CN113419210A - Data processing method and device, electronic equipment and storage medium - Google Patents

Abstract

The present application discloses a data processing method, device, electronic device and storage medium, and relates to the technical field of data processing. The method includes: determining jitter characteristic data according to the measurement data to be processed, and the jitter characteristic data is used to verify the filtering effect; Weight parameter; obtain target measurement data according to the weight parameter. The method can flexibly adjust the weight ratio of the measurement data to be processed in the filtering process according to the jitter characteristics of the measurement data to be processed, thereby effectively improving the filtering effect and improving the stability of data measurement.

Description

Data processing method, device, electronic device and storage medium

technical field

The present application relates to the technical field of data processing, and more particularly, to a data processing method, apparatus, electronic device and storage medium.

Background technique

Ultra Wide Band (UWB, Ultra Wide Band) technology is a wireless carrier communication technology, which uses nanosecond non-sinusoidal narrow pulses to transmit data, occupies a wide spectrum range, and is widely used in the arrival phase difference ( PDoA, Phasedifference of arrival) and other measurement calculations. However, the PDoA measured by the current mainstream UWB chips has obvious jitter and poor filtering effect.

SUMMARY OF THE INVENTION

The present application proposes a data processing method, apparatus, electronic device and storage medium to improve the above problems.

In a first aspect, an embodiment of the present application provides a data processing method, the method includes: determining jitter characteristic data according to to-be-processed measurement data, where the jitter characteristic data is used to verify a filtering effect; and according to the to-be-processed measurement data and The jitter characteristic data determines a weight parameter of the to-be-processed measurement data in the filtering process; and the target measurement data is acquired according to the weight parameter.

In a second aspect, an embodiment of the present application provides a data processing apparatus, the apparatus includes: a first data acquisition module, configured to determine jitter characteristic data according to the measurement data to be processed, where the jitter characteristic data is used to verify the filtering effect; a data processing module, configured to determine the weight parameter of the to-be-processed measurement data in the filtering process according to the to-be-processed measurement data and the jitter characteristic data; a second data acquisition module, used to obtain the target measurement according to the weight parameter data.

In a third aspect, embodiments of the present application provide an electronic device, comprising: one or more processors; a memory; and one or more application programs, wherein the one or more application programs are stored in the memory and Configured to be executed by the one or more processors, the one or more application programs are configured to execute the data processing method provided by the first aspect.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where a program code is stored in the computer-readable storage medium, and the program code can be invoked by a processor to execute the data provided in the first aspect above Approach.

A data processing method, device, electronic device and storage medium provided by the present application, the method determines jitter characteristic data according to the measurement data to be processed, the jitter characteristic data is used to verify the filtering effect, and then according to the measurement data to be processed and the jitter The characteristic data determines the weight parameters of the measurement data to be processed in the filtering process, and then obtains the target measurement data according to the weight parameters. The method can flexibly adjust the weight ratio of the measurement data to be processed in the filtering process according to the jitter characteristics of the measurement data to be processed, thereby effectively improving the filtering effect and improving the stability of data measurement.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present application more clearly, the following briefly introduces the drawings that are used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those skilled in the art, other drawings can also be obtained from these drawings without creative effort.

FIG. 1 shows a schematic diagram of the basic principle of UWB angle measurement in the related art.

FIG. 2 shows an example diagram of each PDoA measurement result of the UWB device provided by the embodiment of the present application in the process of stationary-slightly moving-stationary.

FIG. 3 shows an example diagram of the effect of filtering measurement data by using a sliding window FIR filter provided by an embodiment of the present application.

FIG. 4 shows a flowchart of a data processing method provided by an embodiment of the present application.

FIG. 5 shows a flowchart of a data processing method provided by another embodiment of the present application.

FIG. 6 shows a flowchart of a data processing method provided by another embodiment of the present application.

FIG. 7 shows a schematic diagram of data processing performed by an electronic device on measurement data to be processed according to an embodiment of the present application.

FIG. 8 shows a comparison diagram of the filtering effect of the target measurement data proposed in this embodiment and the effect of the existing sliding window filtering processing.

FIG. 9 shows a structural block diagram of a data processing apparatus provided by an embodiment of the present application.

FIG. 10 shows a structural block diagram of an electronic device provided by an embodiment of the present application.

FIG. 11 shows a storage unit for storing or carrying a program code for implementing a data processing method according to an embodiment of the present application according to an embodiment of the present application.

Detailed ways

In order to make those skilled in the art better understand the solutions of the present application, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application.

In order to facilitate the understanding of the present application, the basic principle of UWB angle measurement in the related art is introduced first. As shown in FIG. 1 , the DUT characterizes the UWB device to be measured (such as a UWB tag), and the DUT sends a UWB signal to the measurement device (which may be a mobile communication device such as a mobile phone).

Two antennas antA and antB with a specific distance d are arranged on the measuring device (such as a mobile phone). The measuring device can measure the phases of the UWB signals received by antA and antB and sent from the DUT, thereby calculating the phase difference PDoA. Through PDoA, the path difference p between the antenna distances antA and antB of the DUT can be calculated. From p and d, the angle of arrival θ (the azimuth of the DUT with respect to the measuring end) can be calculated from the (trigonometric) functional relationship.

In the actual device, due to the influence of mutual coupling between the antennas, the measured PDoA has obvious jitter (as shown in Figure 2, which shows that the UWB device is in the static-slightly-moved-static process, each PDoA measurement results). In order to optimize this problem, a sliding-window FIR filter can be used to filter the measurement data. However, after long-term research, the inventor found that, as shown in Figure 3, the sliding-window FIR filter has the following problems: 1. If the filter order is Less (such as the 140-220 order shown in Figure 3), although the group delay is low (fast response speed), the filtering effect; 2. If the filtering order is high (such as the 220-340 order shown in Figure 3) , although the filtering effect is good, but the group delay is high (the response speed is very slow).

Therefore, in order to improve the above problems, the inventor proposes that the weight ratio of the measurement data to be processed in the filtering process can be flexibly adjusted according to the jitter characteristics of the measurement data to be processed, so as to effectively improve the filtering effect, thereby improving the data Data processing method, apparatus, electronic device and storage medium for measured stability.

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

Please refer to FIG. 4 , which shows a flowchart of a data processing method provided by an embodiment of the present application. This embodiment provides a data processing method, which can be applied to an electronic device. The method includes:

Step S110: Determine jitter characteristic data according to the measurement data to be processed, where the jitter characteristic data is used to verify the filtering effect.

In this embodiment, the measurement data to be processed may be understood as the PDoA measurement value obtained by the electronic device, and the specific quantity of the measurement value may not be limited. Optionally, if the buffer unit of the electronic device can buffer a fixed number of PDoA measurement values, the measurement data to be processed can be understood as the fixed number of PDoA measurement values buffered recently.

Among them, the jitter characteristic data can be used to verify the filtering effect, that is, it can reflect the jitter situation of the latest PDoA measurement data. As a way, the jitter characteristic data can be determined according to the measurement data to be processed, so that the jitter characteristic data can be determined according to the latest PDoA measurement value, so that the filtering effect can be better avoided due to the jitter of the PDoA measurement data.

Step S120: Determine a weight parameter of the to-be-processed measurement data in the filtering process according to the to-be-processed measurement data and the jitter characteristic data.

After the jitter characteristic data is determined, the weight parameters of the to-be-processed measurement data in the filtering process can be reasonably adjusted according to the to-be-processed measurement data and the jitter characteristic data, so that the weight of the to-be-processed measurement data in the filtering process can be adjusted in a targeted manner ratio, so that a measurement result with better filtering effect can be obtained.

Step S130: Acquire target measurement data according to the weight parameter.

The target measurement data refers to the current target measurement data. As a method, if the measurement times of the measurement data to be processed is equal to the number of times threshold, the current target measurement data can be obtained based on the first output result, the measurement data to be processed, and the weight parameter of the measurement data to be processed in the filtering process. An output result is obtained through sliding window filtering.

As another way, if the measurement times of the measurement data to be processed is greater than the number of times threshold, the current target measurement data can be obtained based on the second output result, the measurement data to be processed, and the weight parameter of the measurement data to be processed in the filtering process. The second output result is the last target measurement data.

As another way, if the measurement times of the measurement data to be processed is less than the times threshold, the first output result can be directly used as the current target measurement data, and the first output result is obtained through sliding window filtering. The output result may be the result of averaging filtering processing on the measurement data to be processed by the sliding window filtering unit of the electronic device. The specific numerical value of the number of times threshold in this embodiment may not be limited.

In the data processing method provided in this embodiment, the jitter characteristic data is determined according to the measurement data to be processed, the jitter characteristic data is used to verify the filtering effect, and then the measurement data to be processed is determined according to the measurement data to be processed and the jitter characteristic data in the filtering process. The weight parameter of , and then obtain the target measurement data according to the weight parameter. The method can flexibly adjust the weight ratio of the measurement data to be processed in the filtering process according to the jitter characteristics of the measurement data to be processed, thereby effectively improving the filtering effect and improving the stability of data measurement.

Please refer to FIG. 5, which shows a flowchart of a data processing method provided by another embodiment of the present application. This embodiment provides a data processing method, which can be applied to an electronic device, and the method includes:

Step S210 : if the measurement times of the measurement data to be processed is greater than the times threshold, determine jitter characteristic data according to the measurement data to be processed, and the jitter characteristic data is used to verify the filtering effect.

Among them, when the number of measurements of the measurement data to be processed is small, the jitter of the measured PDoA measurement data is not obvious. If the jitter characteristic data is directly determined according to the measurement data to be processed, the verification of the filtering effect may be affected. . In order to overcome this problem, in this embodiment, if the number of measurements of the measurement data to be processed is greater than the number of times threshold, the jitter characteristic data is determined according to the measurement data to be processed, so that the PDoA measurement can be regularly analyzed when the PDoA measurement data is sufficient. The jitter of the data can effectively improve the filtering effect.

Step S220: Determine a weight parameter of the to-be-processed measurement data in the filtering process according to the to-be-processed measurement data and the jitter characteristic data.

Step S230: Acquire target measurement data according to the weight parameter.

The data processing method provided in this embodiment can flexibly adjust the weight ratio of the measurement data to be processed in the filtering process according to the jitter characteristics of the measurement data to be processed, thereby effectively improving the filtering effect and improving the stability of data measurement.

Please refer to FIG. 6 , which shows a flowchart of a data processing method provided by another embodiment of the present application. This embodiment provides a data processing method, which can be applied to an electronic device. The method includes:

Step S310: Determine a variance parameter based on the plurality of measurement data.

In this embodiment, the measurement data to be processed may include multiple measurement data. For example, in a specific application scenario, as shown in FIG. 7 , the electronic device may include a PDoA measurement unit, a buffering unit, a sliding window filtering unit, a parameter calculating unit, and a second filtering calculating unit. When the electronic device (which can be understood as a UWB device) receives the UWB data packet, it can use the PDoA measurement value obtained by the PDoA measurement unit, and input the PDoA measurement value to the buffer unit.

Optionally, if the buffer size of the buffer unit is N, the plurality of measurement data represent the latest N PDoA measurement values. Wherein, when the amount of data M buffered by the buffer unit is less than N, the buffer unit will transmit M pieces of data to the sliding window filtering unit. When the amount of data buffered by the cache unit M is equal to N, the cache unit will transmit M data to the sliding window filtering unit and the parameter calculation unit, and at the same time transmit the latest PDoAk (assuming it is the kth data, k≥N) to the th Two filtering calculation units, in this way, the variance parameter Var _k can be determined based on the N PDoA measurement data.

Step S320: Determine a corresponding specified parameter based on the variance parameter, where the variance parameter and the specified parameter have a mapping relationship.

The specified parameter can be a Q parameter. As a way, the mapping relationship between the variance parameter Var _k and the Q parameter can be established through a mapping table or a mapping function, so that the corresponding Q parameter can be determined based on the variance parameter Var _k . In this embodiment, the variance parameter and the specified parameter The mapping relationship between them can be a non-linear relationship. For example, in a specific application scenario, the mapping relationship between the variance parameter Var _k and the corresponding Q parameter can be established as follows:

Table 1. Mapping relation table between variance parameter Var _k and corresponding Q parameter

Var_k 20 30 40 50 70 90 120 140 Q 0.01 0.05 0.2 1 2 4 8 16

The specific numerical values of the variance parameter Var _k and the specific numerical values of the Q parameter described above are only examples, and do not constitute a limitation on the specific numerical values. Optionally, for the variance parameter Var _k not in the table, the corresponding Q parameter can be found through an interpolation (eg linear interpolation) algorithm.

Step S330: Determine jitter characteristic data based on the specified parameters, where the jitter characteristic data is used to verify the filtering effect.

As a way, in this embodiment, the jitter characteristic data can be determined according to the following formula:

表征抖动特征数据，Q表征指定参数(即前述的Q参数)，P₀表征预设的参数，P_k-1表征上一次计算的第二抖动参数。in,

Characterizing jitter characteristic data, Q characterizing a specified parameter (ie, the aforementioned Q parameter), P ₀ characterizing a preset parameter, and P _k-1 characterizing the second jitter parameter calculated last time.

Step S340: Determine the weight parameter of the measurement data to be processed in the filtering process according to the variance parameter and the jitter characteristic data.

Wherein, in this embodiment, the weight parameter of the measurement data to be processed in the filtering process can be determined according to the following formula:

表征抖动特征数据，Var_k表征方差参数，K表征权重参数。in,

Characterize the jitter characteristic data, Var _k characterizes the variance parameter, and K characterizes the weight parameter.

The current second jitter parameter P _k in this embodiment can be calculated by using the following formula:

P _k = (1-K)*P ^- _k

表征抖动特征数据，该P_k可以用于下一次(K+1次)的滤波计算。Among them, P _k represents the current second jitter parameter, K represents the weight parameter,

Characterizing jitter characteristic data, the P _k can be used for the next (K+1) filtering calculation.

Step S350: Acquire target measurement data according to the weight parameter.

As a way, after the weight parameter is determined, the target measurement data can be obtained according to the weight parameter according to the following calculation formula:

_{PDoA_AFk} =PDoA_AFk _-1 + _K *(PDoAk-PDoA_AFk _-1 )

=(1-K)PDoA_AF _k-1 +K*PDoA _k

Among them, PDoA_AF _k (PDoA after filter, the kth result) represents the current target measurement data, K represents the weight parameter, PDoA _k represents the measurement data to be processed (which can be understood as the latest PDoA _k ), and PDoA_AF _k-1 represents the last time target measurement data. As shown in Figure 7, when k (representing the number of measurements)=N (representing the threshold of the number of times), PDoA_AFk-1 is the output result of the sliding window filtering unit, and when k>N, PDoA_AFk-1 is the output of the second filtering unit result.

In this embodiment, when the jitter trend of the PDoA measurement value changes, the variance parameter Var becomes relatively large, the corresponding Q parameter is also relatively large, and the final calculated weight parameter K is relatively large. Then, in the output of k-th filtering results, the k-1 filtering results account for a small proportion, and the k-th PDoA measurement results account for a large proportion, and the k-th filtering results will depend on the value of PDoA_k.

When there is no jitter change in the trend of the PDoA measurement value, the variance parameter Var is relatively small, the corresponding Q parameter is also small, and the final weight parameter K is also relatively small. In this way, in the output of the k-th filtering results, the k-1 filtering results account for a large proportion, and the k-th PDoA measurement results account for a small proportion, and the k-th filtering results will be the same as the k-1 filtering results. The difference between the filtering results is relatively small (the final result is that the data jitter is small and the filtering effect is good).

In a specific application scenario, please refer to FIG. 8 , which shows a comparison diagram between the filtering effect of the target measurement data proposed in this embodiment and the effect after filtering by the existing sliding window. As shown in Figure 8, the filtering effect of the target measurement data calculated by the data processing method of this scheme is smaller than the jitter of the measurement data calculated by using the sliding window FIR, so that the azimuth angle finally measured by the UWB device of the electronic equipment can be more It is stable, but also responds quickly, and the filtering effect is better.

The data processing method provided in this embodiment can flexibly adjust the weight ratio of the to-be-processed measurement data in the filtering process according to the jitter characteristics of the to-be-processed measurement data, so as to realize the latest PDoA measurement data and the latest data jitter situation Dynamically adjust the weight parameters to dynamically adjust the filtered output results, thereby effectively improving the filtering effect, thereby improving the stability of data measurement.

Please refer to FIG. 9 , which is a structural block diagram of a data processing apparatus provided by an embodiment of the present application. This embodiment provides a data processing apparatus 400 that can run on an electronic device. The apparatus 400 includes: a first data acquisition module 410 , the data processing module 420 and the second data acquisition module 430:

The first data acquisition module 410 is configured to determine jitter characteristic data according to the measurement data to be processed, where the jitter characteristic data is used to verify the filtering effect.

As a way, the first data acquisition module 410 can be specifically used to determine the jitter characteristic data according to the measurement data to be processed if the data volume of the measurement data to be processed is equal to the data volume threshold; or it can be used to measure the measurement data to be processed. When the number of times is greater than the number of times threshold, the jitter characteristic data is determined according to the measurement data to be processed.

In this embodiment, the measurement data to be processed includes a plurality of measurement data. Optionally, the first data acquisition module 410 may be specifically configured to determine a variance parameter based on the multiple measurement data; determine a corresponding specified parameter based on the variance parameter, and the variance parameter and the specified parameter have a mapping relationship; Jitter characteristic data is determined based on the specified parameters.

The data processing module 420 is configured to determine the weight parameter of the measurement data to be processed in the filtering process according to the measurement data to be processed and the jitter characteristic data.

As an example, the data processing module 420 may be specifically configured to determine the weight parameter of the measurement data to be processed in the filtering process according to the variance parameter and the jitter characteristic data.

The second data acquisition module 430 is configured to acquire target measurement data according to the weight parameter.

As an approach, the second data acquisition module 430 may be specifically configured to acquire the current target measurement data based on the first output result, the to-be-processed measurement data and the weight parameter if the measurement times of the measurement data to be processed is equal to the number of times threshold , the first output result is obtained by sliding window filtering; if the measurement times of the measurement data to be processed is greater than the number of times threshold, the current target measurement data is obtained based on the second output result, the measurement data to be processed and the weight parameter, The second output result is the last target measurement data.

Optionally, the second data acquisition module 430 may be further configured to use the first output result as the current target measurement data if the measurement times of the measurement data to be processed is less than the times threshold.

Those skilled in the art can clearly understand that, for the convenience and brevity of description, for the specific working process of the above-described devices and modules, reference may be made to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

In several embodiments provided in this application, the coupling between the modules may be electrical, mechanical or other forms of coupling.

In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically alone, or two or more modules may be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware, and can also be implemented in the form of software function modules.

Referring to FIG. 10 , based on the foregoing data processing method and apparatus, an embodiment of the present application further provides an electronic device 100 that can execute the foregoing data processing method. The electronic device 100 includes a memory 102 and one or more (only one shown in the figure) processors 104 coupled with each other, and a communication line between the memory 102 and the processors 104 is connected. The memory 102 stores programs that can execute the contents of the foregoing embodiments, and the processor 104 can execute the programs stored in the memory 102 .

The processor 104 may include one or more processing cores. The processor 104 uses various interfaces and lines to connect various parts of the entire electronic device 100, and executes by running or executing the instructions, programs, code sets or instruction sets stored in the memory 102, and calling the data stored in the memory 102. Various functions of the electronic device 100 and processing data. Optionally, the processor 104 may adopt at least one of a digital signal processing (Digital Signal Processing, DSP), a Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA), and a Programmable Logic Array (Programmable Logic Array, PLA) implemented in hardware. The processor 104 may integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU), a modem, and the like. Among them, the CPU mainly handles the operating system, user interface and application programs, etc.; the GPU is used for rendering and drawing of the display content; the modem is used to handle wireless communication. It can be understood that, the above-mentioned modem may not be integrated into the processor 104, and is implemented by a communication chip alone.

The memory 102 may include random access memory (Random Access Memory, RAM), or may include read-only memory (Read-Only Memory). Memory 102 may be used to store instructions, programs, codes, sets of codes, or sets of instructions. The memory 102 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.) , instructions for implementing the foregoing embodiments, and the like. The storage data area may also store data (such as phone book, audio and video data, chat record data) created by the electronic device 100 during use.

Please refer to FIG. 11 , which shows a structural block diagram of a computer-readable storage medium provided by an embodiment of the present application. The computer-readable medium 500 stores program codes, and the program codes can be invoked by the processor to execute the methods described in the above method embodiments.

The computer-readable storage medium 500 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read Only Memory), EPROM, hard disk, or ROM. Optionally, the computer-readable storage medium 500 includes a non-transitory computer-readable storage medium. Computer readable storage medium 500 has storage space for program code 510 to perform any of the method steps in the above-described methods. These program codes can be read from or written to one or more computer program products. Program code 510 may be compressed, for example, in a suitable form.

To sum up, in a data processing method, device, electronic device, and storage medium provided by the embodiments of the present application, jitter characteristic data is determined according to the measurement data to be processed, and the jitter characteristic data is used to verify the filtering effect, and then according to the measurement data to be processed The measurement data and the jitter characteristic data are processed to determine the weight parameter of the measurement data to be processed in the filtering process, and then the target measurement data is obtained according to the weight parameter. The method can flexibly adjust the weight ratio of the measurement data to be processed in the filtering process according to the jitter characteristics of the measurement data to be processed, thereby effectively improving the filtering effect and improving the stability of data measurement.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand: it can still be Modifications are made to the technical solutions described in the foregoing embodiments, or some technical features thereof are equivalently replaced; and these modifications or replacements do not drive the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims (10)

1. a data processing method, is characterized in that, described method comprises: Determine jitter characteristic data according to the measurement data to be processed, where the jitter characteristic data is used to verify the filtering effect; Determine the weight parameter of the to-be-processed measurement data in the filtering process according to the to-be-processed measurement data and the jitter characteristic data; Obtain target measurement data according to the weight parameter. 2. The method according to claim 1, wherein the acquiring target measurement data according to the weight parameter comprises: If the measurement times of the measurement data to be processed is equal to the times threshold, obtain the current target measurement data based on the first output result, the measurement data to be processed, and the weight parameter, and the first output result is obtained through sliding window filtering; If the measurement times of the to-be-processed measurement data is greater than the times threshold, the current target measurement data is acquired based on the second output result, the to-be-processed measurement data and the weight parameter, and the second output result is the previous target measurement data. 3. The method according to claim 2, wherein the method further comprises: If the measurement times of the measurement data to be processed is less than the times threshold, the first output result is used as the current target measurement data. 4. The method according to claim 1, wherein the determining the jitter characteristic data according to the measurement data to be processed comprises: If the data volume of the measurement data to be processed is equal to the data volume threshold, the jitter characteristic data is determined according to the measurement data to be processed. 5. The method according to claim 1, wherein the determining the jitter characteristic data according to the measurement data to be processed comprises: If the measurement times of the to-be-processed measurement data is greater than the times threshold, the jitter characteristic data is determined according to the to-be-processed measurement data. 6. The method according to any one of claims 1-5, wherein the measurement data to be processed comprises a plurality of measurement data, and the determination of the jitter characteristic data according to the measurement data to be processed comprises: determining a variance parameter based on the plurality of measurement data; Determine the corresponding specified parameter based on the variance parameter, and the variance parameter and the specified parameter have a mapping relationship; Jitter characteristic data is determined based on the specified parameters. 7. The method according to claim 6, wherein the determining, according to the to-be-processed measurement data and the jitter characteristic data, a weight parameter of the to-be-processed measurement data in a filtering process comprises: The weight parameter of the measurement data to be processed in the filtering process is determined according to the variance parameter and the jitter characteristic data. 8. A data processing device, wherein the device comprises: a first data acquisition module, configured to determine jitter characteristic data according to the measurement data to be processed, where the jitter characteristic data is used to verify the filtering effect; a data processing module, configured to determine the weight parameter of the to-be-processed measurement data in the filtering process according to the to-be-processed measurement data and the jitter characteristic data; The second data acquisition module is configured to acquire target measurement data according to the weight parameter. 9. An electronic device, comprising one or more processors and a memory; One or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs being configured to perform the method of any of claims 1-7. 10. A computer-readable storage medium, wherein a program code is stored in the computer-readable storage medium, wherein when the program code is run by a processor, any one of claims 1-7 is executed method.

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