Error compensation method for scatter dot DTOF chip

Abstract

The present application relates to the technical field of DTOF chip error compensation. Specifically relates to a kind of scattered point DTOF chip error compensation method, its method includes obtaining the N first depth value and N first histogram of each scattered point, the first rising edge width of highest wave crest is calculated, the first preset distance is obtained according to first preset depth value, to calculate the first error value between first depth value and first preset depth value, to obtain the N first error value and N first rising edge width of each scattered point, the N first error value and N first rising edge width of each scattered point are input into mathematical model, generate a fitting formula, calculate the error compensation coefficient of each scattered point, the error compensation coefficient of each scattered point and the width of second rising edge are input into fitting formula, obtain the second error value of each scattered point at current distance, second error value is added to second depth value, obtain final measurement depth.The present application has the effect of improving overall ranging performance.

Description

Technical Field

[0001] This invention relates to the technical field of DTOF chip error compensation, and in particular to a method for error compensation of scattered DTOF chips. Background Technology

[0002] With the rapid development of laser ranging technology, Direct Time-of-Flight (DTOF) technology has been widely used in many applications due to its high accuracy and fast response capabilities, such as robot navigation, autonomous driving, 3D reconstruction, and industrial measurement. DTOF technology calculates the distance to an object by emitting a light pulse and measuring the time difference between emission and reception. This method not only improves the accuracy and speed of ranging but also expands its application scenarios. However, traditional methods struggle to adapt to various measurement environments simultaneously, leading to insufficient ranging accuracy. Specifically, variations in signal strength cause deviations in measurement time, especially noticeable in close-range measurements. Therefore, existing technologies often require manual adjustments or complex calibration processes when dealing with varying measurement conditions. This not only increases system complexity and implementation costs but also limits reliability and flexibility in practical applications. Summary of the Invention

[0003] To improve overall ranging performance, this application provides a method for error compensation of scattered DTOF chips.

[0004] The above-mentioned objective of this application is achieved through the following technical solution:

[0005] A method for error compensation of a scattered DTOF chip includes:

[0006] At N different preset distances, obtain N first depth values ​​and N first histograms for each scatter point;

[0007] For each of the scattered points, the first rising edge width of the highest peak is calculated based on a first histogram, and a first preset depth value is obtained based on a first preset distance. Then, a first error value between the first depth value and the first preset depth value is calculated, thereby obtaining the N first error values ​​and the N first rising edge widths for each scattered point.

[0008] The N first error values ​​and N first rising edge widths of each scatter point are input into the mathematical model to generate a fitting formula. The error compensation coefficient of each scatter point is calculated through the fitting formula and stored in the chip.

[0009] During real-time ranging, a second histogram of each scatter point is acquired, and the second rising edge width and second depth value of the highest peak are determined based on the second histogram.

[0010] The error compensation coefficient of each scatter point and the width of the second rising edge are input into the fitting formula to obtain the second error value of each scatter point at the current distance;

[0011] The second error value is added to the second depth value to obtain the final measured depth.

[0012] By employing the above technical solution, the error compensation coefficient for each scatter point can be obtained by fitting the depth error value and the rising edge width of the highest peak in the histogram. This effectively corrects errors caused by signal waveform distortion or environmental changes during ranging. By combining the error compensation coefficient with real-time measurement data, the system can accurately correct the depth value of each scatter point and achieve high-precision measurement, significantly improving ranging accuracy and system stability. It maintains excellent performance, especially when facing different ranging distances and environmental changes, ensuring the accuracy of the measurement results. Furthermore, the error compensation coefficient storage method in this solution gives the system good adaptability, enabling automatic adjustments for different ranging conditions, improving the system's robustness and adaptability, and reducing the need for manual adjustments.

[0013] In a preferred embodiment of this application, the step of obtaining N first depth values ​​and N first histograms for each scatter point at N different preset distances includes:

[0014] At a preset distance, obtain a first histogram for each of the scattered points;

[0015] Based on the first histogram, the highest peak is obtained, and based on the highest peak, a first depth value is obtained;

[0016] After obtaining the first depth value, the preset distance is changed to obtain the N first depth values ​​and the N first histograms for each scatter point.

[0017] By adopting the above technical solution, depth information of each scattered point can be effectively obtained at multiple preset distances, and the depth value of each scattered point can be obtained through histogram analysis. First, the first histogram of each scattered point is obtained at a preset distance, and the corresponding first depth value is calculated based on the highest peak value of the first histogram, thereby achieving preliminary depth measurement. As the preset distance changes, N different depth values ​​and N corresponding first histograms are obtained.

[0018] In a preferred embodiment of this application, the first rising edge width and the second rising edge width include:

[0019] The first rising edge width is obtained by calculating the time bin difference between the highest point of the highest peak in the first histogram and the starting point of the highest peak;

[0020] The second rising edge width is obtained by calculating the time bin difference between the highest point of the highest peak and the starting point of the highest peak in the second histogram.

[0021] By employing the above technical solution, the rising edge width of each scatter point in the first and second histograms can be accurately calculated. During the measurement process, the system first analyzes the first histogram to find the highest peak and determines the first rising edge width by calculating the time bin difference between the highest point and the peak's starting point. Subsequently, a similar calculation is performed based on the second histogram to obtain the second rising edge width.

[0022] In a preferred embodiment of this application: the first depth value and the second depth value include:

[0023] The first depth value is the first time bin corresponding to the highest point of the highest peak in the first histogram;

[0024] The second depth value is the second time box corresponding to the highest point of the highest peak in the second histogram.

[0025] By employing the above technical solution, the depth value of each scatter point can be accurately calculated based on the highest point of the highest peak in both the first and second histograms. When processing the first histogram, the highest peak of the signal is first located, and the corresponding time box position is found. This time box is the first depth value, representing the depth information of the scatter point at a specific distance. Subsequently, for the second histogram, the system similarly locates the highest point of the highest peak and determines the corresponding time box. This time box is the second depth value, representing the actual depth during the measurement process.

[0026] In a preferred embodiment of this application, the mathematical model includes a linear mathematical model.

[0027] By adopting the above technical solution, the complex data fitting process can be simplified using a linear mathematical model, making the calculation of error compensation coefficients more efficient and accurate. In this solution, the linear model effectively expresses the error characteristics of the scatter plot depth values ​​by determining the linear relationship between the error and the rising edge width.

[0028] In a preferred embodiment of this application, the fitting formula includes:

[0029] The fitting formula is y = a·x + b, where y is the error value, x is the rising edge width of the highest peak, and a and b are the error compensation coefficients.

[0030] By adopting the above technical solution, the relationship between the error value y and the peak rise width x in the fitting formula is determined by coefficients a and b. These coefficients are obtained by fitting historical data, ensuring the accuracy and consistency of the error compensation coefficients.

[0031] In a preferred embodiment of this application, the N different preset distances further include: N-1 different preset distances under the assumed distance as short distances; and 1 preset distance outside the assumed distance as long distances.

[0032] By adopting the above technical solution, N-1 preset distances within the assumed range are considered as near distances. These distances are relatively close to the target object and can usually provide more accurate measurement results. Far distances, on the other hand, are outside the assumed range and are usually more affected by environmental factors, thus requiring special processing methods. By distinguishing between near and far distances, different compensation strategies and error models can be selected according to different distance ranges, thereby improving the system's adaptability to different ranging scenarios.

[0033] In a preferred embodiment of this application, the long-distance condition includes: selecting, at the long distance, scatter points in the scatter array that meet the preset scatter point conditions as the center scatter points, and the remaining scatter points as edge scatter points.

[0034] By adopting the above technical solution, at long distances, due to the considerable distance, the scattered points at the upper edge of the scattered point array will not receive the echo signal from the reflector. Therefore, it is necessary to select scattered points with high signal quality and measurement accuracy through preset scattered point conditions. The methods for error compensation coefficients of the center scattered points and the edge scattered points are slightly different and need to be distinguished.

[0035] In a preferred embodiment of this application, the edge scatter points include: for the edge scatter points, firstly removing the first error value and the first rising edge width at the far distance, then inputting N-1 of the first error values ​​and N-1 of the first rising edge widths at the near distance into the mathematical model to generate a fitting formula, and calculating the error compensation coefficient of the edge scatter points through the fitting formula.

[0036] By employing the above technical solution, for edge scattered points, the first error value and the first rising edge width from the long distance are removed to avoid the influence of errors caused by noise or interference in the long-distance measurement data on the compensation process. Next, multiple error values ​​and rising edge width data of the edge scattered points at close range are input into the mathematical model to re-estimate their error compensation coefficients. Through this process, the mathematical model can fit the effective data at close range, generating a new fitting formula. This formula can adjust the error compensation coefficients according to the actual situation, thereby providing more accurate correction values ​​for the edge scattered points during the compensation process.

[0037] In a preferred embodiment of this application, the method for selecting the center scatter point includes: selecting a 6×6 area as the scatter point area to be measured, with the current scatter point as the center; obtaining the third depth values ​​of m scatter points within the scatter point area to be measured; calculating m differences between the third depth values ​​of the m scatter points and the depth values ​​corresponding to the actual distance; counting the number of scatter points with the m differences less than 40mm; if the number of scatter points is greater than 6, then the current scatter point is considered the center scatter point.

[0038] By adopting the above technical solution, central scattered points can be effectively screened during the measurement process, further improving measurement accuracy. First, a 6×6 area is selected as the area to be measured, centered on the current scattered point. This allows for the collection of more data within a smaller range, enabling a more accurate evaluation of the validity of the current scattered point. Next, by obtaining the third depth values ​​of m scattered points within this area, the specific measurement data for the scattered points in this area can be obtained. Subsequently, the differences between these third depth values ​​and the depth values ​​corresponding to the true distance are calculated, resulting in m differences used to evaluate the measurement error of each scattered point. Finally, by counting the number of scattered points with differences less than 40mm, if the number of central scattered points meeting this condition exceeds 6, the current scattered point is considered a central scattered point, thus ensuring that the screened scattered points meet the requirements of high-precision measurement.

[0039] This application also provides a scatter-point DTOF chip, including an transmitter, a scatter array, a histogram module, and a controller, wherein the controller performs the method as described in any of the preceding claims.

[0040] This application also provides an electronic device, including the scatter point DTOF chip described above.

[0041] In summary, this application includes at least one of the following beneficial technical effects:

[0042] 1. By adopting the above technical solution, the error compensation coefficient for each scatter point can be obtained by fitting the depth error value and the rising edge width of the highest peak of the histogram. This effectively corrects errors caused by signal waveform distortion or environmental changes during the ranging process. By combining the error compensation coefficient with real-time measurement data, the system can accurately correct the depth value of each scatter point and achieve high-precision measurement, significantly improving ranging accuracy and system stability. Especially when facing different ranging distances and environmental changes, it maintains excellent performance and ensures the accuracy of the measurement results. Furthermore, the error compensation coefficient storage method in the solution gives the system good adaptability, enabling it to automatically adjust for different ranging conditions, improving the system's robustness and adaptability, and reducing the need for manual adjustment.

[0043] 2. At long distances, due to the greater distance, environmental factors and noise may have a greater impact, and some scattered points may not receive the reflector signal. Therefore, it is necessary to distinguish between center scattered points and edge scattered points. The linear fitting formula for edge scattered points is slightly different. Center scattered points that meet the conditions will be used for subsequent error compensation calculations, while scattered points that do not meet the conditions are identified as edge scattered points. The calculation method for the error compensation coefficient of edge scattered points is slightly different from that of center scattered points. However, during the ranging process, edge scattered points also need to output depth values, and depth error compensation is required.

[0044] 3. The system effectively filters out central scattered points during the measurement process, further improving measurement accuracy. First, a 6×6 area is selected as the area to be measured, centered on the current scattered point. This allows for the collection of more data within a smaller range, enabling a more accurate evaluation of the current scattered point's validity. Next, by obtaining the third depth values ​​of m scattered points within this area, the specific measurement data for those points can be obtained. Subsequently, the differences between these third depth values ​​and the depth values ​​corresponding to the actual distances are calculated, yielding m differences used to evaluate the measurement error of each scattered point. Finally, by counting the number of scattered points with differences less than 40mm, if the number of central scattered points meeting this condition exceeds six, the current scattered point is considered a central scattered point, thus ensuring that the selected scattered points meet the requirements for high-precision measurement. Attached Figure Description

[0045] Figure 1 This is a flowchart of a scattered DTOF chip error compensation method in one embodiment of this application;

[0046] Figure 2 This is a graph showing the relationship between the rising edge width of the scatter points at different distances and the error value in one embodiment of this application;

[0047] Figure 3 This is a histogram of any scattered points in one embodiment of this application;

[0048] Figure 4 This is a schematic diagram of a scatter array including a center scatter point and edge scatter points in one embodiment of this application;

[0049] Figure 5 This is a graph showing the relationship between the rising edge width and error value of edge points at different distances in one embodiment of this application;

[0050] Figure 6 This is a block diagram of a scatter-point DTOF chip in one embodiment of this application. Detailed Implementation

[0051] The present application will be further described in detail below with reference to the accompanying drawings.

[0052] In one embodiment, such as Figure 1 As shown, this application discloses a scattered DTOF chip error compensation method, which specifically includes the following steps:

[0053] S10: At N different preset distances, obtain N first depth values ​​and N first histograms for each scatter point.

[0054] Specifically, at different preset distances, multiple preset distances (e.g., 300mm, 500mm, 800mm, etc.) are first set, each corresponding to a fixed measurement range. Next, using the principle of laser ranging, a laser sensor emits pulse signals and receives the signals reflected from the object's surface. For each point, the relationship between the intensity of the received signal and time is converted into a histogram, recording the reflected signal intensity at different time points. The depth of each point is obtained from the histogram. (See [link to documentation]). Figure 3 .

[0055] S20: For each scatter point, calculate the first rising edge width of the highest peak according to a first histogram, obtain the first preset depth value according to the first preset distance, and then calculate the first error value between the first depth value and the first preset depth value, thereby obtaining N first error values ​​and N first rising edge widths for each scatter point.

[0056] Specifically, when analyzing the first histogram, first identify the peaks in the histogram to locate the starting and maximum points of the signal peaks. Then, calculate the rising edge width of the peaks, which is the time difference between the time point when the signal begins to rise and the time point when it reaches its maximum value. See [link to relevant documentation]. Figure 3This width can be obtained by analyzing sampling points on the time axis to determine the rise speed and shape of the peak. Next, based on a preset distance, using the relationship distance = speed of light * time, a first preset depth value at that distance is calculated and compared with the actual measured first depth value. The difference between the two is calculated, and this difference is the first error value. This error value reflects the depth measurement error caused by equipment deviation, environmental influences, etc. Through multiple calculations at different preset distances, N first error values ​​and N first rise widths of the scatter plot at different preset distances are finally obtained.

[0057] S30: Input the N first error values ​​and N first rising edge widths of each scatter point into the mathematical model to generate a fitting formula. Calculate the error compensation coefficient for each scatter point using the fitting formula and save the error compensation coefficient in the chip.

[0058] Specifically, the error value and rising edge width of each scatter point are used as input data and fed into a preset mathematical model. This model can be a linear regression model or a multinomial fitting model. The most suitable model is selected based on the distribution and relationship of the data. See [link to relevant documentation]. Figure 2 The purpose of the fitting model is to derive a functional relationship between the known error value and the rise time width, representing the dependence of the error on the rise time width. Through the fitting process, a fitting formula is generated to calculate the error compensation coefficients. Finally, the obtained error compensation coefficients are stored in the chip's memory, ensuring that the error compensation value for each point can be quickly retrieved in subsequent measurements to guarantee real-time measurement accuracy.

[0059] S40: During real-time ranging, acquire the second histogram of each scatter point, and determine the second rising edge width and second depth value of the highest peak based on the second histogram.

[0060] Specifically, during real-time measurement, a new histogram, called the second histogram, is generated each time a laser pulse is emitted and reflected back. This histogram records the relationship between the intensity of the new reflected signal and time. By analyzing this histogram, peaks are identified, and the starting and maximum points of these peaks are located. Next, the second rising edge width of the peak is calculated, which is the time difference from the starting point of the peak to the maximum point. This width is calculated by detecting the time difference between the initial rise of the signal and the time it takes to reach its maximum value, thus determining the second rising edge width. Simultaneously, based on the time information and using the relationship between the speed of light and propagation time, a second depth value is calculated. This second depth value refers to the time depth from the laser signal's emission to its arrival at the target object and its reflection back from the target object.

[0061] S50: Input the error compensation coefficient and the width of the second rising edge of each scatter point into the fitting formula to obtain the second error value of each scatter point at the current distance.

[0062] Specifically, first, the error compensation coefficient stored for each scatter point is read from the chip memory. This coefficient, calculated during the previous fitting process, typically exists as a constant or polynomial coefficient. Second, the peak data from the second histogram during real-time ranging is acquired. The time bin corresponding to the highest peak is the second depth value. The rising edge width of the second peak, i.e., the time difference from the initial rising point to the peak point, is calculated. Then, the error compensation coefficient and the second rising edge width are input into the established fitting formula. According to the formula, the second error value for each scatter point at the current distance is calculated. This calculation process relies on the previously defined fitting relationship, where the fitting coefficients are optimized based on test data from multiple scatter points. Therefore, the input error compensation coefficient and the second rising edge width are calculated using the formula to ultimately obtain the error value for each scatter point at the current distance. See [link to relevant documentation]. Figure 2 .

[0063] S60: Add the second error value to the second depth value to obtain the final measured depth.

[0064] Specifically, the second error value measured in real time is added to the second depth value to obtain the final measured depth. This error value is calculated using a fitting formula; it represents the error caused by equipment deviation or environmental changes and needs to be added to the actual measured depth value for correction. Through addition, the error is compensated for in the actual depth value, resulting in a more accurate measurement. This final measured depth represents the actual distance between the object and the ranging device after error compensation.

[0065] In one embodiment, at N different preset distances, N first depth values ​​and N first histograms are obtained for each scatter point, including:

[0066] S101: At a preset distance, obtain a first histogram for each scatter point.

[0067] Specifically, first, a preset distance is determined, for example, setting a distance point (e.g., 300mm). Then, a sensor measures scattered points within this distance range. The measurement data corresponding to each scattered point generates a histogram, which represents the distribution of the number of photons reflected back by the laser signal at different depths (times). By sampling the intensity of the reflected signal, a histogram corresponding to that scattered point is plotted with depth as the x-axis and the intensity of the reflected signal as the y-axis. See [link to relevant documentation]. Figure 3 As can be seen, each scatter point generates a corresponding histogram at a preset distance.

[0068] S102: Based on a first histogram, obtain the highest peak, and based on the highest peak, obtain a first depth value.

[0069] Specifically, waveform data of the signal is extracted from the first histogram. By analyzing the signal strength values ​​of each time bin in the histogram, the highest point of signal strength, i.e., the "peak," is found. Then, the depth location of this highest point is determined, which usually corresponds to the strongest point of reflected signal. Based on the depth values ​​of the histogram's horizontal axis, the depth value of the highest peak is mapped to a distance calculation formula to calculate the depth value corresponding to the current scatter point. For example, the relationship between the speed of light and time (…) Where c is the speed of light, the distance at this moment is calculated based on this depth value, thus obtaining the first depth value of the scatter point. This depth value represents the measured depth of the scatter point at a preset distance.

[0070] S103: After obtaining one first depth value, change the preset distance to obtain N first depth values ​​and N first histograms for each scatter point.

[0071] Specifically, after obtaining the first depth value, the preset distance of the measurement system is adjusted according to the set measurement strategy. For example, if the initial preset is 300mm, it is adjusted to different measurement distances such as 500mm, 800mm, and 1000mm. Each time the preset distance is adjusted, the sensor remeasures and generates new scatter data, thus obtaining a new histogram. For each new distance, a new histogram is acquired and the corresponding depth value is calculated. Each acquired histogram and calculated depth value are stored in the chip's storage unit, with the corresponding distance as a condition, ultimately resulting in depth values ​​and histograms for multiple scatter points corresponding to multiple preset distances.

[0072] In one embodiment, in step S20, the first rising edge width and the second rising edge width include:

[0073] The first rising edge width is obtained by calculating the time bin difference between the highest point of the highest peak and the starting point of the highest peak in the first histogram.

[0074] Specifically, first, the data from the first histogram is extracted. This histogram is obtained by sampling the time distribution of the reflected signal, where the horizontal axis represents the time bin (usually a time bin, indicating the measurement period) and the vertical axis represents the signal strength. From this histogram, the highest peak, i.e., the point with the strongest signal strength, is identified. Then, the location of the highest point of the peak is determined, corresponding to a specific time point within the time bin. Next, the starting point of the peak is determined. The peak starting point refers to the earliest moment when the signal strength begins to rise from zero, i.e., the point where the signal strength begins to increase and reaches a significant increase. The time difference between the starting point and the highest point is calculated, i.e., the time bin difference. This difference represents the time taken for the peak to reach its maximum value. This difference is the first rise edge width, reflecting the rise time of the signal peak. The first rise edge width is obtained through this time bin difference.

[0075] The second rising edge width is obtained by calculating the time bin difference between the highest point of the highest peak and the starting point of the highest peak in the second histogram.

[0076] Specifically, first, the data from the second histogram is extracted. This histogram is obtained by sampling the reflected signal from the second measurement, with the horizontal axis representing time bins and the vertical axis representing signal strength. The peak with the highest signal strength, i.e., the point of maximum signal value, is identified from this second histogram. Then, the highest point of this peak is determined, which is the moment when the signal strength in the second histogram is at its maximum. Next, the starting point of the peak is found; this starting point is the moment when the signal strength begins to rise significantly, i.e., the position where the peak signal gradually increases from low intensity. The time difference from the starting point to the highest point is calculated; this time difference is the second rise edge width, representing the time taken for the signal to rise from its initial rise to reach maximum intensity. This time bin difference is the second rise edge width.

[0077] In one embodiment, the first depth value and the second depth value include: the first depth value is the first timebox corresponding to the highest point of the highest peak in the first histogram.

[0078] Specifically, first, the data from the first histogram is acquired. This histogram is obtained by sampling the reflected signal, with the horizontal axis representing the time bin and the vertical axis representing the signal intensity. Within this histogram, the point of highest signal intensity is determined, i.e., the location of the peak. The time bin corresponding to this highest point is the first depth value, representing the time scale at which the reflected signal reaches its maximum intensity. For example, if the maximum signal intensity in the first histogram occurs at time bin 500, then the depth value corresponding to this time bin is the first depth value. This depth value represents the time it takes for the laser pulse to reflect back to the target during measurement, reflecting the distance between the target and the sensor. Based on this time bin position, the corresponding target depth value can be calculated.

[0079] The second depth value is the second time box corresponding to the highest point of the highest peak in the second histogram.

[0080] Specifically, the second histogram data is obtained by sampling the reflected signal from the second measurement. The horizontal axis represents the time bin, and the vertical axis represents the signal intensity. The highest point of signal intensity, i.e., the highest peak position, is found in the second histogram. The time bin corresponding to this highest point is the second depth value, representing the time scale at which the maximum intensity of the reflected signal occurred. For example, if the maximum signal intensity in the second histogram occurs at time bin 800, then the time value corresponding to this time bin is the second depth value. By calculating the relationship between the time bin position and the speed of light, the actual distance between the reflecting target and the measuring device can be obtained.

[0081] In one embodiment, in step S30, the mathematical model is a linear mathematical model.

[0082] Specifically, the basic objective of error compensation is defined as calculating the error compensation coefficient using known measurement errors and some measurement parameters (such as rise width). This objective can be achieved through a mathematical model, specifically a linear mathematical model. A linear mathematical model assumes a linear relationship between the error compensation coefficient and the input parameters. It is assumed that the relationship between the error compensation coefficient (y) and the rise width (x) can be represented by a simple linear equation, for example: y = a·x + b, where y represents the error compensation coefficient, x represents the rise width, and a and b are constant coefficients in the linear model. a represents the slope, indicating the strength of the relationship between the error and the rise width, and b represents the bias term, indicating the error value when the rise width is zero. To determine these coefficients (a and b), scatter data measured at different preset distances during the calibration phase can be used for fitting. The optimal coefficient values ​​are calculated using the least squares method or other regression analysis methods, thus obtaining the parameters of the linear model. The basic principle of the least squares method is to obtain the best-fit curve by minimizing the sum of squares of the prediction errors, i.e., through the formula: Among them, y i Given the known error value, x i Let be the corresponding rising edge width, and N be the total number of sample points. The optimal values ​​of a and b are found by minimizing this sum of squared errors. After fitting, a linear model is obtained.

[0083] In one embodiment, in step S40, the fitting formula is y = a·x + b, where y is the error value, x is the rising edge width of the highest peak, and a and b are error compensation coefficients.

[0084] Specifically, the error value (y) is first defined as the difference between the actual depth value obtained during the measurement process and the theoretical depth value; that is, the degree to which the measured value deviates from the expected result under a specific condition. By recording the relationship between these error values ​​and the corresponding rise-edge width (x), an error compensation coefficient can be calculated for each scatter plot. The rise-edge width (x) typically refers to the time region covered by the rising segment of the highest peak in the histogram of the reflected signal, i.e., the time difference from the start of the signal rise to its maximum value. By analyzing the relationship between different rise-edge widths and error values, a suitable fitting curve can be found for each measurement scenario.

[0085] In one embodiment, the N different preset distances further include: N-1 different preset distances under the assumed distance as short distances, and 1 preset distance outside the assumed distance as long distances.

[0086] Specifically, first, an assumed distance is set as a reference point for measurement. This assumed distance can be based on common measurement distances in the normal operating environment or a standard distance preset during design, such as 1000mm. Then, several other distances close to the assumed distance are selected as proximity distances. These distances are typically slightly shorter or longer than the assumed distance, and the range can be adjusted according to the specific application and design requirements of the measurement system. For example, if the assumed distance is 1000mm, distances such as 900mm, 950mm, 1050mm, and 100mm can be selected as proximity distances. These distances are usually adjusted by adjusting the working distance setting of the measuring equipment or gradually adjusted according to the system's measurement capabilities. Ultimately, all selected proximity distances should cover the measurement area near the assumed distance. Obtaining the long distance is usually done at the hardware level by adjusting the target detection range of the sensor, or by setting the target area for that measurement distance in the software.

[0087] In one embodiment, at long distances, scatter points that meet preset scatter point conditions are selected as center scatter points, and the remaining scatter points are edge scatter points.

[0088] Specifically, in long-distance measurements, the first step is to extract all scattered data from the scattered data array. This scattered data is typically collected using laser rangefinders or related measuring equipment. Next, these scattered points are filtered according to preset criteria. These criteria may include, for example, the signal strength, reflectivity, and the error range between the depth value and the actual distance. For instance, a condition might be set requiring the signal strength of a scattered point to be greater than a certain threshold (e.g., 50%), or the error between the depth value and the theoretical depth value to be less than a certain range (e.g., 0.1 mm). Scattered points that meet these criteria are considered center scattered points. Scattered points that do not meet these criteria are usually due to weak signals, poor reflection, or large errors, and are marked as edge scattered points. Edge scattered points may receive more environmental noise at long distances. The filtering method is usually automated through algorithms, which judge and compare the data of each scattered point to ultimately determine which scattered points meet the criteria and are retained.

[0089] In one embodiment, for edge points, see [reference needed]. Figure 5 First, the first error value and the first rising edge width at long distance are removed. Then, the N-1 first error values ​​and N-1 first rising edge widths of the edge scattered points at close distance are input into the mathematical model to generate a fitting formula. The error compensation coefficient of the edge scattered points is calculated through the fitting formula.

[0090] Specifically, for each edge point, its corresponding error value (first error value) and first rising edge width are obtained during long-distance measurement. These values ​​are typically calculated from characteristic data such as signal strength and time response curves of the point. These error values ​​and rising edge widths of the edge points at long distances do not meet preset conditions, so these data need to be removed at this stage, i.e., not used in subsequent fitting processes. Removal can be achieved through simple data filtering or labeling to exclude data from error compensation calculations for these non-compliant points. Next, the error values ​​and rising edge widths of these edge points at close distances are extracted. These close distances are typically multiple distance values ​​near the assumed distance (e.g., 900mm, 950mm, 1050mm, etc.). These close-distance measurement error values ​​and rising edge widths are relatively more reliable because they usually meet preset scatter point conditions and are less affected by measurement errors and signal noise. By extracting N-1 error values ​​and N-1 rising edge widths of the edge points at close distances, a set of data is formed for calculating the fitting model. These data will serve as input, and a mathematical model, typically using polynomial or linear fitting, will generate a fitting formula. This formula aims to derive the error compensation coefficients for edge points at long distances based on the error values ​​and rising edge width. The process of generating the fitting formula usually involves: first, fitting the data to N-1 error values ​​and rising edge widths, calculating fitting coefficients (e.g., a, b, etc.), which characterize the relationship between error and rising edge width. The generated fitting formula will then be applied to the measurement data of the edge points, ultimately yielding the error compensation coefficients for the edge points.

[0091] In one embodiment, see Figure 4 Methods for selecting the center point of the scatter plot include:

[0092] S1212: Select a 6×6 area as the scatter point region to be measured, centered on the current scatter point.

[0093] Specifically, first, the current scatter point is selected as the center point in the measurement area. Then, a 6×6 area is selected around this center point, containing 6 rows and 6 columns, for a total of 36 scatter points. This area is selected by determining the coordinates of the current scatter point in a two-dimensional coordinate system and extending it by one unit in all directions, thus defining the boundary of the area.

[0094] S1213: Obtain the third depth value of m scattered points within the area to be measured.

[0095] Specifically, within a selected 6×6 area, depth sensors or measuring tools are used to measure each point. By acquiring the depth value of each point within this area, the depth information of these points during the measurement process is obtained. These depth values ​​are calculated based on the round-trip time of the reflected signal. The reflected signal is sent and received via laser or other sensing technology. The sensor measures the time of flight of the light signal and calculates the distance from each point to the target object based on the time of flight. The formula for calculating the depth value of each point is: Depth value = (Speed ​​of light × Round-trip time) / 2. The resulting depth value is the third depth value of that point.

[0096] S1214: Calculate the m differences between the third depth value of m scattered points and the depth value corresponding to the true distance.

[0097] Specifically, after obtaining the third depth value for each point within the 6×6 area, the first step is to acquire the true distance of each point at that location, i.e., the predetermined distance between these points and the true reference target. The true distance can be obtained through manual measurement or a pre-calibrated standard distance; for example, it might be obtained using the known location of the reference target and data from a known calibration instrument. Then, for each point, the error value is calculated using the formula "Error = Third Depth Value - True Distance". This process is performed once for each point within the area, yielding m difference values.

[0098] S1215: Count the number of m scatter points with a difference less than 40mm. If the number of scatter points is greater than 6, then the current scatter point is considered the center scatter point.

[0099] Specifically, for the obtained m error values, a conditional judgment method is used to filter out all scatter points with error values ​​less than 40mm. Specifically, each error value is checked one by one to determine if it meets the condition of "error value < 40mm". If the error is less than 40mm, the scatter point is considered a center point. This process is achieved by iterating through each difference value and comparing them. Finally, the number of center points that meet the condition is counted. If the number of center points is greater than 6, the current scatter point is considered a center point and meets the conditions for subsequent processing. If the number of center points is less than 6, the current scatter point does not meet the condition for a center point and needs to be excluded.

[0100] In one embodiment, this application also provides a scatter-point DTOF chip, see [link to relevant documentation]. Figure 6 It includes a transmitter, a scatter array, a histogram module, and a controller, wherein the controller performs the method as described in any of the preceding items.

[0101] A transmitter used to emit laser light;

[0102] A scattered array is used to receive laser signals reflected back from the target object;

[0103] The histogram module is used to perform histogram processing on the received signal to obtain histogram data;

[0104] The controller is used to acquire a second histogram of each scatter point during real-time ranging, and determine the second rising edge width and second depth value of the highest peak based on the second histogram; input the error compensation coefficient of each scatter point and the width of the second rising edge into the fitting formula to obtain the second error value of each scatter point at the current distance; add the second error value to the second depth value to obtain the final measured depth.

[0105] The controller is further configured to acquire N first depth values ​​and N first histograms for each scatter point at N different preset distances; for each scatter point, calculate the first rising edge width of the highest peak based on a first histogram, obtain a first preset depth value based on a first preset distance, and calculate a first error value between the first depth value and the first preset depth value, thereby obtaining the N first error values ​​and the N first rising edge widths for each scatter point; input the N first error values ​​and N first rising edge widths for each scatter point into a mathematical model to generate a fitting formula, calculate the error compensation coefficient for each scatter point through the fitting formula, and store the error compensation coefficient in the chip.

[0106] This application also provides an electronic device, including the scattered DTOF chip described above.

[0107] In summary, this application includes at least one of the following beneficial technical effects:

[0108] 1. By adopting the above technical solution, the error compensation coefficient for each scatter point can be obtained by fitting the depth error value and the rising edge width of the highest peak of the histogram. This effectively corrects errors caused by signal waveform distortion or environmental changes during the ranging process. By combining the error compensation coefficient with real-time measurement data, the system can accurately correct the depth value of each scatter point and achieve high-precision measurement, significantly improving ranging accuracy and system stability. Especially when facing different ranging distances and environmental changes, it maintains excellent performance and ensures the accuracy of the measurement results. Furthermore, the error compensation coefficient storage method in the solution gives the system good adaptability, enabling it to automatically adjust for different ranging conditions, improving the system's robustness and adaptability, and reducing the need for manual adjustment.

[0109] 2. At long distances, due to the greater distance, environmental factors and noise may have a greater impact, and some scattered points may not receive the reflector signal. Therefore, it is necessary to distinguish between center scattered points and edge scattered points. The linear fitting formula for edge scattered points is slightly different. Center scattered points that meet the conditions will be used for subsequent error compensation calculations, while scattered points that do not meet the conditions are identified as edge scattered points. The calculation method for the error compensation coefficient of edge scattered points is slightly different from that of center scattered points. However, during the ranging process, edge scattered points also need to output depth values, and depth error compensation is required.

[0110] 3. The system effectively filters out central scattered points during the measurement process, further improving measurement accuracy. First, a 6×6 area is selected as the area to be measured, centered on the current scattered point. This allows for the collection of more data within a smaller range, enabling a more accurate evaluation of the current scattered point's validity. Next, by obtaining the third depth values ​​of m scattered points within this area, the specific measurement data for those points can be obtained. Subsequently, the differences between these third depth values ​​and the depth values ​​corresponding to the actual distances are calculated, yielding m differences used to evaluate the measurement error of each scattered point. Finally, by counting the number of scattered points with differences less than 40mm, if the number of central scattered points meeting this condition exceeds six, the current scattered point is considered a central scattered point, thus ensuring that the selected scattered points meet the requirements for high-precision measurement.

[0111] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for error compensation in a scattered DTOF chip, characterized in that, include: At N different preset distances, obtain N first depth values ​​and N first histograms for each scatter point; For each of the scattered points, the first rising edge width of the highest peak is calculated based on a first histogram, and a first preset depth value is obtained based on a first preset distance. Then, a first error value between the first depth value and the first preset depth value is calculated, thereby obtaining the N first error values ​​and the N first rising edge widths for each scattered point. The N first error values ​​and N first rising edge widths of each scatter point are input into the mathematical model to generate a fitting formula. The error compensation coefficient of each scatter point is calculated through the fitting formula and stored in the chip. During real-time ranging, a second histogram of each scatter point is acquired, and the second rising edge width and second depth value of the highest peak are determined based on the second histogram. The error compensation coefficient of each scatter point and the width of the second rising edge are input into the fitting formula to obtain the second error value of each scatter point at the current distance; The second error value is added to the second depth value to obtain the final measured depth.

2. The scattered point DTOF chip error compensation method according to claim 1, characterized in that, The step of obtaining N first depth values ​​and N first histograms for each scatter point at N different preset distances includes: At a preset distance, obtain a first histogram for each of the scattered points; Based on the first histogram, the highest peak is obtained, and based on the highest peak, a first depth value is obtained; After obtaining the first depth value, the preset distance is changed to obtain the N first depth values ​​and the N first histograms for each scatter point.

3. The scattered point DTOF chip error compensation method according to claim 1, characterized in that, The first rising edge width and the second rising edge width include: The first rising edge width is obtained by calculating the time bin difference between the highest point of the highest peak in the first histogram and the starting point of the highest peak; The second rising edge width is obtained by calculating the time bin difference between the highest point of the highest peak and the starting point of the highest peak in the second histogram.

4. The scattered point DTOF chip error compensation method according to claim 3, characterized in that, The first depth value and the second depth value include: The first depth value is the first time bin corresponding to the highest point of the highest peak in the first histogram; The second depth value is the second time box corresponding to the highest point of the highest peak in the second histogram.

5. The scattered point DTOF chip error compensation method according to claim 1, characterized in that, The mathematical model includes: The mathematical model is a linear mathematical model.

6. The scattered point DTOF chip error compensation method according to claim 1, characterized in that, The fitting formula includes: The fitting formula is as follows: Wherein, y is the error value, x is the rising edge width of the highest peak, and a and b are the error compensation coefficients.

7. The scattered point DTOF chip error compensation method according to claim 1, characterized in that, The N different preset distances also include: N-1 different preset distances under the assumed distance are considered as close distances; A preset distance outside the assumed distance is the long distance.

8. The scattered point DTOF chip error compensation method according to claim 7, characterized in that, At the aforementioned long distance, including: At the long distance, the scattered points that meet the preset scattered point conditions in the scattered point array are selected as the center scattered points, and the remaining scattered points are the edge scattered points.

9. The scattered point DTOF chip error compensation method according to claim 8, characterized in that, The edge points include: For the edge scattered points, firstly remove the first error value and the first rising edge width at the far distance, then input the N-1 first error values ​​and N-1 first rising edge widths of the edge scattered points at the near distance into the mathematical model to generate a fitting formula, and calculate the error compensation coefficient of the edge scattered points through the fitting formula.

10. The scattered point DTOF chip error compensation method according to claim 8, characterized in that, The method for selecting the center points includes: Centered on the current scatter points, select a 6×6 area as the scatter point area to be measured; Obtain the third depth value of m scattered points within the area to be measured; Calculate the m differences between the third depth value of the m scattered points and the depth value corresponding to the true distance; Count the number of scattered points with a difference of less than 40mm. If the number of scattered points is greater than 6, then the current scattered point is considered to be the center scattered point.

11. A scattered point DTOF chip, characterized in that, It includes a transmitter, a scatter array, a histogram module, and a controller, wherein the controller performs the method as described in any one of claims 1-10.

12. An electronic device, characterized in that, Including the scatter point DTOF chip as described in claim 11.

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