Adaptive calibration system based on 3D rocker sensor to digital quantity center point

Abstract

The invention relates to the field of electronic signal processing, and discloses a 3D rocker sensor-based digital quantity center point adaptive verification system, which comprises a data acquisition layer used for acquiring an analog signal of a 3D rocker sensor through an analog-to-digital converter and converting the analog signal into a digital signal; the data preprocessing layer is used for carrying out filtering processing and center point correction on the acquired digital signals and dynamically adjusting the maximum value and the minimum value of the signals; the signal conversion layer is used for converting the corrected signal into a standardized data format so as to adapt to a control system; and the signal output layer is used for smoothing the standardized signal and compensating the signal according to action recognition. Through a digital quantity dynamic correction technical scheme based on the 3D rocker sensor, real-time correction of a rocker signal center point is realized, signal deviation caused by drifting and external interference is eliminated, signal stability and processing precision are improved, and meanwhile, robustness and use reliability of a system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic signal processing, and specifically to a 3D joystick sensor to digital quantity center point adaptive calibration system. Background Art

[0002] With the rapid development of human-computer interaction technology, 3D joysticks, as an important input device, are widely used in fields such as game controllers, robot control, and industrial equipment operation. In the prior art, the signal acquisition and processing of 3D joysticks usually adopt fixed initialization calibration and signal mapping methods. For example, the analog signals of the joystick are digitized through a preset algorithm, and then the signals are converted into control data by combining simple filtering and proportional mapping methods. These technical solutions can provide a certain degree of accuracy and stability in the initial use stage of the joystick, and at the same time meet the needs of most basic operations. However, with the complexity of the application scenario and the extension of the device usage time, the prior art solutions show some limitations in a dynamically changing environment.

[0003] On the one hand, during long-term use, 3D joysticks are prone to be affected by hardware aging, environmental interference (such as temperature changes, electromagnetic interference), and insufficient sensor accuracy, resulting in signal drift and jitter. On the other hand, the existing center point calibration methods are usually static settings, lacking real-time performance and dynamic adjustment capabilities, and it is difficult to adapt to the problem of center point offset during use. In addition, in terms of signal processing, the anti-interference ability of the prior art is weak, and the simple filtering method adopted is difficult to effectively process short-term fluctuations and drifts in a complex environment, resulting in unstable signal output. At the same time, the calculation accuracy of the signal direction angle and dynamic mapping is insufficient, which may cause problems such as a decrease in control accuracy. Especially in the trigger conditions for center point correction, the prior art is mostly based on single-condition judgment, there is a possibility of false triggering or missed triggering, and it cannot effectively adapt to the dynamic change requirements in a complex environment. These problems affect the overall performance of the system and the user experience, and further improvement is urgently needed. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention provides a 3D joystick sensor to digital quantity center point adaptive calibration system, which solves the problems of signal drift, center point offset, and unstable signal processing caused by hardware aging, environmental interference, and dynamic changes during the long-term use of 3D joystick signals.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: A 3D joystick sensor to digital quantity center point adaptive calibration system, comprising:

[0006] A data acquisition layer, used to collect analog signals of the 3D joystick sensor through an analog-to-digital converter and convert them into digital signals;

[0007] The data preprocessing layer is used to filter the collected digital signals, correct the center point, and dynamically adjust the maximum and minimum values of the signals.

[0008] The signal conversion layer is used to convert the corrected signals into a standardized data format to adapt to the control system.

[0009] The signal output layer is used to smooth the standardized signals and compensate the signals according to action recognition.

[0010] The dynamic correction layer is used to dynamically adjust the center point position of the joystick by real-time judging the signal change state of the joystick.

[0011] Preferably, the data acquisition layer includes:

[0012] Setting the sampling period and sampling channels;

[0013] Collecting the signals of each channel multiple times and calculating the change amount between adjacent sampling points;

[0014] When the change amount exceeds the set threshold, the current data is retained, otherwise it is discarded.

[0015] Preferably, the data preprocessing layer corrects the center point of the joystick signal, dynamically adjusts the coordinates of the center point by real-time calculating the maximum and minimum values of the signal, and the coordinates of the center point are calculated by the average value of the current maximum and minimum values.

[0016] Preferably, the data preprocessing layer dynamically adjusts the maximum and minimum values according to the signal range of the joystick. If the current sampling value is greater than the maximum value, the maximum value is updated; if the current sampling value is less than the minimum value, the minimum value is updated.

[0017] Preferably, the signal conversion layer calculates the offset direction and angle according to the signal offset of the joystick, where the offset direction is determined by the offset amount of the current signal value relative to the center point, and the offset angle is calculated by the proportional relationship of the offset amount.

[0018] Preferably, the signal conversion layer maps the offset amount of the signal to a standardized range and converts the standardized signal into integer data to adapt to the data format of the control system.

[0019] Preferably, the signal output layer smooths the converted signals, and generates a smooth signal by taking the average value of consecutive multiple signal values by setting a sliding window.

[0020] Preferably, the signal output layer performs signal compensation according to action recognition. When it is judged that the change amplitude of adjacent signal values is less than the set threshold, the current signal value is regarded as a static signal and compensated.

[0021] Preferably, the dynamic correction layer determines whether to re-correct the center point according to the change of the radius of the rocker signal and the magnitude of the signal change within the sampling interval. When the signal radius decreases and the change amount is less than the set threshold, the center point correction is triggered.

[0022] Preferably, the dynamic correction layer updates the position of the center point by calculating the weighted average of the sampling values of the rocker signal within a certain time, so that the center point can adapt to the signal change state of the rocker in real time.

[0023] The present invention provides a 3D rocker sensor-based digital center point adaptive calibration system, which has the following beneficial effects:

[0024] 1. Through the digital quantity dynamic correction technical solution based on the 3D rocker sensor, the present invention achieves the technical effects of real-time correcting the center point of the rocker signal, eliminating drift, and improving signal stability. Compared with the prior art technical solution that only processes signals through a fixed algorithm, the problem of center point offset caused by hardware aging and external interference during long-term use is solved, and the accuracy of signal processing and the robustness of the system are greatly improved.

[0025] 2. By combining the sliding window smoothing and dynamic compensation algorithms, the present invention can effectively filter out the noise signals with short-term fluctuations, and achieve the smoothing and continuity of the output signal. Compared with the prior art method that simply relies on a high sampling frequency to reduce noise, the present invention avoids the problem of system performance degradation caused by excessive hardware resource occupation, and solves the deficiency of unstable signal output in complex scenarios.

[0026] 3. Through the signal dynamic mapping and direction angle calculation technical solutions, the present invention can accurately convert the motion signal of the rocker into standardized control data, ensuring compatibility in different application scenarios. Compared with the simple mapping method in the prior art that does not fully consider the dynamic characteristics of the signal, the problems of insufficient signal accuracy and large angle error are solved, and the response performance of the control system is improved at the same time.

[0027] 4. Through the dynamic correction judgment mechanism combining multiple conditions, the present invention accurately triggers the center point correction operation through multiple verifications such as signal radius decrease, change rate judgment, and time stationary window. Compared with the prior art solution that only relies on a single condition for judgment, the present invention solves the deficiencies of mis-triggering or missed triggering of correction, and ensures the stability and reliability of the center point adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is the internal layer distribution diagram of the system of the present invention;

[0029] Figure 2 It is the rocker correction flow chart of the present invention;

[0030] Figure 3 This is the flowchart of the rocker signal output of the present invention. Specific embodiments

[0031] Next, in combination with the accompanying drawings of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0032] Please refer to the attached Figure 1 - attached Figure 3 , the embodiment of the present invention provides a 3D rocker sensor to digital quantity center point adaptive calibration system, including:

[0033] The data acquisition layer is used to collect the analog signal of the 3D rocker sensor through an analog-to-digital converter and convert it into a digital signal;

[0034] The data preprocessing layer is used to filter the collected digital signal, correct the center point, and dynamically adjust the maximum and minimum values of the signal;

[0035] The signal conversion layer is used to convert the corrected signal into a standardized data format to adapt to the control system;

[0036] The signal output layer is used to smooth the standardized signal and compensate the signal according to action recognition;

[0037] The dynamic correction layer is used to dynamically adjust the center point position of the rocker by real-time judging the signal change state of the rocker;

[0038] The data acquisition layer includes:

[0039] Set the sampling period and sampling channels;

[0040] After collecting the signals of each channel multiple times, calculate the change amount between adjacent sampling points;

[0041] When the change amount exceeds the set threshold, retain the current data, otherwise discard it;

[0042] The data preprocessing layer corrects the center point of the rocker signal. By calculating the maximum and minimum values of the signal in real time, the coordinates of the center point are dynamically adjusted, and the coordinates of the center point are calculated by the average value of the current maximum and minimum values;

[0043] The data preprocessing layer dynamically adjusts the maximum and minimum values according to the signal range of the rocker. If the current sampling value is greater than the maximum value, update the maximum value. If the current sampling value is less than the minimum value, update the minimum value;

[0044] The signal conversion layer calculates the offset direction and angle based on the signal offset of the joystick, where the offset direction is determined by the offset of the current signal value relative to the center point, and the offset angle is calculated through the proportional relationship of the offset;

[0045] The signal conversion layer maps the offset of the signal to a standardized range and converts the standardized signal into integer data to adapt to the data format of the control system;

[0046] The signal output layer performs smoothing processing on the converted signal, generating a smoothed signal by taking the average value of consecutive multiple signal values through setting a sliding window;

[0047] The signal output layer performs signal compensation according to action recognition. When it is judged that the change amplitude of adjacent signal values is less than the set threshold, the current signal value is regarded as a static signal and compensated;

[0048] The dynamic correction layer judges whether the center point needs to be re-corrected according to the radius change of the joystick signal and the magnitude of the signal change amount within the sampling interval. When the signal radius decreases and the change amount is less than the set threshold, the center point correction is triggered;

[0049] The dynamic correction layer updates the position of the center point by calculating the weighted average of the sampling values of the joystick signal within a certain time, enabling the center point to adapt to the signal change state of the joystick in real time.

[0050] Specifically, the core function of the data acquisition layer is to obtain the original signal from the 3D joystick sensor and convert the analog signal into a digital quantity through an analog-to-digital converter (ADC), providing reliable basic data for the processing and correction of subsequent modules. The implementation of the data acquisition layer needs to be connected with the subsequent filtering module, preprocessing module and dynamic correction module to ensure the sufficient accuracy and stability of the acquired data. Generally, the data acquisition layer needs to be designed in combination with the physical characteristics of the joystick and the performance parameters of the sampling system to be compatible with various working conditions and complex external environments.

[0051] In this embodiment, the main implementation steps of the data acquisition layer include the following aspects:

[0052] First, signal acquisition is performed on the three-axis signals (X, Y, Z) of the 3D joystick. Specifically, the system converts the analog signal of the joystick into a digital signal through an analog-to-digital converter. As an option, the sampling period T s can be set to a fixed value according to the requirements of the system response speed, for example, sampling is performed every 10 ms. In a possible implementation manner, each sampling can cover three channels, namely the X-axis, Y-axis, and Z-axis, to capture the complete position information of the joystick in space.

[0053] In some embodiments, to ensure the reliability of the signal, the sampling of each channel will be repeated multiple times. Specifically, assuming the number of single-channel samplings is N c , the system will collect N c times of data within a sampling period and calculate the mean value of the collected values as the final digital signal. The mean value of the sampling values can be expressed as:

[0054]

[0055] where X i represents the original value of the i-th sampling, and X avg is the average value of this channel.

[0056] Secondly, to suppress small-amplitude jitter in the signal, the system adopts the method of minimum unit change filtering. In this method, the change amount |x[n] - x[n - 1]| between sampling points will be compared with a preset threshold Δ min . If the change amount is less than the threshold, the current data will be regarded as invalid data and discarded; if the change amount is greater than the threshold, the current data will be retained. This process can be expressed as:

[0057] If |x[n] - x[n - 1]| > Δ min , then retain x[n]

[0058] where x[n] is the n-th sampling value and Δ min is the filtering threshold set by the system.

[0059] Generally, the minimum unit change filtering can effectively eliminate small-range jitter caused by hardware noise or environmental interference, thereby improving the effectiveness of the data. In a possible implementation, the filtering threshold Δ min can be set to 1% to 5% of the full-scale range according to the sensitivity of the joystick sensor.

[0060] As an extended application, when the system performs multi-channel signal acquisition, it can set the filtering threshold for each channel separately. For example, the filtering threshold for the X-axis signal can be set to Δ min ,X, while the filtering threshold for the Y-axis signal is Δ min ,Y. This method can provide higher adaptability when the sensitivities of the axes of the joystick are inconsistent.

[0061] In addition, to achieve multi-level optimization of the joystick signal, the data acquisition layer also supports the function of periodically adjusting the sampling parameters. For example, when the system detects a change in the intensity of external interference signals, it can dynamically change the sampling period T s or the number of samplings N c to adapt to the new environmental conditions. The adjusted sampling data will be stored in the system memory in real time to support the subsequent data processing module.

[0062] In some embodiments, the data acquisition layer also provides an abnormal signal detection function. When the collected signal exceeds the physical range designed for the joystick (for example, the X-axis signal is greater than X max or less than X min ), the system will record this abnormal state and trigger an alarm mechanism. This design can be used to monitor the hardware health of the joystick and prevent signal distortion caused by sensor failures.

[0063] The function of the data preprocessing layer is to further process the digital signals collected by the data acquisition layer, including signal filtering and correction, center point correction, and dynamic range adjustment, to ensure the stability and accuracy of subsequent signal conversion and output. The data preprocessing layer is closely connected to the data acquisition layer, receives the filtered data output by the acquisition layer, and provides standardized and optimized signal data for the signal conversion layer. Generally, the data preprocessing layer needs to be designed according to the dynamic characteristics of the joystick and the characteristics of environmental interference, so as to meet the requirements of different application scenarios.

[0064] In this embodiment, the data preprocessing layer mainly includes the following functional modules and processing steps:

[0065] First, for the problem of center point drift, the system will perform real-time correction on the center point position of the joystick. Specifically, the initial value of the center point is usually obtained through system calibration, denoted as P c =(X c , Y c ), but with the aging of the hardware or the change of the environment, the center point may drift. In a possible implementation, the center point correction adopts the dynamic average calculation method, and adjusts the center point position dynamically through the maximum value P max =(X max , Y max ) and the minimum value P min =(X min , Y min ) collected in real time. The calculation formula is:

[0066]

[0067] After the center point is corrected, the new center point position is stored in the system memory and used as the reference for subsequent signal conversion.

[0068] In some embodiments, to improve the accuracy of correction, the system will perform multiple samplings on the center point position and take the average value. For example, within a correction period, N c groups of maximum and minimum values are collected, and all sampled values are averaged to calculate a more stable center point coordinate:

[0069]

[0070] Among them, X max,i and X min,i are respectively the maximum and minimum values of the i-th sampling.

[0071] Secondly, the system dynamically adjusts the maximum and minimum value ranges of the signal. As an option, when the currently acquired signal value exceeds the preset range, the system will automatically update the maximum or minimum value. For example, when the X-axis signal X acquired satisfies X > X max , the system will update X max to the current value; when X < X min , then X min will be updated to the current value. This dynamic adjustment mechanism can adapt to fluctuations in hardware performance while ensuring the accuracy of the signal range.

[0072] In a possible implementation, to avoid misadjustment during the dynamic adjustment process, the system will continuously verify the current sampling value multiple times. Only when the consecutive N v sampling values all exceed the range will the update of the maximum or minimum value be triggered. The verification mechanism can further reduce the impact of environmental noise or instantaneous interference on the system.

[0073] In addition, the data preprocessing layer also includes signal normalization processing. The purpose of normalization processing is to map the original signal to the standardized interval [-1, 1] according to the center point and range after dynamic adjustment, so that it can be directly called by the subsequent signal conversion layer. Generally, the normalization formula is as follows:

[0074]

[0075] Among them, S x and S y are respectively the normalized X-axis and Y-axis signals, X c , Y c is the current center point, X max , X min , Y max , Y min are respectively the maximum and minimum values after dynamic adjustment.

[0076] The main function of the signal conversion layer is to further convert the normalized signal output by the data preprocessing layer into a standardized format that the control system can directly use, and at the same time accurately calculate the direction and angle of the signal to support more complex joystick action recognition. The signal conversion layer receives the signal after center point correction and dynamic range adjustment, and its processing result will directly affect the final signal output quality. Generally, the signal conversion layer needs to have high computational accuracy and real-time processing capabilities to adapt to the dynamic changes of the joystick in various operating environments.

[0077] In this embodiment, the specific implementation of the signal conversion layer includes the following main functional modules:

[0078] First, for the direction and angle of the joystick signal, the system calculates the angle of the normalized signal. Specifically, the system calculates the offset angle of the joystick through the relative relationship between the offset of the current signal and the center point. In a possible implementation, the calculation of the offset angle uses the arctangent function:

[0079]

[0080] where X and Y represent the current sampled signal values, X c , Y c represents the center point position, and θ represents the offset angle of the joystick. As an option, to avoid calculation anomalies of the arctangent function in specific angle regions (such as 90° or 270°), the system can use the four-quadrant arctangent function to ensure the continuity and accuracy of the calculation results.

[0081] In some embodiments, the system also classifies the offset direction of the joystick according to the angle value. For example, specific angle intervals are set, corresponding to offset directions such as up and down, left and right, diagonal, etc. Specifically, when -45° ≤ θ < 45°, the signal offset direction is "right"; when 45° ≤ θ < 135°, the direction is "up". This classification method can directly provide input for the control logic.

[0082] Secondly, the system maps the normalized signal to the integer format required by the control system. Generally, the input signal of the control system is required to be within a fixed numerical range, such as [-32768, 32767]. In this embodiment, the system uses a linear mapping method to convert the normalized signal S x , S y into an integer signal L x , L y . The mapping formula is:

[0083] L x = int(32767 × S x ), L y = int(32767 × S y )

[0084] where int represents the floor operation, S x , S y is the normalized signal value, and L x , L y is the converted integer signal.

[0085] In some embodiments, the system calculates the movement stroke based on the displacement of the joystick and stores the stroke information in the format of integer data. Specifically, the movement stroke can be obtained by calculating the normalized value of the joystick and the length of the displacement path:

[0086]

[0087] where D is the normalized stroke length, which can be further converted into an integer form to represent the movement distance of the joystick.

[0088] In addition, the signal conversion layer also supports joint processing of data with different signal dimensions. For example, in the application of a 3D joystick, the Z-axis signal is often used to determine pressing or other actions. As an option, the system can combine the normalized values of the X, Y, and Z axis signals to further calculate the comprehensive offset distance or composite angle to support more complex control requirements.

[0089] In a possible implementation, the signal conversion layer also includes a function for suppressing signal noise. When the normalized signal value of a certain axis fluctuates significantly within a short period of time, the system smooths the signal of that axis through a time window smoothing algorithm. For example, assuming the size of the time window is W, the smoothed signal value is:

[0090]

[0091] where:

[0092] S x [i] represents the normalized signal value of the X axis at the i-th sampling within the time window.

[0093] S y [i] represents the normalized signal value of the Y axis at the i-th sampling within the time window.

[0094] S x ′ represents the normalized signal value of the X axis after smoothing processing.

[0095] S y ′ represents the normalized signal value of the Y axis after smoothing processing.

[0096] W represents the size of the time window, that is, the number of sampling points, which is used to average multiple sampling values.

[0097] i represents the sampling sequence number, and the range of i is from 1 to W.

[0098] This smoothing method can further improve the stability of the converted signal and avoid the influence of signal jitter on the angle calculation or mapping result.

[0099] The main function of the signal output layer is to further optimize and compensate the standardized signal generated by the signal conversion layer, and then output a stable digital signal to meet the requirements of the actual control system. This module not only needs to ensure the real-time and accuracy of the signal, but also takes into account the special requirements of the system for signal stability, so as to achieve efficient and reliable output performance. The signal output layer is closely connected with the signal conversion layer, receiving the standardized signal provided by it, and at the same time smoothing, compensating and dynamically predicting the signal according to the actual situation to adapt to the dynamic changes in different operating environments.

[0100] In this embodiment, the implementation of the signal output layer includes the following main processing modules and methods:

[0101] First, for the short-term fluctuations of the signal, the signal output layer uses a smoothing algorithm to process the signal. Generally, the signal fluctuations within a short period may be caused by external environmental interference or instantaneous errors of the sensor. Specifically, the system performs a sliding window smoothing process on the signal value before output to reduce the impact of short-term fluctuations on the control output. In a possible implementation, the smoothing process is as shown in the content of the signal conversion layer.

[0102] In some embodiments, to further optimize the smoothing effect, the system dynamically adjusts the window size according to the fluctuation characteristics of the current signal. For example, when the change rate of the signal is small, the system can automatically increase the window size; when the signal change rate is fast, the system can reduce the window size to balance the signal stability and response speed.

[0103] Secondly, for the signal output compensation in the stationary state, the signal output layer ensures the accuracy of the signal through threshold judgment and compensation algorithm. Specifically, when it is detected that the change amplitude of the signal is less than the set threshold, the system regards the current signal as a stationary signal and performs a compensated output according to the previous output signal value.

[0104] As a possible implementation, when the signal is judged to be in a stationary state, the system directly outputs the previous signal value.

[0105] This compensation mechanism can effectively prevent the influence of signal drift on the output result in the stationary state, thus improving the signal stability.

[0106] In addition, the signal output layer also includes a signal dynamic prediction module, which is used to predict the change trend of the signal in advance and optimize the output in the motion state. Specifically, the system performs a trend analysis on the historical change data of the signal to predict the signal value at the next moment. The prediction algorithm can adopt a first-order linear model:

[0107]

[0108] where k x and ky is the prediction coefficient set for the system, ΔS x and ΔS y is the change rate of the current signal.

[0109] The main function of the dynamic correction layer is to perform real-time correction on the signal drift caused by hardware aging, sensor errors, or external interference during the use of the joystick. This module is closely connected to the signal output layer. By analyzing the states of historical signals and current signals, it determines whether the joystick needs to perform dynamic center adjustment. Generally, the dynamic correction layer needs to comprehensively judge the change trend, range of the signal, and the action state of the joystick to ensure the accuracy and stability of the correction result.

[0110] In this embodiment, the specific implementation of the dynamic correction layer includes the following main processing steps:

[0111] First, the dynamic correction layer determines whether the joystick is in the centering motion state by detecting the change in the radius of the signal. Specifically, the system calculates the Euclidean distance between the current signal value and the center point, that is, the radius of the signal:

[0112]

[0113] where R[n] is the signal radius of the nth sampling, X[n] and Y[n] are the current X-axis and Y-axis signal values, X c and Y c are the coordinates of the current center point.

[0114] As an option, the system compares the signal radii of multiple consecutive samplings to determine whether there is a decreasing trend. When the signal radius meets the following conditions, the system considers that the joystick is approaching the center point:

[0115] R[n]<R[n-1]<R[n-2]

[0116] In some embodiments, to avoid misjudgment, the system also sets a tolerance threshold, that is, only when R[n-1] < tolerance threshold, it is considered that the current signal is in the centering state.

[0117] Secondly, the dynamic correction layer combines the signal change rate for analysis. Generally, the system determines the signal change rate by calculating the difference between two consecutive sampling signals:

[0118] ΔX = |X[n] - X[n-1]|, ΔY = |Y[n] - Y[n-1]|

[0119] When the change rates ΔX and ΔT of the signal are both less than the preset threshold, the system further confirms that the joystick is in a stationary state and the correction operation can be performed.

[0120] In a possible implementation, the dynamic correction layer also makes a judgment in combination with time factors. For example, when the joystick remains without significant movement within a specific time T s , the system considers that the condition for center point correction is met.

[0121] In addition, in this embodiment, the dynamic correction layer uses the weighted average method to dynamically correct the signal. Specifically, the system performs a weighted average calculation on the signal values within a certain time window to determine the new center point position:

[0122]

[0123] where X c ′ and Y c ′ are the corrected center point coordinates, X[i] and Y[i] are the signal values within the time window, w i is the weight of the i-th signal, and N is the size of the time window.

[0124] As an optimization measure, the system can dynamically adjust the weight w i according to the stability of the signal change. For example, when the signal fluctuates greatly at a certain moment, the corresponding weight at that moment is reduced; while when the signal is relatively stable, the weight at that moment is increased. This dynamic adjustment mechanism can further improve the accuracy of the correction.

[0125] Finally, the dynamic correction layer supports verifying and storing the correction result. After the correction is completed, the system compares the new center point position with the current signal value to ensure that the corrected center point can effectively cover the current signal range. Specifically, the system checks whether the following conditions are met:

[0126] X min ≤X′ c ≤X max ,Y min ≤Y′ c ≤Y max

[0127] If the corrected center point exceeds the preset range, the system will trigger a warning or recalculate.

[0128] In some embodiments, the system can adjust the size of the prediction coefficient according to actual needs. For example, when the moving speed of the joystick is relatively fast, the system can appropriately increase k x and k y to improve the dynamic response ability of the prediction value; while when the moving speed is relatively slow, the prediction coefficient can be reduced to reduce the error of signal prediction.

[0129] Although embodiments of the present invention have been shown and described, those of ordinary skill in the art will appreciate that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Based on the 3D rocker sensor to digital quantity center point adaptive calibration system, it is characterized by: include: The data acquisition layer is used to collect the analog signal of the 3D joystick sensor through an analog-to-digital converter and convert it into a digital signal; The data preprocessing layer is used to filter the collected digital signals, perform center point correction, and dynamically adjust the maximum and minimum values ​​of the signals; The signal conversion layer is used to convert the corrected signal into a standardized data format to adapt to the control system; The signal output layer is used to smooth the normalized signal and compensate the signal according to the action recognition; The dynamic correction layer is used to dynamically adjust the center point position of the joystick by judging the signal change status of the joystick in real time.

2. The adaptive calibration system based on the 3D rocker sensor to digital quantity center point according to claim 1 is characterized in that: The data collection layer includes: Set the sampling period and sampling channel; After collecting the signal of each channel multiple times, the change of adjacent sampling points is calculated; When the change exceeds the set threshold, the current data is retained, otherwise it is discarded.

3. The adaptive calibration system based on the 3D rocker sensor to digital quantity center point according to claim 1 is characterized in that: The data preprocessing layer corrects the center point of the joystick signal, and dynamically adjusts the coordinates of the center point by calculating the maximum and minimum values ​​of the signal in real time, wherein the coordinates of the center point are calculated by the average value of the current maximum and minimum values.

4. The adaptive calibration system based on the 3D rocker sensor to digital quantity center point according to claim 1 is characterized in that: The data preprocessing layer dynamically adjusts the maximum value and the minimum value according to the signal range of the joystick, updates the maximum value if the current sampling value is greater than the maximum value, and updates the minimum value if the current sampling value is less than the minimum value.

5. The adaptive calibration system based on the 3D rocker sensor to digital quantity center point according to claim 1 is characterized in that: The signal conversion layer calculates the offset direction and angle according to the signal offset of the joystick, wherein the offset direction is determined by the offset of the current signal value relative to the center point, and the offset angle is calculated by the proportional relationship of the offset.

6. The adaptive calibration system based on the 3D rocker sensor to digital quantity center point according to claim 1 is characterized in that: The signal conversion layer maps the offset of the signal to a standardized range and converts the standardized signal into integer data to adapt to the data format of the control system.

7. The adaptive calibration system based on the 3D rocker sensor to digital quantity center point according to claim 1 is characterized in that: The signal output layer performs smoothing processing on the converted signal, and generates a smoothed signal by averaging a plurality of continuous signal values ​​by setting a sliding window.

8. The adaptive calibration system based on the 3D rocker sensor to digital quantity center point according to claim 1 is characterized in that: The signal output layer performs signal compensation according to action recognition, and when it is determined that the change amplitude of adjacent signal values ​​is less than a set threshold, the current signal value is regarded as a static signal and compensation is performed.

9. The adaptive calibration system based on the 3D rocker sensor to digital quantity center point according to claim 1, characterized in that: The dynamic correction layer determines whether the center point needs to be recalibrated according to the radius change of the joystick signal and the size of the signal change within the sampling interval. When the signal radius decreases and the change is less than the set threshold, the center point correction is triggered.

10. The adaptive calibration system based on the 3D rocker sensor to digital quantity center point according to claim 1, characterized in that: The dynamic correction layer updates the position of the center point by performing weighted average calculation on the sampled values ​​of the joystick signal within a certain period of time, so that the center point can adapt to the signal change state of the joystick in real time.

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