as capacitive in-ear detection, Specific Absorption Rate (SAR) application, etc., the capacitance variation Δ C may drift slowly due to the ambient temperature, and when the capacitance variation caused by the slow temperature rise approaches a set approach threshold, the approach sensing device may determine that a person approaches the proximity sensing device.

Disclosure of Invention

The embodiment of the application provides a method and a device for processing temperature drift, which are used for reducing the capacitance variation of a sensing capacitor in a proximity sensing device caused by the temperature drift and obtaining a more accurate capacitance signal.

In one aspect, a method for processing temperature drift is provided, the method being applied to a proximity sensing apparatus, the method comprising: determining filtering data corresponding to the N frame of original capacitance data according to the (N-M + 1) frame of original capacitance data to the N frame of original capacitance data output by the proximity sensing device; determining a first variation corresponding to the N frame of original capacitance data according to the filtering data corresponding to the (N-K + 1) th frame of original capacitance data to the filtering data corresponding to the N frame of original capacitance data, wherein the first variation is used for indicating the fluctuation of the capacitance variation of the sensing capacitor in the proximity sensing device; determining a reference value corresponding to the N frame of original capacitance data according to a first variation corresponding to the N frame of original capacitance data, wherein the reference value is used for indicating the capacitance variation of the sensing capacitor caused by the environmental temperature variation; and the difference between the reference value corresponding to the original capacitance data of the Nth frame and the reference value corresponding to the original capacitance data of the Nth frame is used for indicating a second variable quantity corresponding to the original capacitance data of the Nth frame, and the second variable quantity is used for indicating a capacitance variable quantity of the sensing capacitor caused by approach.

The method comprises the steps of firstly carrying out data processing on current original capacitance data and original capacitance data in a recent period of time to obtain filtering data, then determining fluctuation of capacitance variation of corresponding sensing capacitance, further determining the capacitance variation caused by ambient temperature according to the fluctuation of the capacitance variation, and being beneficial to reducing the capacitance variation caused by temperature drift and approaching the sensing capacitance in a sensing device, thereby being beneficial to obtaining more accurate capacitance signals, so that the method can be better suitable for various applications based on capacitance detection, such as wearing detection, SRA, pressure detection, touch gesture operation and the like. For example, when the proximity detection is performed, the capacitance variation caused by the temperature drift is extracted, so that the misjudgment probability of the proximity identification is favorably reduced, the influence of the temperature drift is favorably reduced when a human body approaches the proximity sensing device, and the signal-to-noise ratio of the detected capacitance signal is improved. For another example, in a scene of wearing the earphone, the capacitance variation caused by the temperature drift is extracted, so that the wearing state of the earphone can be accurately identified, and the user experience can be improved.

With reference to the first aspect, in an implementation manner of the first aspect, the determining, according to the (N-M + 1) th frame of original capacitance data to the nth frame of original capacitance data output by the proximity sensing device, filtered data corresponding to the nth frame of original capacitance data includes: determining the minimum value from the (N-M + 1) th frame of original capacitance data to the Nth frame of original capacitance data as first data corresponding to the Nth frame of original capacitance data; and determining the filtered data corresponding to the N-th frame of original capacitance data according to the first data corresponding to the (N-L + 1) -th frame of original capacitance data to the first data corresponding to the N-th frame of original capacitance data, wherein L is a positive integer and is less than N.

The minimum value of M frames of continuously output original capacitance data is firstly obtained, and the final filtering data is determined according to L minimum values obtained in a similar mode, so that the method is easy to realize and is beneficial to reducing the buffer amount.

With reference to the first aspect and the foregoing implementation manner, the determining, according to first data corresponding to an (N-L + 1) th frame of original capacitance data to first data corresponding to the nth frame of original capacitance data, filtered data corresponding to the nth frame of original capacitance data includes: determining second data corresponding to the N frame of original capacitance data according to first data corresponding to the (N-L + 1) th frame of original capacitance data to first data corresponding to the N frame of original capacitance data, wherein the second data is the maximum value of the first data corresponding to the (N-L + 1) th frame of original capacitance data to the first data corresponding to the N frame of original capacitance data; and determining second data corresponding to the N-th frame of original capacitance data as filtering data corresponding to the N-th frame of original capacitance data.

The minimum value of M frames of original capacitance data which are continuously output each time is firstly obtained, and then L minimum values obtained in a similar mode are subjected to maximum value processing, so that the gradual change characteristic of capacitance variation caused by temperature drift can be obtained. Because temperature change is slow, so the capacitance change that temperature change arouses is also slow, so the capacitance change that temperature change arouses generally is slower than the capacitance change that human body is close to and arouses, and then this application comes the discernment according to the trend of change to original capacitance data whether the capacitance change that the temperature arouses, can improve the accuracy of capacitance detection signal, and realize fairly simply, accurate.

With reference to the first aspect and the foregoing implementation manner of the first aspect, in another implementation manner of the first aspect, the determining a first variation corresponding to the nth frame of original capacitance data according to filtered data corresponding to the (N-K + 1) th frame of original capacitance data to filtered data corresponding to the nth frame of original capacitance data includes: determining a plurality of adjacent difference values between the filter data corresponding to the (N-K + 1) th frame of original capacitance data and the filter data corresponding to the N N th frame of original capacitance data, wherein the adjacent difference values are the difference values between the filter data corresponding to the (N-K + 1) th frame of original capacitance data and two adjacent filter data in the N N th frame of original capacitance data; and determining a first variation corresponding to the N-th frame of original capacitance data according to the plurality of adjacent differential values.

With reference to the first aspect and the foregoing implementation manner of the first aspect, in another implementation manner of the first aspect, the determining a first variation corresponding to the nth frame of original capacitance data according to the multiple adjacent differential values includes: and determining the sum of the absolute values of (K-1) adjacent difference values between the filtered data corresponding to the (N-K + 1) th frame of original capacitance data and the filtered data corresponding to the N (N-K + 1) th frame of original capacitance data as a first variation corresponding to the N (N-K + 1) th frame of original capacitance data, wherein K > 1.

With reference to the first aspect and the foregoing implementation manner of the first aspect, in another implementation manner of the first aspect, the determining a reference value corresponding to the nth frame of original capacitance data according to the first variation corresponding to the nth frame of original capacitance data includes: if the first variation corresponding to the nth frame of original capacitance data is greater than or equal to the fluctuation threshold, determining a reference value corresponding to the (N-1) th frame of original capacitance data as a reference value corresponding to the nth frame of original capacitance data; or if the first variation corresponding to the nth frame of original capacitance data is smaller than the fluctuation threshold, determining a reference value corresponding to the nth frame of original capacitance data according to the second variation corresponding to the (N-1) th frame of original capacitance data.

With reference to the first aspect and the foregoing implementation manner of the first aspect, in another implementation manner of the first aspect, the determining a reference value corresponding to the nth frame of original capacitance data according to the second variation corresponding to the (N-1) th frame of original capacitance data includes: if the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold, determining the maximum value from the filtered data corresponding to the (N-K + 1) th frame of original capacitance data to the filtered data corresponding to the Nth frame of original capacitance data as the reference value corresponding to the Nth frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is greater than or equal to the approach threshold, determining the sum of the average value of the plurality of adjacent difference values after the elimination of the maximum value and the minimum value in the (K-1) adjacent difference values and the reference value corresponding to the (N-1) th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data.

With reference to the first aspect and the foregoing implementation manner, in another implementation manner of the first aspect, before determining a reference value corresponding to the nth frame of original capacitance data according to the first variation corresponding to the nth frame of original capacitance data, the method further includes: determining the magnitude relation between the second variation corresponding to the (N-1) th frame of original capacitance data and the approximate threshold value; the determining a reference value corresponding to the nth frame of original capacitance data according to the first variation corresponding to the nth frame of original capacitance data includes: if the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold and the first variation corresponding to the N N th frame of original capacitance data is larger than or equal to the fluctuation threshold, determining a reference value corresponding to the (N-1) th frame of original capacitance data as a reference value corresponding to the N N th frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold and the first variation corresponding to the N N th frame of original capacitance data is smaller than the fluctuation threshold, determining the maximum value from the filtered data corresponding to the (N-K + 1) th frame of original capacitance data to the filtered data corresponding to the N N th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is greater than or equal to the approach threshold and the first variation corresponding to the N th frame of original capacitance data is greater than or equal to the fluctuation threshold, determining the reference value corresponding to the (N-1) th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is greater than or equal to the approach threshold and the first variation corresponding to the N th frame of original capacitance data is smaller than the fluctuation threshold, determining the sum of the average value of the adjacent difference values after eliminating the maximum value and the minimum value of the (K-1) adjacent difference values and the reference value corresponding to the (N-1) th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data.

If the first variation corresponding to the nth frame of original capacitance data does not exceed the fluctuation range, the reference value corresponding to the nth frame of original capacitance data can be determined according to the previously determined filtering data, and the reference value corresponding to the original capacitance data can be tracked in time, so that the second variation can be kept at a fixed level, and misjudgment of approach identification is not easy to cause. If the first variation corresponding to the N-th frame of original capacitance data exceeds the fluctuation range, the reference value may not be updated, that is, the reference value output last time may be a result of approaching a human body, while the previous reference value is simply a result caused by temperature drift, and since the temperature drift slowly rises, the result caused by the temperature drift needs to be locked, so as to make a subsequent determination.

With reference to the first aspect and the foregoing implementation manner of the first aspect, in another implementation manner of the first aspect, the method further includes: and determining the difference value of the reference value corresponding to the N-th frame of original capacitance data and the N-th frame of original capacitance data as a second variation corresponding to the N-th frame of original capacitance data.

With reference to the first aspect and the foregoing implementation manner of the first aspect, in another implementation manner of the first aspect, the proximity sensing device is a self-contained proximity sensing device.

With reference to the first aspect and the foregoing implementation manner, in another implementation manner of the first aspect, the (N-M + 1) th frame of original capacitance data to the nth frame of original capacitance data are multiple frames of original capacitance data output within a first time period, where the first time period is greater than or equal to a processing time period of the proximity sensing device when a human body approaches the proximity sensing device.

The original capacitance data output within the time length enough for judging that the human body is close to the proximity sensing device is subjected to data processing, so that the working efficiency of the processor can be obviously improved.

In another aspect, there is provided an apparatus for treating temperature drift, the apparatus comprising: the first determining unit is used for determining filtering data corresponding to the N frame of original capacitance data according to the (N-M + 1) frame of original capacitance data output by the proximity sensing device and the N frame of original capacitance data; a second determining unit, configured to determine, according to filter data corresponding to an (N-K + 1) th frame of original capacitance data to filter data corresponding to an nth frame of original capacitance data, a first variation corresponding to the nth frame of original capacitance data, where the first variation is used to indicate fluctuation of a capacitance variation of a sensing capacitor in the proximity sensing apparatus; a third determining unit, configured to determine a reference value corresponding to the nth frame of original capacitance data according to the first variation corresponding to the nth frame of original capacitance data, where the reference value is used to indicate a capacitance variation of the sensing capacitor caused by an environmental temperature variation; and the difference between the reference value corresponding to the original capacitance data of the Nth frame and the reference value corresponding to the original capacitance data of the Nth frame is used for indicating a second variable quantity corresponding to the original capacitance data of the Nth frame, and the second variable quantity is used for indicating a capacitance variable quantity of the sensing capacitor caused by approach.

With reference to the second aspect, in an implementation manner of the second aspect, the first determining unit is specifically configured to: determining the minimum value from the (N-M + 1) th frame of original capacitance data to the Nth frame of original capacitance data as first data corresponding to the Nth frame of original capacitance data; and determining the filtered data corresponding to the N-th frame of original capacitance data according to the first data corresponding to the (N-L + 1) -th frame of original capacitance data to the first data corresponding to the N-th frame of original capacitance data, wherein L is a positive integer and is less than N.

With reference to the second aspect and the foregoing implementation manner of the second aspect, in another implementation manner of the second aspect, the determining, by the first determining unit, filter data corresponding to an nth frame of original capacitance data according to first data corresponding to an (N-L + 1) th frame of original capacitance data to first data corresponding to the nth frame of original capacitance data includes: determining second data corresponding to the N frame of original capacitance data according to first data corresponding to the (N-L + 1) th frame of original capacitance data to first data corresponding to the N frame of original capacitance data, wherein the second data is the maximum value of the first data corresponding to the (N-L + 1) th frame of original capacitance data to the first data corresponding to the N frame of original capacitance data; and determining second data corresponding to the N-th frame of original capacitance data as filtering data corresponding to the N-th frame of original capacitance data.

With reference to the second aspect and the foregoing implementation manner of the second aspect, in another implementation manner of the second aspect, the second determining unit is specifically configured to: determining a plurality of adjacent difference values between the filter data corresponding to the (N-K + 1) th frame of original capacitance data and the filter data corresponding to the N N th frame of original capacitance data, wherein the adjacent difference values are the difference values between the filter data corresponding to the (N-K + 1) th frame of original capacitance data and two adjacent filter data in the N N th frame of original capacitance data; and determining a first variation corresponding to the N-th frame of original capacitance data according to the plurality of adjacent differential values.

With reference to the second aspect and the foregoing implementation manner of the second aspect, in another implementation manner of the second aspect, the determining, by the second unit, a first variation corresponding to the nth frame of original capacitance data according to the multiple adjacent differential values includes: and determining the sum of the absolute values of (K-1) adjacent difference values between the filtered data corresponding to the (N-K + 1) th frame of original capacitance data and the filtered data corresponding to the N (N-K + 1) th frame of original capacitance data as a first variation corresponding to the N (N-K + 1) th frame of original capacitance data.

With reference to the second aspect and the foregoing implementation manner of the second aspect, in another implementation manner of the second aspect, the third determining unit is specifically configured to: if the first variation corresponding to the nth frame of original capacitance data is greater than or equal to the fluctuation threshold, determining a reference value corresponding to the (N-1) th frame of original capacitance data as a reference value corresponding to the nth frame of original capacitance data; or if the first variation corresponding to the nth frame of original capacitance data is smaller than the fluctuation threshold, determining a reference value corresponding to the nth frame of original capacitance data according to the second variation corresponding to the (N-1) th frame of original capacitance data.

With reference to the second aspect and the foregoing implementation manner, in another implementation manner of the second aspect, if a first variation corresponding to the nth frame of original capacitance data is smaller than the fluctuation threshold, the determining, by the third determining unit, a reference value corresponding to the nth frame of original capacitance data according to a second variation corresponding to the (N-1) th frame of original capacitance data includes: if the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold, determining the maximum value from the filtered data corresponding to the (N-K + 1) th frame of original capacitance data to the filtered data corresponding to the Nth frame of original capacitance data as the reference value corresponding to the Nth frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is greater than or equal to the approach threshold, determining the sum of the average value of the plurality of adjacent difference values after the elimination of the maximum value and the minimum value in the (K-1) adjacent difference values and the reference value corresponding to the (N-1) th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data.

With reference to the second aspect and the foregoing implementation manner of the second aspect, in another implementation manner of the second aspect, the apparatus further includes: a fourth determining unit, configured to determine a magnitude relationship between a second variation corresponding to the (N-1) th frame of original capacitance data and an approach threshold before determining a reference value corresponding to the nth frame of original capacitance data according to the first variation corresponding to the nth frame of original capacitance data; the third determining unit determines a reference value corresponding to the N-th frame of original capacitance data according to the first variation corresponding to the N-th frame of original capacitance data, and includes: if the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold and the first variation corresponding to the N N th frame of original capacitance data is larger than or equal to the fluctuation threshold, determining a reference value corresponding to the (N-1) th frame of original capacitance data as a reference value corresponding to the N N th frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold and the first variation corresponding to the N N th frame of original capacitance data is smaller than the fluctuation threshold, determining the maximum value from the filtered data corresponding to the (N-K + 1) th frame of original capacitance data to the filtered data corresponding to the N N th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is greater than or equal to the approach threshold and the first variation corresponding to the N th frame of original capacitance data is greater than or equal to the fluctuation threshold, determining the reference value corresponding to the (N-1) th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is greater than or equal to the approach threshold and the first variation corresponding to the N th frame of original capacitance data is smaller than the fluctuation threshold, determining the sum of the average value of the adjacent difference values after eliminating the maximum value and the minimum value of the (K-1) adjacent difference values and the reference value corresponding to the (N-1) th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data.

With reference to the second aspect and the foregoing implementation manner of the second aspect, in another implementation manner of the second aspect, the apparatus further includes: and the fifth determining unit is used for determining the difference value of the reference value corresponding to the nth frame of original capacitance data and the nth frame of original capacitance data as the second variation corresponding to the nth frame of original capacitance data.

With reference to the second aspect and the foregoing implementation manner of the second aspect, in another implementation manner of the second aspect, the proximity sensing device is a self-contained proximity sensing device.

In a third aspect, a chip is provided, which includes: and a processor, configured to call and run the computer program from the memory, so that the device on which the chip is installed performs the method in the first aspect or each implementation manner thereof.

In a fourth aspect, there is provided an apparatus for processing temperature drift, comprising: a processor and a memory, the memory being used for storing a computer program, and the processor being used for calling and executing the computer program stored in the memory, and executing the method of the first aspect or its implementation manner.

In a fifth aspect, a computer-readable storage medium is provided for storing a computer program, which causes a computer to execute the method of the first aspect or its implementations.

Drawings

Fig. 1 is an application scenario diagram according to an embodiment of the present application.

Fig. 2 is a schematic block diagram of a method for processing temperature drift of an embodiment of the present application.

Fig. 3 is a flow chart of a method for processing temperature drift according to an embodiment of the present application.

Fig. 4 is a schematic diagram of raw capacitance data and a reference value when no human body approaches in the embodiment of the present application.

Fig. 5 is a schematic diagram of the difference value when no human body approaches in the embodiment of the present application.

Fig. 6 is a schematic diagram of original capacitance data and a reference value when a human body approaches in the embodiment of the present application.

Fig. 7 is a schematic diagram of the difference value when a human body approaches in the embodiment of the present application.

Fig. 8 shows a schematic block diagram of an apparatus for processing temperature drift according to an embodiment of the present application.

Fig. 9 shows a schematic block diagram of another apparatus for processing temperature drift according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings.

Fig. 1 shows an application scenario diagram according to an embodiment of the present application.

Fig. 2 shows a schematic block diagram of a method 100 for processing temperature drift of an embodiment of the application. The method 100 may be performed by a reference unit in fig. 1, which may be, for example, a processor. As shown in fig. 2, the method 100 includes some or all of the following:

s110, determining filtering data corresponding to the N frame of original capacitance data according to the (N-M + 1) frame of original capacitance data to the N frame of original capacitance data output by the proximity sensing device;

s120, determining a first variation corresponding to the N frame of original capacitance data according to the filtering data corresponding to the (N-K + 1) th frame of original capacitance data to the filtering data corresponding to the N frame of original capacitance data, wherein the first variation is used for indicating the fluctuation of the capacitance variation of the sensing capacitor in the proximity sensing device;

s130, determining a reference value corresponding to the N frame of original capacitance data according to a first variation corresponding to the N frame of original capacitance data, wherein the reference value is used for indicating the capacitance variation of the sensing capacitor caused by the environmental temperature variation;

the capacitance variation of the sensing capacitor caused by the approach is indicated by the difference between the reference values corresponding to the original capacitance data of the nth frame and the original capacitance data of the nth frame.

Specifically, the processor may perform data processing on multiple frames of original capacitance data that are recently output at present to obtain corresponding filtered data, that is, the filtered data corresponding to the nth frame of original capacitance data is obtained by performing a series of data processing on M frames of original capacitance data that are continuously output and include the nth frame of original capacitance data; the processor determines a first variable quantity corresponding to the currently output original capacitance data according to the recently acquired filtering data corresponding to the multiple frames of original capacitance data, wherein the first variable quantity corresponding to each frame of original capacitance data forms fluctuation of the capacitance variable quantity of the sensing capacitor in the proximity sensing device; and then the processor determines a reference value corresponding to the currently output original capacitance data according to a first variation corresponding to the currently output original capacitance data, wherein the reference value is used for indicating a capacitance variation caused by the ambient temperature, a difference value between each frame of original capacitance data and the corresponding reference value is used for indicating a second variation corresponding to the corresponding original capacitance data, and the second variation is used for indicating a capacitance variation caused by approach. And the second variation corresponding to each frame of original capacitance data can be used to obtain a reference value corresponding to the next frame of original capacitance data. Namely, the second variation corresponding to the N-th frame of original capacitance data is used to obtain the reference value corresponding to the (N + 1) -th frame of original capacitance data, the second variation corresponding to the (N-1) -th frame of original capacitance data is used to obtain the reference value corresponding to the N-th frame of original capacitance data, and so on.

In general, the original capacitance data output by the proximity sensing device may be a capacitance variation caused by the ambient temperature alone, or may include both the capacitance variation caused by the approach of a person and the capacitance variation caused by the ambient temperature. It should be noted that the capacitance change amount caused by approach in the embodiment of the present application may include both the capacitance change amount when no person approaches or the capacitance change amount when a person approaches.

It should be noted that, when the number of the currently output original capacitance data is smaller than the number M of the original capacitance data used for determining the filtered data, the reference value output by the processor may always be a fixed data (e.g., the first original capacitance data). When the number of the currently output original capacitance data is greater than the number M of the original capacitance data used for determining the filtered data, step S110 in the method 100 may be executed every time one frame of the original capacitance data is output.

Similarly, when the number of the currently determined filtered data is smaller than the number K of the filtered data for determining the first variation, the reference value output by the processor may still be a fixed data (e.g., the first original capacitance data). When the number of the currently determined filtered data is greater than the number K of the filtered data for determining the first variation, the method 100 may be performed every time the filtered data corresponding to one frame of the original capacitance data is determined.

Therefore, the method for processing the temperature drift according to the embodiment of the application is beneficial to reducing the capacitance variation of the sensing capacitor in the proximity sensing device caused by the temperature drift, so as to be beneficial to obtaining a more accurate capacitance signal, and thus, the method can be better suitable for various applications based on capacitance detection, such as wearing detection, SRA, pressure detection, touch gesture operation and the like. For example, when the proximity detection is performed, the capacitance variation caused by the temperature drift is extracted, so that the misjudgment probability of the proximity identification is favorably reduced, the influence of the temperature drift is favorably reduced when a human body approaches the proximity sensing device, and the signal-to-noise ratio of the detected capacitance signal is improved. For another example, in a scene of wearing the earphone, the capacitance variation caused by the temperature drift is extracted, so that the wearing state of the earphone can be accurately identified, and the user experience can be improved.

Optionally, in this embodiment of the application, the (N-M + 1) th frame of original capacitance data to the nth frame of original capacitance data are multiple frames of original capacitance data output within a first time period, where the first time period is greater than or equal to a processing time period of the proximity sensing device when a human body approaches the proximity sensing device.

The processing time of the proximity sensing device when the output time of the M frames of continuous original capacitance data in the embodiment of the application is greater than or equal to the processing time of the proximity sensing device when a human body approaches the proximity sensing device, that is, the time for acquiring the capacitance variation of the sensing capacitor can be further limited. The original capacitance data output within the time length enough for judging that the human body is close to the proximity sensing device is processed, so that the working efficiency of the processor can be obviously improved.

Optionally, in the embodiment of the present application, the method is particularly suitable for use in a self-contained proximity sensing apparatus, that is, the proximity sensing apparatus in the embodiment of the present application may be a self-contained proximity sensing apparatus. The method of the embodiment of the present application can be used for various detection based on capacitance, for example, the application scenario may be capacitive-based in-ear detection, capacitive-based pressure detection, capacitive-based wearing detection, and Specific Absorption Rate (SAR) application.

Optionally, in this embodiment of the application, the determining, according to the (N-M + 1) th frame of original capacitance data to the nth frame of original capacitance data output by the proximity sensing device, filter data corresponding to the nth frame of original capacitance data includes: determining the minimum value from the (N-M + 1) th frame of original capacitance data to the Nth frame of original capacitance data as first data corresponding to the Nth frame of original capacitance data; and determining the filtered data corresponding to the N-th frame of original capacitance data according to the first data corresponding to the (N-L + 1) -th frame of original capacitance data to the first data corresponding to the N-th frame of original capacitance data, wherein L is a positive integer and is less than N.

An alternative implementation is: and performing other data processing such as maximum value, median value or average value and the like on the M frames of original capacitance data continuously output each time, and determining final filtering data according to the processed L frame data.

Optionally, in this embodiment of the application, the determining, according to first data corresponding to (N-L + 1) th frame original capacitance data to first data corresponding to the nth frame original capacitance data, filter data corresponding to the nth frame original capacitance data includes: determining second data corresponding to the N frame of original capacitance data according to first data corresponding to the (N-L + 1) th frame of original capacitance data to first data corresponding to the N frame of original capacitance data, wherein the second data is the maximum value of the first data corresponding to the (N-L + 1) th frame of original capacitance data to the first data corresponding to the N frame of original capacitance data; and determining second data corresponding to the N-th frame of original capacitance data as filtering data corresponding to the N-th frame of original capacitance data.

The minimum value of M frames of original capacitance data which are continuously output every time is firstly solved, and then the maximum value of L minimum values which are solved in a similar mode is solved, so that the slow change characteristic of capacitance variation caused by temperature drift can be obtained. Because temperature change is slow, so the capacitance change that temperature change arouses is also slow, so the capacitance change that temperature change arouses generally is slower than the capacitance change that human body is close to and arouses, and then this application comes the discernment according to the trend of change to original capacitance data whether the capacitance change that the temperature arouses, can improve the accuracy of capacitance detection signal, and realize fairly simply, accurate.

Optionally, the filtered data may be obtained by performing data processing on continuously output multiple frames of original capacitance data once, or may be obtained by performing data processing multiple times, for example, a combination of a minimum value operation and a maximum value operation, a combination of a minimum value operation and a median value operation, or may also be three kinds of data processing. The embodiment of the present application does not limit how to obtain the filtered data.

Optionally, in this embodiment of the application, the determining, according to the filtered data corresponding to the (N-K + 1) th frame of original capacitance data to the filtered data corresponding to the nth frame of original capacitance data, a first variation corresponding to the nth frame of original capacitance data includes: determining a plurality of adjacent difference values between the filter data corresponding to the (N-K + 1) th frame of original capacitance data and the filter data corresponding to the N N th frame of original capacitance data, wherein the adjacent difference values are the difference values between the filter data corresponding to the (N-K + 1) th frame of original capacitance data and two adjacent filter data in the N N th frame of original capacitance data; and determining a first variation corresponding to the N-th frame of original capacitance data according to the plurality of adjacent differential values.

Specifically, there are (K-1) adjacent difference values between the K frames of filtered data, and the embodiments of the present application may use a plurality of adjacent difference values to obtain the corresponding first variation. It is also possible to use all neighboring difference values, i.e. (K-1) neighboring difference values, to obtain the corresponding first variance.

Alternatively, the adjacent differential value may also be a difference value of two pieces of filtered data equally spaced between K frames of filtered data. For example, there are 7 frames of filtered data in total, and 2 adjacent difference values may be determined, specifically, the difference value between the first frame of filtered data and the fourth frame of filtered data and the difference value between the fourth frame of filtered data and the seventh frame of filtered data, that is, the two adjacent difference values may be directly adjacent or indirectly adjacent. The embodiments of the present application are not limited thereto.

The corresponding first variation is determined through the continuously determined (K-1) adjacent difference values in the K frames of filtering data, and the fluctuation of the more accurate capacitance variation can be obtained.

Optionally, in this embodiment of the application, the determining, according to the multiple adjacent differential values, a first variation corresponding to the nth frame of original capacitance data includes: and determining the sum of the absolute values of (K-1) adjacent difference values between the filtered data corresponding to the (N-K + 1) th frame of original capacitance data and the filtered data corresponding to the N (N-K + 1) th frame of original capacitance data as a first variation corresponding to the N (N-K + 1) th frame of original capacitance data.

Optionally, other processing may be performed on the (K-1) adjacent difference values to obtain corresponding first variations. For example, the absolute value of the difference between the first and last values of the (K-1) adjacent difference values may be determined as the corresponding first variation. For another example, the absolute value of the average value of the (K-1) adjacent differential values may be determined as the corresponding first variation.

Alternatively, the sum of the squares of the (K-1) adjacent difference values (i.e., the mean square error of the K frames of filtered data) may be determined as the first variation corresponding to the nth frame of original capacitance data.

Optionally, in this embodiment of the application, the reference value corresponding to the nth frame of original capacitance data may be determined by combining a magnitude relationship between a first variation corresponding to the nth frame of original capacitance data and a fluctuation threshold and/or a magnitude relationship between a second variation corresponding to the (N-1) th frame of original capacitance data and an approach threshold.

It should be understood that the fluctuation threshold and the proximity threshold in the embodiments of the present application are both empirical thresholds, the fluctuation threshold refers to a threshold of fluctuation of the capacitance variation amount, and the proximity threshold refers to a threshold of capacitance variation amount caused by proximity.

For example, the magnitude relationship between the first variation corresponding to the N-th frame of original capacitance data and the fluctuation threshold may be determined first, and then the magnitude relationship between the second variation corresponding to the (N-1) -th frame of original capacitance data and the approach threshold may be determined (i.e., fluctuation determination-approach determination). For another example, the magnitude relationship between the second variation corresponding to the (N-1) th frame of original capacitance data and the proximity threshold may be determined, and then the magnitude relationship between the first variation corresponding to the nth frame of original capacitance data and the fluctuation threshold may be determined (i.e., proximity determination-fluctuation determination).

The following describes specific implementations of the reference value corresponding to the nth frame of original capacitance data according to the above two determination sequences.

First, wave judgment-approach judgment

Optionally, in this embodiment of the application, the determining the reference value corresponding to the nth frame of original capacitance data according to the first variation corresponding to the nth frame of original capacitance data includes: if the first variation corresponding to the nth frame of original capacitance data is greater than or equal to the fluctuation threshold, determining a reference value corresponding to the (N-1) th frame of original capacitance data as a reference value corresponding to the nth frame of original capacitance data; or

And if the first variation corresponding to the N-th frame of original capacitance data is smaller than the fluctuation threshold, determining a reference value corresponding to the N-th frame of original capacitance data according to the second variation corresponding to the (N-1) -th frame of original capacitance data.

Optionally, in this embodiment of the application, the determining the reference value corresponding to the N-th frame of original capacitance data according to the second variation corresponding to the (N-1) -th frame of original capacitance data includes: if the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold, determining the maximum value from the filtered data corresponding to the (N-K + 1) th frame of original capacitance data to the filtered data corresponding to the Nth frame of original capacitance data as the reference value corresponding to the Nth frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is greater than or equal to the approach threshold, determining the sum of the average value of the plurality of adjacent difference values after the elimination of the maximum value and the minimum value in the (K-1) adjacent difference values and the reference value corresponding to the (N-1) th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data.

Optionally, if the second variation corresponding to the (N-1) th frame of original capacitance data is greater than or equal to the approach threshold, determining a sum of a reference value corresponding to the (N-1) th frame of original capacitance data and an average value of the (K-3) adjacent difference values from which the maximum value and the minimum value of the (K-1) th adjacent difference values are removed, as the reference value corresponding to the N-th frame of original capacitance data.

Second, approach judgment-fluctuation judgment

Optionally, in this embodiment of the application, the determining the reference value corresponding to the nth frame of original capacitance data according to the first variation corresponding to the nth frame of original capacitance data includes: if the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold and the first variation corresponding to the N N th frame of original capacitance data is larger than or equal to the fluctuation threshold, determining a reference value corresponding to the (N-1) th frame of original capacitance data as a reference value corresponding to the N N th frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold and the first variation corresponding to the N N th frame of original capacitance data is smaller than the fluctuation threshold, determining the maximum value from the filtered data corresponding to the (N-K + 1) th frame of original capacitance data to the filtered data corresponding to the N N th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is greater than or equal to the approach threshold and the first variation corresponding to the N th frame of original capacitance data is greater than or equal to the fluctuation threshold, determining the reference value corresponding to the (N-1) th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is greater than or equal to the approach threshold and the first variation corresponding to the N th frame of original capacitance data is smaller than the fluctuation threshold, determining the sum of the average value of the adjacent difference values after eliminating the maximum value and the minimum value of the (K-1) adjacent difference values and the reference value corresponding to the (N-1) th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data.

And determining a reference value corresponding to the N-th frame of original capacitance data by judging the relationship between the first variation corresponding to the N-th frame of original capacitance data and a fluctuation threshold (namely, an empirically obtained threshold). If the first variation corresponding to the N-th frame of original capacitance data does not exceed the fluctuation range, the reference value corresponding to the N-th frame of original capacitance data can be determined according to the previously determined filtering data, and the reference value corresponding to the original capacitance data can be tracked in time, so that the second variation (i.e., the difference Diff) can be kept at a fixed level, and misjudgment of proximity identification is not easily caused. If the first variation corresponding to the N-th frame of original capacitance data exceeds the fluctuation range, the reference value may not be updated, that is, the reference value output last time may be a result of approaching a human body, while the previous reference value is simply a result caused by temperature drift, and since the temperature drift slowly rises, the result caused by the temperature drift needs to be locked, so as to make a subsequent determination.

Alternatively, when the second variation corresponding to the (N-1) th frame of original capacitance data is greater than or equal to the approach threshold, the reference value when the second variation corresponding to the (N-1) th frame of original capacitance data is less than the approach threshold may be calculated using a unified algorithm. Namely, the reference value corresponding to the N frame of original capacitance data of the person approaching and the no person approaching is the same. For example, the reference value corresponding to the nth frame of raw capacitance data may be unified as the maximum value in the K frames of filtered data determined above. Alternatively, the minimum value, the median value, the average value, and the like in the K frames of the filter data determined above may be used.

Alternatively, the (K-1) adjacent difference values may be processed, for example, a maximum value, a minimum value, a median value, and an average value may be determined therefrom, and the determined values may be added to a reference value corresponding to the (N-1) th frame of original capacitance data to be used as a reference value corresponding to the N-th frame of original capacitance data.

Optionally, when there is a person approaching, in order to reduce the influence of the ambient temperature on the capacitance variation caused by the approach of the person, the maximum value and the minimum value of the K frames of filtered data or (K-1) adjacent difference values may be eliminated, and the remaining items are averaged, so that the slow variation may be extracted well, and the second variation (i.e., the difference Diff) is at a more stable level.

The method 200 for processing temperature drift of the present application will be described in detail below with reference to the flowchart of fig. 3. In particular, the amount of the solvent to be used,

first, the nth frame of raw capacitance data rawdata (n) is generated by the proximity sensing apparatus shown in fig. 1. n denotes an nth frame.

S201, obtaining the minimum value of M frames of original capacitance data RawData from RawData (n-M + 1) to RawData (n), and obtaining first data MinData (n) corresponding to the n frame of original capacitance data:

first data MinData (n) = Min (RawData (n), RawData (n-1), … … RawData (n-M + 1)) corresponding to the n-th frame of original capacitance data;

s202, obtaining the maximum value of first data MinData of N frames from MinData (N-N + 1) to MinData (N) to obtain second data MaxData (N) corresponding to the original capacitance data of the nth frame:

second data maxdata (N) = Max (MinData (N), MinData (N-1), … … MinData (N-N + 1)) corresponding to the N-th frame of original capacitance data;

s203, solving adjacent differential values of second data MaxData corresponding to K items of n frame original capacitance data from MaxData (n-K + 1) to MaxData (n) to obtain (K-1) adjacent differential values Var (1 … K):

namely, (K-1) adjacent differential values Var (1 … K) = (MaxData (n) -MaxData (n-1), … …, MaxData (K-2) -MaxData (K-1));

and S204, summing the absolute values of the adjacent difference values of the item (K-1) to obtain a first variation Sum (Abs (Var (n)):

namely, the first variation Sum (Abs (var (n)) = Abs (| MaxData (n)) = MaxData (n) -MaxData (n-1) | +, … …, | MaxData (K-2) -MaxData (K-1) |) corresponding to the n-th frame original capacitance data.

S205, judging whether a human body approaches, namely judging the size relation between the second variation Diff (n-1) corresponding to the original data of the (n-1) th frame and the approach threshold ProxThr. If so, go to step S206. If so, the process proceeds to step S209.

S206, further judging the magnitude relation between a first variation Sum (Abs (Var (n))) corresponding to the n-th frame of original capacitance data and a fluctuation threshold DeltThr, and if the first variation Sum (Abs (Var (n))) is within the fluctuation range, performing the step S207; if not, the process proceeds to step S208.

S207, a reference value out (n) = max (MaxData (n); … …, MaxData (K-2), MaxData (K-1)) corresponding to the n-th frame of original capacitance data.

S208, a reference value Out (n) = Out (n-1) corresponding to the n-th frame of original capacitance data.

S209, further judging the magnitude relation between a first variation Sum (Abs (Var (n))) corresponding to the n-th frame of original capacitance data and a fluctuation threshold DeltThr, and if the first variation Sum (Abs (Var (n))) is within the fluctuation range, performing step S210; if not, the process proceeds to step S208.

S210, sorting the (K-1) adjacent difference values to obtain (K-1) sorted adjacent difference values VarSort (1, …, K-1) = sort (Var (1), … …, Var (K-1)), eliminating the maximum and minimum values, averaging the remaining entries, and adding the average values to the reference value output last time:

namely Out (n) = Out (n-1) + mean corresponding to the n frame original capacitance data (VarSort (2), …, VarSort (K-2)).

Fig. 4 to 7 show schematic diagrams of various stages of an embodiment of the present application.

Specifically, fig. 4 shows a diagram of raw capacitance data versus a reference value when no human body is approaching. Fig. 5 shows a schematic diagram of the difference Diff when no human body approaches. As can be seen from fig. 4 and 5, by updating the reference value in time using the method of the embodiment of the present application, the difference value Diff does not exceed the approach threshold over time, and thus it is not determined that no person approaches as a person approaches.

FIG. 6 shows a graph of raw capacitance data versus a reference value when a human body is approaching. Fig. 7 shows a diagram of the difference Diff when a human body approaches. It can be seen from fig. 6 and 7 that when there is a capacitance variation caused by both the ambient temperature and the human body approaching, the capacitance variation caused by the ambient temperature in the gradual change can be better extracted, so that the difference Diff can be at a more stable level.

Fig. 4 to fig. 7 are diagrams illustrating that the reference value can track the capacitance variation caused by the ambient temperature in time, and accurately reflect the real operating state of the user.

The method for processing temperature drift according to the embodiment of the present application is described above in detail, and the apparatus for processing temperature drift according to the embodiment of the present application is described below with reference to fig. 8, and the technical features described in the embodiment of the method are applicable to the following embodiments of the apparatus.

Fig. 8 shows a schematic block diagram of an apparatus 300 for processing temperature drift according to an embodiment of the present application, and as shown in fig. 8, the apparatus 300 includes:

the first determining unit 310 is configured to determine, according to the (N-M + 1) th frame of original capacitance data output by the proximity sensing apparatus to the nth frame of original capacitance data, filtering data corresponding to the nth frame of original capacitance data;

a second determining unit 320, configured to determine, according to the filtered data corresponding to the (N-K + 1) th frame of original capacitance data to the filtered data corresponding to the nth frame of original capacitance data, a first variation corresponding to the nth frame of original capacitance data, where the first variation is used to indicate fluctuation of a capacitance variation of a sensing capacitor in the proximity sensing apparatus;

a third determining unit 330, configured to determine a reference value corresponding to the nth frame of original capacitance data according to the first variation corresponding to the nth frame of original capacitance data, where the reference value is used to indicate a capacitance variation of the sensing capacitor caused by an environmental temperature change;

and the difference between the reference value corresponding to the original capacitance data of the Nth frame and the reference value corresponding to the original capacitance data of the Nth frame is used for indicating a second variable quantity corresponding to the original capacitance data of the Nth frame, and the second variable quantity is used for indicating a capacitance variable quantity of the sensing capacitor caused by approach.

Therefore, the device for processing temperature drift of the embodiment of the application performs data processing on the current original capacitance data and the original capacitance data in the recent period of time, and then determines the fluctuation of the capacitance variation of the corresponding sensing capacitor, so that the capacitance variation caused by the environmental temperature can be determined according to the fluctuation of the capacitance variation, thereby being beneficial to obtaining more accurate capacitance signals and being better suitable for various applications based on capacitance detection. For example, when the proximity detection is performed, the capacitance variation caused by the temperature drift is extracted, so that the misjudgment probability of the proximity identification is favorably reduced, the influence of the temperature drift is favorably reduced when a human body approaches the proximity sensing device, and the signal-to-noise ratio of the detected capacitance signal is improved. For another example, in a scene of wearing the earphone, the capacitance variation caused by the temperature drift is extracted, so that the wearing state of the earphone can be accurately identified, and the user experience can be improved.

Optionally, in this embodiment of the application, the first determining unit is specifically configured to: determining the minimum value from the (N-M + 1) th frame of original capacitance data to the Nth frame of original capacitance data as first data corresponding to the Nth frame of original capacitance data; and determining the filtered data corresponding to the N-th frame of original capacitance data according to the first data corresponding to the (N-L + 1) -th frame of original capacitance data to the first data corresponding to the N-th frame of original capacitance data, wherein L is a positive integer and is less than N.

Optionally, in this embodiment of the application, the determining, by the first determining unit, the filtered data corresponding to the N-th frame of original capacitance data according to the first data corresponding to the (N-L + 1) -th frame of original capacitance data to the first data corresponding to the N-th frame of original capacitance data includes: determining second data corresponding to the N frame of original capacitance data according to first data corresponding to the (N-L + 1) th frame of original capacitance data to first data corresponding to the N frame of original capacitance data, wherein the second data is the maximum value of the first data corresponding to the (N-L + 1) th frame of original capacitance data to the first data corresponding to the N frame of original capacitance data; and determining second data corresponding to the N-th frame of original capacitance data as filtering data corresponding to the N-th frame of original capacitance data.

Optionally, in this embodiment of the application, the second determining unit is specifically configured to: determining a plurality of adjacent difference values between the filter data corresponding to the (N-K + 1) th frame of original capacitance data and the filter data corresponding to the N N th frame of original capacitance data, wherein the adjacent difference values are the difference values between the filter data corresponding to the (N-K + 1) th frame of original capacitance data and two adjacent filter data in the N N th frame of original capacitance data; and determining a first variation corresponding to the N-th frame of original capacitance data according to the plurality of adjacent differential values.

Optionally, in this embodiment of the application, the determining, by the second determining unit, a first variation corresponding to the nth frame of original capacitance data according to the multiple adjacent differential values includes: and determining the sum of the absolute values of (K-1) adjacent difference values between the filtered data corresponding to the (N-K + 1) th frame of original capacitance data and the filtered data corresponding to the N (N-K + 1) th frame of original capacitance data as a first variation corresponding to the N (N-K + 1) th frame of original capacitance data.

Optionally, in this embodiment of the application, the third determining unit is specifically configured to: if the first variation corresponding to the nth frame of original capacitance data is greater than or equal to the fluctuation threshold, determining a reference value corresponding to the (N-1) th frame of original capacitance data as a reference value corresponding to the nth frame of original capacitance data; or if the first variation corresponding to the nth frame of original capacitance data is smaller than the fluctuation threshold, determining a reference value corresponding to the nth frame of original capacitance data according to the second variation corresponding to the (N-1) th frame of original capacitance data.

Optionally, in this embodiment of the application, if a first variation corresponding to the nth frame of original capacitance data is smaller than the fluctuation threshold, the third determining unit determines the reference value corresponding to the nth frame of original capacitance data according to a second variation corresponding to the (N-1) th frame of original capacitance data, including: if the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold, determining the maximum value from the filtered data corresponding to the (N-K + 1) th frame of original capacitance data to the filtered data corresponding to the Nth frame of original capacitance data as the reference value corresponding to the Nth frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is greater than or equal to the approach threshold, determining the sum of the average value of the plurality of adjacent difference values after the elimination of the maximum value and the minimum value in the (K-1) adjacent difference values and the reference value corresponding to the (N-1) th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data.

Optionally, in an embodiment of the present application, the apparatus further includes: a fourth determining unit, configured to determine a magnitude relationship between a second variation corresponding to the (N-1) th frame of original capacitance data and an approach threshold before determining a reference value corresponding to the nth frame of original capacitance data according to the first variation corresponding to the nth frame of original capacitance data; the third determining unit determines a reference value corresponding to the N-th frame of original capacitance data according to the first variation corresponding to the N-th frame of original capacitance data, and includes: if the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold and the first variation corresponding to the N N th frame of original capacitance data is larger than or equal to the fluctuation threshold, determining a reference value corresponding to the (N-1) th frame of original capacitance data as a reference value corresponding to the N N th frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold and the first variation corresponding to the N N th frame of original capacitance data is smaller than the fluctuation threshold, determining the maximum value from the filtered data corresponding to the (N-K + 1) th frame of original capacitance data to the filtered data corresponding to the N N th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is greater than or equal to the approach threshold and the first variation corresponding to the N th frame of original capacitance data is greater than or equal to the fluctuation threshold, determining the reference value corresponding to the (N-1) th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data; or if the second variation corresponding to the (N-1) th frame of original capacitance data is greater than or equal to the approach threshold and the first variation corresponding to the N th frame of original capacitance data is smaller than the fluctuation threshold, determining the sum of the average value of the adjacent difference values after eliminating the maximum value and the minimum value of the (K-1) adjacent difference values and the reference value corresponding to the (N-1) th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data.

Optionally, in an embodiment of the present application, the apparatus further includes: and the fifth determining unit is used for determining the difference value of the reference value corresponding to the nth frame of original capacitance data and the nth frame of original capacitance data as the second variation corresponding to the nth frame of original capacitance data.

Optionally, in this embodiment of the present application, the proximity sensing device is a self-contained proximity sensing device.

Optionally, in this embodiment of the application, the (N-M + 1) th frame of original capacitance data to the nth frame of original capacitance data are multiple frames of original capacitance data output within a first time period, where the first time period is longer than a processing time period of the proximity sensing device when a human body approaches the proximity sensing device.

Fig. 9 is a schematic structural diagram of an apparatus 400 for processing temperature drift provided in an embodiment of the present application. The apparatus 400 for processing temperature drift shown in fig. 9 comprises a processor 410, and the processor 410 can call and run a computer program from a memory to implement the method in the embodiment of the present application.

Optionally, as shown in fig. 9, the apparatus 400 for processing temperature drift may further include a memory 420. From the memory 420, the processor 410 can call and run a computer program to implement the method in the embodiment of the present application.

The memory 420 may be a separate device from the processor 410, or may be integrated into the processor 410.

Optionally, the apparatus 400 for processing temperature drift may specifically be the apparatus for processing temperature drift in the embodiment of the present application, and the apparatus 400 for processing temperature drift may implement a corresponding process implemented by the apparatus for processing temperature drift in each method in the embodiment of the present application, and for brevity, details are not described here again.

The embodiment of the present application further provides a chip, where the chip includes a processor, and the processor can call and run a computer program from a memory to implement the method in the embodiment of the present application.

Optionally, the chip may be applied to the apparatus for processing temperature drift in the embodiment of the present application, and the chip may implement a corresponding process implemented by the apparatus for processing temperature drift in each method in the embodiment of the present application, and for brevity, no further description is given here.

It should be understood that the chips mentioned in the embodiments of the present application may also be referred to as a system-on-chip, a system-on-chip or a system-on-chip, etc.

Optionally, the present application further provides a computer-readable medium for storing a computer program to implement the method in the present application.

It should be understood that the processor of the embodiments of the present application may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method embodiments may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.

It will be appreciated that the memory in the embodiments of the subject application can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The non-volatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of example, but not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic random access memory (Synchronous DRAM, SDRAM), Double Data Rate Synchronous Dynamic random access memory (DDR SDRAM), Enhanced Synchronous SDRAM (ESDRAM), Synchronous link SDRAM (SLDRAM), and Direct Rambus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.

It should be understood that the above memories are exemplary but not limiting illustrations, for example, the memories in the embodiments of the present application may also be Static Random Access Memory (SRAM), dynamic random access memory (dynamic RAM, DRAM), Synchronous Dynamic Random Access Memory (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (enhanced SDRAM, ESDRAM), Synchronous Link DRAM (SLDRAM), Direct Rambus RAM (DR RAM), and the like. That is, the memory in the embodiments of the present application is intended to comprise, without being limited to, these and any other suitable types of memory.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method for handling temperature drift, the method being applied in a proximity sensing device, the method comprising:

performing data filtering on the (N-M + 1) th frame original capacitance data to the Nth frame original capacitance data output by the proximity sensing device to obtain filtering data corresponding to the Nth frame original capacitance data;

determining a first variation corresponding to an nth frame of original capacitance data according to a plurality of adjacent difference values between filtering data corresponding to the (N-K + 1) th frame of original capacitance data and filtering data corresponding to the nth frame of original capacitance data, where the adjacent difference value is a difference between two adjacent filtering data in the (N-K + 1) th frame of original capacitance data and the nth frame of original capacitance data, and the first variation is used for indicating fluctuation of capacitance variation of an induction capacitor in the proximity induction device;

determining a reference value corresponding to the N frame of original capacitance data according to a size relation between a first variation corresponding to the N frame of original capacitance data and a fluctuation threshold, wherein the reference value is used for indicating the capacitance variation of the sensing capacitor caused by the change of the environmental temperature, and the fluctuation threshold is a fluctuation threshold of the capacitance variation of the sensing capacitor;

2. The method of claim 1, wherein the data filtering of the (N-M + 1) th frame of raw capacitance data to the nth frame of raw capacitance data output by the proximity sensing device to obtain filtered data corresponding to the nth frame of raw capacitance data comprises:

performing minimum value filtering on the (N-M + 1) th frame original capacitance data to the Nth frame original capacitance data to obtain first data corresponding to the Nth frame original capacitance data;

and determining filtering data corresponding to the N frame of original capacitance data according to first data corresponding to (N-L + 1) th frame of original capacitance data to first data corresponding to the N frame of original capacitance data, wherein L is a positive integer and is less than N.

3. The method according to claim 2, wherein the determining the filtered data corresponding to the N-th frame of raw capacitance data according to the first data corresponding to the (N-L + 1) -th frame of raw capacitance data to the first data corresponding to the N-th frame of raw capacitance data comprises:

and carrying out maximum value filtering on the first data corresponding to the (N-L + 1) th frame of original capacitance data to the first data corresponding to the Nth frame of original capacitance data to obtain filtered data corresponding to the Nth frame of original capacitance data.

4. The method of claim 3, wherein determining a first variation corresponding to the N frame of original capacitance data according to a plurality of adjacent difference values between the filtered data corresponding to the (N-K + 1) th frame of original capacitance data and the filtered data corresponding to the N frame of original capacitance data comprises:

and determining the sum of the absolute values of (K-1) adjacent difference values between the filtered data corresponding to the (N-K + 1) th frame of original capacitance data and the filtered data corresponding to the N (N-K + 1) th frame of original capacitance data as a first variation corresponding to the N (N-K + 1) th frame of original capacitance data, wherein K > 1.

5. The method according to claim 4, wherein the determining the reference value corresponding to the N-th frame of original capacitance data according to a magnitude relationship between a first variation corresponding to the N-th frame of original capacitance data and a fluctuation threshold comprises:

if the first variation corresponding to the nth frame of original capacitance data is greater than or equal to the fluctuation threshold, determining a reference value corresponding to the (N-1) th frame of original capacitance data as a reference value corresponding to the nth frame of original capacitance data; or

If the first variation corresponding to the nth frame of original capacitance data is smaller than the fluctuation threshold, determining a reference value corresponding to the nth frame of original capacitance data according to a magnitude relation between a second variation corresponding to the (N-1) th frame of original capacitance data and an approach threshold, wherein the approach threshold is a threshold of capacitance variation of the sensing capacitor caused by approach.

6. The method according to claim 5, wherein the determining the reference value corresponding to the N-th frame of raw capacitance data according to the magnitude relationship between the second variation corresponding to the (N-1) -th frame of raw capacitance data and the proximity threshold comprises:

if the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold, determining a maximum value from the filtered data corresponding to the (N-K + 1) th frame of original capacitance data to the filtered data corresponding to the N th frame of original capacitance data as a reference value corresponding to the N th frame of original capacitance data; or

And if the second variation corresponding to the (N-1) th frame of original capacitance data is larger than or equal to the approach threshold, determining the sum of the average value of the plurality of adjacent difference values after the elimination of the maximum value and the minimum value in the (K-1) adjacent difference values and the reference value corresponding to the (N-1) th frame of original capacitance data as the reference value corresponding to the N th frame of original capacitance data.

7. The method according to claim 4, wherein before determining the reference value corresponding to the N-th frame of original capacitance data according to a magnitude relationship between a first variation corresponding to the N-th frame of original capacitance data and a fluctuation threshold, the method further comprises:

determining a size relation between a second variation corresponding to the (N-1) th frame of original capacitance data and a proximity threshold, wherein the proximity threshold refers to a threshold of capacitance variation of the sensing capacitor caused by proximity;

determining a reference value corresponding to the nth frame of original capacitance data according to a magnitude relation between a first variation corresponding to the nth frame of original capacitance data and a fluctuation threshold, including:

if the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold and the first variation corresponding to the N N th frame of original capacitance data is larger than or equal to the fluctuation threshold, determining a reference value corresponding to the (N-1) th frame of original capacitance data as a reference value corresponding to the N N th frame of original capacitance data; or

If the second variation corresponding to the (N-1) th frame of original capacitance data is smaller than the approach threshold and the first variation corresponding to the nth frame of original capacitance data is smaller than the fluctuation threshold, determining a maximum value from the filtered data corresponding to the (N-K + 1) th frame of original capacitance data to the filtered data corresponding to the nth frame of original capacitance data as a reference value corresponding to the nth frame of original capacitance data; or

If the second variation corresponding to the (N-1) th frame of original capacitance data is larger than or equal to the approach threshold and the first variation corresponding to the N N th frame of original capacitance data is larger than or equal to the fluctuation threshold, determining a reference value corresponding to the (N-1) th frame of original capacitance data as a reference value corresponding to the N N th frame of original capacitance data; or

And if the second variation corresponding to the (N-1) th frame of original capacitance data is larger than or equal to the approach threshold and the first variation corresponding to the N N th frame of original capacitance data is smaller than the fluctuation threshold, determining the sum of the average value of the adjacent difference values after the maximum value and the minimum value of the (K-1) adjacent difference values are removed and the reference value corresponding to the (N-1) th frame of original capacitance data as the reference value corresponding to the N N th frame of original capacitance data.

8. The method of claim 1, further comprising:

and determining a difference value of the reference value corresponding to the N-th frame of original capacitance data and the N-th frame of original capacitance data as a second variation corresponding to the N-th frame of original capacitance data.

9. The method of any one of claims 1 to 8, wherein the proximity sensing device is a self-contained proximity sensing device.

10. An apparatus for treating temperature drift, the apparatus comprising:

the first determining unit is used for performing data filtering on (N-M + 1) th frame original capacitance data to Nth frame original capacitance data output by the proximity sensing device to obtain filtering data corresponding to the Nth frame original capacitance data;

a second determining unit, configured to determine a first variation corresponding to an nth frame of original capacitance data according to a plurality of adjacent difference values between filter data corresponding to an (N-K + 1) th frame of original capacitance data and filter data corresponding to the nth frame of original capacitance data, where the adjacent difference value is a difference between two adjacent filter data in the (N-K + 1) th frame of original capacitance data and the nth frame of original capacitance data, and the first variation is used to indicate a fluctuation of a capacitance variation of an induction capacitor in the proximity sensing apparatus;

a third determining unit, configured to determine a reference value corresponding to the nth frame of original capacitance data according to a size relationship between a first variation corresponding to the nth frame of original capacitance data and a fluctuation threshold, where the reference value is used to indicate a capacitance variation of the sensing capacitor caused by an environmental temperature change, and the fluctuation threshold is a threshold of fluctuation of the capacitance variation of the sensing capacitor;

11. The apparatus according to claim 10, wherein the first determining unit is specifically configured to:

12. The apparatus according to claim 11, wherein the first determining unit determines the filtered data corresponding to the N-th frame of original capacitance data according to the first data corresponding to the (N-L + 1) -th frame of original capacitance data through the first data corresponding to the N-th frame of original capacitance data, and includes:

13. The apparatus according to claim 12, wherein the second determining unit is specifically configured to:

14. The apparatus according to claim 13, wherein the third determining unit is specifically configured to:

15. The apparatus according to claim 14, wherein if the first variation corresponding to the N-th frame of original capacitance data is smaller than the fluctuation threshold, the third determining unit determines the reference value corresponding to the N-th frame of original capacitance data according to a magnitude relationship between the second variation corresponding to the (N-1) -th frame of original capacitance data and a proximity threshold, including:

16. The apparatus of claim 13, further comprising:

a fourth determining unit, configured to determine a magnitude relation between a second variation corresponding to the (N-1) th frame of original capacitance data and an approach threshold, where the approach threshold is a threshold of a capacitance variation of the sensing capacitance caused by approach, before determining a reference value corresponding to the nth frame of original capacitance data according to a magnitude relation between a first variation corresponding to the nth frame of original capacitance data and a fluctuation threshold;

the third determining unit determines a reference value corresponding to the N-th frame of original capacitance data according to a magnitude relation between a first variation corresponding to the N-th frame of original capacitance data and a fluctuation threshold, and includes:

17. The apparatus of claim 10, further comprising:

a fifth determining unit, configured to determine a difference between the reference value corresponding to the nth frame of original capacitance data and the nth frame of original capacitance data as a second variation corresponding to the nth frame of original capacitance data.

18. The apparatus of any one of claims 10 to 17, wherein the proximity sensing apparatus is a self-contained proximity sensing apparatus.

19. A chip, comprising: a processor for calling and running a computer program from a memory so that a device on which the chip is installed performs the method of any one of claims 1 to 9.

20. An apparatus for treating temperature drift, comprising: a processor and a memory for storing a computer program, the processor for invoking and executing the computer program stored in the memory, performing the method of any one of claims 1 to 9.

21. A computer-readable storage medium for storing a computer program which causes a computer to perform the method of any one of claims 1 to 9.