Calibration correction method and test method of single-point DTOF laser radar

Abstract

The invention discloses a calibration correction method and a test method of a single-point DTOF laser radar, and the correction method comprises the steps: carrying out the temperature drift correction of a collected conventional channel distance value TOF 1 through a mapping relation between original TOF data and original temperature data TS by employing the single-point DTOF laser radar; and carrying out one-time global fitting calibration correction and two-time segmented calibration linear correction on acquired data of a black target, a white target, a high-reflection target and the like under different calibration point distances. The calibration correction method and the test method of the single-point DTOF laser radar provided by the invention can be applied to the single-point DTOF laser radar, and effectively improve ranging result drift caused by temperature drift; the method can overcome the problems that SPAD saturation and black target cannot cover a lower reflectivity scene in different high reflectivity scenes, and improves the ranging error caused by different pileup degrees in different reflectivity scenes. Distance measurement errors caused by different light spot energy distribution at different distances can be improved.

Description

Technical Field

[0001] The present invention belongs to the field of radar calibration and correction, and particularly relates to a calibration and correction method and a testing method for a single-point DTOF lidar. Background Art

[0002] Currently, single-point DTOF lidars are increasingly widely used in various scenarios, including but not limited to commercial scenarios, home scenarios, outdoor environments, augmented reality technologies, and smart home and security monitoring fields. However, in the working scenarios of single-point DTOF lidars, the reflectivities and distances of the detected targets vary. The degree of pileup phenomenon generated by targets with different reflectivities at the radar receiving end also differs. Especially in scenarios with higher reflectivities, SPAD is prone to saturation, making it difficult to distinguish different high-reflectivity scenarios. In low-reflectivity scenarios, there will be scenarios where the reflectivity is lower than that of the black target used for calibration, and conventional calibration schemes cannot cover such scenarios. Moreover, due to the different energy distributions of the emission spots of single-point DTOF lidars at different distances, the degree of pileup phenomenon generated by targets at different distances at the radar receiving end also varies. Therefore, for targets with different distances and different reflectivities, the ranging errors generated by single-point DTOF lidars are different, which has an adverse impact on the correct ranging values output by the radar.

[0003] Based on the defects of the existing technology, a new calibration and correction method for single-point DTOF lidars needs to be designed. Summary of the Invention

[0004] The purpose of the present invention is to provide a calibration and correction method and a testing method for a single-point DTOF lidar that can improve the ranging result drift caused by temperature drift.

[0005] The present invention provides a calibration and correction method for a single-point DTOF lidar, including the following steps:

[0006] S1. Use a single-point DTOF lidar to collect the original TOF data and the original temperature data TS of a black target and a white target at a fixed distance and different temperatures.

[0007] S2. Use a single-point DTOF lidar to collect the conventional channel distance values TOF1, peak values Peak1, decay channel peak values Peak2, and measured temperature data TS1 of the black target, white target, and high-reflectivity target at different calibration point distances under the conditions of full open and non-full open of the photosensitive surface pixels respectively.

[0008] S3. Perform temperature drift correction on the collected conventional channel distance value TOF1 through the mapping relationship between the original TOF data and the original temperature data TS.

[0009] S4. On the basis of temperature drift correction, perform the first global fitting calibration correction on the error values Bias of the peak values Peak1 of the black target and white target and the conventional channel distance value TOF1 at different calibration point distances.

[0010] S5. On the basis of the first global fitting calibration correction, perform the first piecewise calibration linear correction on the error values Bias of the peak values Peak1 of the black target and white target and the conventional channel distance value TOF1 at different calibration point distances. And then perform the second piecewise calibration linear correction on the error values Bias of the peak values Peak2 of the attenuation channels of the black target, white target, and high-reflectivity target and the conventional channel distance value TOF1 at different calibration point distances to complete the calibration of the data.

[0011] As a further improvement of the present invention, the photosensitive surface is configured as a macro-pixel array of N*N, where the macro-pixels in several regions are combined into attenuation channels, and the macro-pixels in the remaining regions are combined into conventional channels.

[0012] As a further improvement of the present invention, the step S2 includes the following steps.

[0013] S21. Under the condition that all the photosensitive surface pixels are fully open, collect the conventional channel distance value TOF1, peak value Peak1, attenuation channel peak value Peak2, and measured temperature data TS1 of the single-point DTOF lidar facing the black target, white target, and high-reflectivity target at different calibration distances.

[0014] S22. Change the photosensitive surface to a configuration with some pixels open, and collect the conventional channel distance value TOF1, peak value Peak1, attenuation channel peak value Peak2, and measured temperature data TS1 of the single-point DTOF lidar facing the black target -1, white target, and high-reflectivity target at different calibration distances.

[0015] As a further improvement of the present invention, the temperature drift correction includes confirming the binomial coefficient p1 and the first-order coefficient p2 through the mapping relationship between the original TOF data and the original temperature data TS, and then performing temperature drift correction on the conventional channel distance value TOF1 and the measured temperature data TS1 collected in S22 and S23. The formula is as follows.

[0016]

[0017] TOF TS = TOF - Cal_temp.

[0018] As a further improvement of the present invention, the step S4 includes the following steps.

[0019] S41. On the basis of temperature drift correction, for the conventional channel distance value TOF measured at each calibration point distance. TSSubtract the true distance value of the corresponding calibration point to obtain the error value Bias, perform polynomial fitting using a quadratic function, and record the maximum value maxPeak1 and the minimum value minPeak1 of the black target and the white target at different non-calibration point distances;

[0020] S42. Limit the peak Peak1 at all different calibration point distances within the range of maxPeak1 and minPeak1, and then subtract the correction value corresponding to Peak1 in the quadratic function curve from the TOF1 value of the normal channel distance at all different calibration point distances to complete the first global fitting calibration correction.

[0021] Cal_first = a * Peak1 2 + b * Peak1 + c

[0022] TOF1 = TOF TS - Cal_first.

[0023] As a further improvement of the present invention, the first segmented calibration linear correction includes the following steps:

[0024] S51. On the basis of the first global fitting calibration correction, fit the mapping relationship between the Bias and the peak Peak1 of the black target - 1, the black target, and the white target at each different calibration point distance, and take the average value of the peak Peak1 of the black target as the correction threshold th1. Record the maximum and minimum values of all the peak Peak1 of the black target - 1, the black target, and the white target at each different calibration point distance, and the mean value MT of all the TOF1 values of the black target - 1, the black target, and the white target at different distances at each different calibration point distance. Denote the mean value of all the TOF1 values of the i-th calibration point as MT i , to complete the first segmented calibration;

[0025] S52. Calculate the TOF results of the first global fitting correction at the front and rear two calibration points MT i and MT i+1 respectively. After limiting Peak1 within the maximum and minimum values, the corresponding error values Cal i and Cal i+1 , and subtract the weighted sum of the correction values corresponding to Peak1 in the piecewise functions of the front and rear two calibration points from the TOF1 values of all the calibration data through the following formula:

[0026]

[0027] TOF2 = TOF1 - Cal_second,

[0028] If the TOF1 value is less than or equal to the mean value MT1 of the first calibration point or greater than or equal to the last calibration point MTend , then set the correction value Cal_second at this point equal to Cal1 or Cal end .

[0029] As a further improvement of the present invention, the second piecewise calibration linear correction includes the following steps

[0030] S53. Based on TOF2 of the first global fitting calibration correction, fit the mapping relationship between the Bias of the black target, white target, and high-reflectivity target and the peak Peak2 of the attenuation channel at each different calibrated point distance, and use the average value of the peak Peak2 of the attenuation channel of the white target as the correction threshold th2. Record the maximum and minimum values of all peak Peak2 of the black target, white target, and high-reflectivity target at each different calibrated point distance, and the mean value MT of all TOF2 values of the black target, white target, and high-reflectivity target at different distances at each different calibrated point distance. Denote the mean value of all TOF2 values of the j-th calibrated point as MT j , to complete the second piecewise calibration;

[0031] S54. Calculate the TOF results after the first piecewise fitting correction at the front and rear two calibrated points MT j and MT j+1 . After the peak Peak2 of its attenuation channel is restricted within the maximum and minimum values, the corresponding error values Cal j and Cal j+1 , and subtract the weighted sum of the correction values corresponding to Peak2 at the front and rear two calibrated points of all calibration data from the TOF2 value of all calibration data through the following formula

[0032]

[0033] TOF3 = TOF2 - Cal_third,

[0034] If the TOF2 value is less than or equal to the mean value MT1 of the first calibrated point or greater than or equal to the last calibrated point MT end , then set the correction value Cal_second at this point equal to Cal1 or Cal end .

[0035] As a further improvement of the present invention, two first-order functions are used for linear fitting in both the first piecewise calibration linear correction and the second piecewise calibration linear correction.

[0036] [[ID=4L]]The present invention also provides a test method for a single-point DTOF lidar. The test method is carried out based on the calibration correction method. The test method includes the following steps

[0037] T1. Use the mapping relationship of temperature drift correction in the calibration method to perform temperature drift correction on the measured unknown TOF value;

[0038] T2. After performing temperature drift correction on the measured unknown TOF value, limit the measured peak Peak1 within the range of maxPeak1 and minPeak1 in the calibration method, and then substitute it into the fitted quadratic function to calculate the global correction value and correct the TOF value to complete the first global fitting correction;

[0039] T3. Substitute the peak Peak1 into the piecewise function of the two adjacent calibration points to calculate the correction values corresponding to the peak Peak1 at the two adjacent calibration points, then calculate the weights of the correction values at the two adjacent calibration points according to the position of the TOF value between the two calibration points, and finally perform weighted average on the two correction values to obtain the correction value of the first piecewise correction and correct the TOF to complete the first piecewise correction;

[0040] T4. Then substitute the peak Peak2 of the attenuation channel into the piecewise function of the two adjacent calibration points to calculate the correction values corresponding to Peak2 at the two adjacent calibration points, then calculate the weights of the correction values at the two adjacent calibration points according to the position of the TOF between the two calibration points, and finally perform weighted average on the two correction values to obtain the correction value of the second piecewise correction and correct the TOF to complete the second piecewise correction.

[0041] Advantages of the present invention

[0042] The calibration and correction method and the testing method of the single-point DTOF lidar provided by the present invention can be applied to the single-point DTOF lidar, effectively improving the ranging result drift caused by temperature drift; it can overcome the problems of SPAD saturation in different high-reflection scenarios and the inability of the black target to cover lower reflectivity scenarios, and improve the ranging error caused by different pileup degrees in different reflectivity scenarios; it can improve the ranging error caused by different spot energy distributions at different distances. Description of the drawings

[0043] Figure 1 It is a schematic flowchart of the calibration and correction method of the single-point DTOF lidar of the present invention;

[0044] Figure 2 It is a schematic flowchart of the testing method of the single-point DTOF lidar of the present invention;

[0045] Figure 3 It is a schematic diagram of the macro-pixel distribution of the photosensitive surface in the embodiment of the present invention;

[0046] Figure 4 It is a schematic diagram of the fitting curve of the temperature drift correction of the present invention;

[0047] Figure 5 It is a schematic diagram of the fitting curve for the first global fitting calibration correction of the present invention;

[0048] Figure 6 It is a schematic diagram of the fitting curve for the first piecewise calibration linear correction of the present invention;

[0049] Figure 7 It is a schematic diagram of the fitting curve for the second piecewise calibration linear correction of the present invention. Detailed implementation manners

[0050] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. For the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts should fall within the protection scope of the present invention.

[0051] As Figure 1 shown, this embodiment provides a calibration and correction method for a single-point DTOF lidar, including the following steps,

[0052] S1. Use a single-point DTOF lidar to collect the original TOF data and the original temperature data TS of the black target and the white target at a fixed distance and different temperatures.

[0053] In this embodiment, the single-point DTOF lidar is placed in an incubator, facing the black target at a distance of 4 meters and the white target at a distance of 0.5 meters respectively, and it is ensured that there is no ambient light in the test scene. The temperature of the incubator is adjusted, and the temperature of the incubator circulates from -10°C to 70°C, and the original temperature data TS and the original TOF data output by the lidar at different temperatures are collected respectively.

[0054] S2. Use a single-point DTOF lidar to collect the conventional channel distance values TOF1, peak Peak1, attenuation channel peak Peak2, and measured temperature data TS1 of the black target, white target, and high-reflectivity target at different calibration point distances under the conditions of full open and non-full open of the photosensitive surface pixels respectively.

[0055] In this embodiment, the photosensitive surface is configured as a macro-pixel array of N*N, and the macro-pixels in several regions are combined into an attenuation channel, and the macro-pixels in the remaining regions are combined into a conventional channel. Preferably, it is specifically described in a 5*5 array. The photosensitive surface is divided into 25 macro-pixels in total. As Figure 3 shown, the pixels 1, 5, 21, and 25 at the four corners are combined into an attenuation channel, and the remaining 21 macro-pixels in the middle are combined into a conventional channel.

[0056] In this embodiment, step S2 specifically includes the following steps:

[0057] S21. Under the condition that the photosensitive surface pixels are fully open, collect the conventional channel distance values TOF1, peak Peak1, attenuation channel peak Peak2, and measured temperature data TS1 of the single-point DTOF lidar facing a black target, a white target, and a high-reflectivity target at different calibration distances.

[0058] In this step, the distances of each different calibration point are configured as 14 calibration distance points: 80mm, 100mm, 150mm, 200mm, 250mm, 300mm, 400mm, 500mm, 750mm, 1000mm, 2000mm, 4000mm, 6000mm, 8000mm. Collect the data of the single-point DTOF lidar with the photosensitive surface pixels fully open facing a black target with a reflectivity of 5%, a white target with a reflectivity of 95%, and a 3M high-reflectivity target at different calibration distances, and define them as the conventional channel distance value TOF1, peak Peak1, attenuation channel peak Peak2, and the temperature TS1 value output by the module.

[0059] S22. Change the photosensitive surface to a configuration with some pixels open, and collect the conventional channel distance values TOF1, peak Peak1, attenuation channel peak Peak2, and measured temperature data TS1 of the single-point DTOF lidar facing a black target -1, a white target, and a high-reflectivity target at different calibration distances.

[0060] In this step, the distances of each different calibration point are configured as 14 calibration distance points: 80mm, 100mm, 150mm, 200mm, 250mm, 300mm, 400mm, 500mm, 750mm, 1000mm, 2000mm, 4000mm, 6000mm, 8000mm. Collect the data of the single-point DTOF lidar with only 1 / 3 of the SPAD pixels of the photosensitive surface open facing a black target with a reflectivity of 5%, a white target with a reflectivity of 95%, and a 3M high-reflectivity target at different calibration distances, and define them as the conventional channel distance value TOF1, peak Peak1, attenuation channel peak Peak2, and the temperature TS1 value output by the module.

[0061] S3. Perform temperature drift correction on the collected conventional channel distance value TOF1 through the mapping relationship between the original TOF data and the original temperature data TS.

[0062] In this embodiment, as Figure 4As shown, first confirm the binomial coefficient p1 and the linear term coefficient p2 through the mapping relationship between the original TOF data and the original temperature data TS, and then perform temperature drift correction on the conventional channel distance value TOF1 and the measured temperature data TS1 collected in S22 and S23. The formula is as follows:

[0063]

[0064] TOF TS = TOF - Cal_temp.

[0065] S4. On the basis of temperature drift correction, perform the first global fitting calibration correction on the peak values Peak1 of the black target and the white target and the error value Bias of the conventional channel distance value TOF TS at different calibration point distances.

[0066] As Figure 5 shown, in this step, the first global fitting calibration correction process defaults to using a quadratic function for polynomial fitting. The specific steps are as follows:

[0067] S41. On the basis of temperature drift correction, subtract the true distance value of each calibration point from the conventional channel distance value TOF1 measured at each calibration point distance to obtain the error value Bias, use a quadratic function for polynomial fitting, and record the maximum value maxPeak1 and the minimum value minPeak1 of the black target and the white target at different calibration point distances.

[0068] In this step, on the basis of temperature drift correction, subtract the true calibration distance value from the TOF1 data of each calibration point distance to obtain the error value Bias, and use polynomial fitting for the peak values Peak1 and Bias of the black and white targets at all calibration point distances. As Figure 4 shown, default to using a quadratic function for fitting calibration, record the quadratic term a, the linear term coefficient b, and the constant term coefficient c, as well as the maximum value maxPeak1 and the minimum value minPeak1 of all Peak1 of the black and white targets.

[0069] S42. Limit all peak values Peak1 at different calibration point distances within the range of maxPeak1 and minPeak1, and then subtract the corrected value corresponding to Peak1 in the quadratic function curve from all conventional channel distance values TOF1 at different calibration point distances to complete the first global fitting calibration correction.

[0070] Cal_first = a * Peak1 2 + b * Peak1 + c

[0071] TOF1 = TOF TS - Cal_first.

[0072] In this step, the Peak1 of all calibration data is restricted within the range of maxPeak1 and minPeak1, and then the TOF values of all calibration data are subtracted by the correction values corresponding to the Peak1 in the quadratic function curve to perform the first global correction. The purpose is to correct the pileup error caused by different reflectivities in the scene with low reflectivity, especially in the scene with lower reflectivity that the black target used for calibration is difficult to cover.

[0073] S5. On the basis of the first global fitting calibration correction, perform the first piecewise calibration linear correction on the error value Bias of the Peak1 of the black target, white target and the TOF1 value of the conventional channel distance at different calibration point distances, and then perform the second piecewise calibration linear correction on the error value Bias of the Peak2 of the attenuation channel of the black target, white target and high-reflectivity target and the TOF1 value of the conventional channel distance at different calibration point distances to complete the calibration of the data.

[0074] As Figures 6 - 7 shown, in this embodiment, on the basis of the global correction, two piecewise calibration linear corrections need to be performed respectively. The specific steps are as follows:

[0075] S51. On the basis of the first global fitting calibration correction, fit the mapping relationship between the Bias and the Peak1 of the black target - 1, black target, and white target at each different calibration point distance, and use the average value of the Peak1 of the black target as the correction threshold th1. Record the maximum and minimum values of all Peak1 of the black target - 1, black target, and white target at each different calibration point distance, and the mean value MT of all TOF1 values of the black target - 1, black target, and white target at different distances. Denote the mean value of all TOF1 values of the i-th calibration point as MT i , to complete the first piecewise calibration.

[0076] On the basis of the first global calibration correction, for each calibration point, use two first-order functions to fit the mapping relationship between the Bias of the black target - 1, black, and white targets and the Peak1, record the slopes and constant terms of the two first-order functions, as Figure 5 shown, and use the mean value of the Peak1 of the black target as the correction threshold th1. Finally, record the maximum and minimum values of all Peak1 of the black - 1, black, and white targets at each calibration point to complete the first piecewise calibration.

[0077] S52. Calculate the error values Cal i and Cal i+1 corresponding to the Peak1 restricted within the maximum and minimum values on the MT i and MTi+1 , and subtract the weighted sum of the correction values corresponding to Peak1 in the piecewise functions at the two calibration points before and after from the TOF1 value of all calibration data through the following formula,

[0078]

[0079] TOF2 = TOF1 - Cal_second.

[0080] According to the piecewise function obtained from the above steps, calculate the TOF2 results of the first global fitting correction at the two calibration points MT i and MT i+1 respectively. After the Peak1 is restricted within the maximum and minimum values, the corresponding error values Cal i and Cal i+1 , and subtract the weighted sum of the correction values corresponding to Peak1 in the piecewise functions at the two calibration points before and after from the TOF1 value of all calibration data to perform the first piecewise correction. If the TOF1 value is less than or equal to the mean value MT1 of the first calibration point or greater than or equal to the last calibration point MT end , then set the correction value Cal_second at this place equal to Cal1 or Cal end . The purpose of this step is to correct the pileup error caused by different reflectivities in the scene with lower reflectivity, especially in the scene with even lower reflectivity that is difficult to cover by the black target used for calibration.

[0081] S53. Based on the TOF2 after the first piecewise calibration linear correction, fit the mapping relationship between the Bias of the black target, white target, and high-reflectivity target and the peak Peak2 of the attenuation channel at each different calibration point distance, and use the average value of the peak Peak2 of the attenuation channel of the white target as the correction threshold th2. Record the maximum and minimum values among all the peak Peak2 of the attenuation channels of the black target, white target, and high-reflectivity target at each different calibration point distance to complete the second piecewise calibration.

[0082] Based on the first piecewise calibration linear correction, for each calibration point, use two first-order functions to fit the mapping relationship between the Bias of the black, white, and high-reflectivity targets and Peak2, record the slopes and constant terms of the two first-order functions, as Figure 6 shown, and use the average value of Peak2 of the white target as the correction threshold th2. Finally, record the maximum and minimum values among all Peak1 of the black, white, and high-reflectivity targets at each calibration point to complete the first piecewise calibration.

[0083] S54. Calculate the TOF results after the first piecewise fitting correction at the two calibration points MT j and MT j+1After the peak Peak2 of its attenuation channel is restricted within the maximum and minimum values, the corresponding error value Cal j and Cal j+1 , and subtract the weighted sum of the correction values corresponding to Peak2 in the piecewise function at the two calibration points before and after from the TOF values of all calibration data through the following formula,

[0084]

[0085] TOF3 = TOF2 - Cal_third.

[0086] According to the piecewise function obtained from the above steps, calculate the TOF results of the first piecewise fitting correction at the two calibration points MT j and MT j+1 After the Peak2 is restricted within the maximum and minimum values, the corresponding error values Cal j and Cal j+1 , and subtract the weighted sum of the correction values corresponding to Peak2 in the piecewise function at the two calibration points before and after from the TOF values of all calibration data. If the TOF2 value is less than or equal to the mean MT1 of the first calibration point or greater than or equal to the last calibration point MT end , then make the correction value Cal_second at this place equal to Cal1 or Cal end . Perform the second piecewise correction,

[0087] The purpose of this step is to correct the pileup error caused by different reflectivities in the scene with a higher reflectivity. Especially when the reflectivity is higher than that of the white target, the peaks of the conventional channels all saturate. However, since the attenuation channel has fewer macro-pixels and is located at the edge of the photosensitive surface, it is not easy to saturate and can distinguish different high-reflectivity scenes.

[0088] The present invention also provides a test method for a single-point DTOF lidar. As Figure 2 shown, the test method is carried out based on the calibration and correction method. The test method includes the following steps,

[0089] T1. Perform temperature drift correction on the measured unknown TOF value by using the mapping relationship of temperature drift correction in the calibration method;

[0090] T2. After performing temperature drift correction on the measured unknown TOF value, restrict the measured peak Peak1 within the range of maxPeak1 and minPeak1 in the calibration method, and then substitute it into the fitted quadratic function to calculate the global correction value and correct the TOF value to complete the first global fitting correction;

[0091] T3. Substitute Peak1 into the piecewise functions of the two calibration points before and after, calculate the calibration values corresponding to Peak1 at the two calibration points before and after, then calculate the weights of the calibration values at the two calibration points before and after according to the position of the TOF value between the two calibration points at this time. Finally, perform a weighted average on the two calibration values to obtain the calibration value of the first piecewise calibration, and correct the TOF to complete the first piecewise calibration;

[0092] T4. Then substitute the decay channel peak Peak2 into the piecewise functions of the two calibration points before and after, calculate the calibration values corresponding to Peak2 at the two calibration points before and after, then calculate the weights of the calibration values at the two calibration points before and after according to the position of the TOF between the two calibration points at this time. Finally, perform a weighted average on the two calibration values to obtain the calibration value of the second piecewise calibration, and correct the TOF to complete the second piecewise calibration.

[0093] The calibration and correction method and the testing method of the single-point DTOF lidar provided by the present invention can be applied to the single-point DTOF lidar, effectively improving the ranging result drift caused by temperature drift; it can overcome the problems of SPAD saturation in different high-reflection scenarios and the inability of the black target to cover lower reflectivity scenarios, and improve the ranging error caused by different pileup degrees in different reflectivity scenarios; it can improve the ranging error caused by different spot energy distributions at different distances.

[0094] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present invention. Any reference signs in the claims should not be regarded as limiting the claims involved.

[0095] In addition, it should be understood that although this specification is described according to the embodiments, not every embodiment only contains an independent technical solution. This narrative way of the specification is only for clarity. Those skilled in the art should regard the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A calibration and correction method for a single-point DTOF lidar, characterized in that: including the following steps, S1. Using a single-point DTOF lidar, collect the original TOF data and the original temperature data TS of the black target and the white target at a fixed distance and different temperatures; S2. Using a single-point DTOF lidar, collect the conventional channel distance values TOF1, peak values Peak1, attenuation channel peak values Peak2, and measured temperature data TS1 of the black target, white target, and high-reflectivity target at different calibration point distances under the conditions of full opening and non-full opening of the photosensitive surface pixels respectively; S3. Perform temperature drift correction on the collected conventional channel distance value TOF1 through the mapping relationship between the original TOF data and the original temperature data TS; S4. On the basis of the temperature drift correction, perform the first global fitting calibration correction on the error values Bias of the peak values Peak1 and the conventional channel distance values TOF1 of the black target and the white target at different calibration point distances; S5. On the basis of the first global fitting calibration correction, perform the first segmented calibration linear correction on the error values Bias of the peak values Peak1 and the conventional channel distance values TOF1 of the black target and the white target at different calibration point distances, and then perform the second segmented calibration linear correction on the error values Bias of the attenuation channel peak values Peak2 and the conventional channel distance values TOF1 of the black target, white target, and high-reflectivity target at different calibration point distances to complete the calibration of the data.

2. The calibration and correction method of the single-point DTOF lidar according to claim 1, characterized in that: The photosensitive surface is configured as a macro-pixel array of N*N, and the macro-pixels in several regions are combined into an attenuation channel, and the macro-pixels in the remaining regions are combined into a conventional channel.

3. The calibration and correction method for a single-point DTOF laser radar according to claim 2, characterized in that: The step S2 includes the following steps, S21. Under the condition of full opening of the photosensitive surface pixels, collect the conventional channel distance values TOF1, peak values Peak1, attenuation channel peak values Peak2, and measured temperature data TS1 of the single-point DTOF lidar facing the black target, white target, and high-reflectivity target at different calibration distances; S22. Change the photosensitive surface to a configuration with partial pixel opening, and collect the conventional channel distance values TOF1, peak values Peak1, attenuation channel peak values Peak2, and measured temperature data TS1 of the single-point DTOF lidar facing the black target -1, white target, and high-reflectivity target at different calibration distances.

4. The calibration and correction method of the single-point DTOF lidar according to claim 3, characterized in that: The temperature drift correction includes confirming the binomial coefficient p1 and the first-order coefficient p2 through the mapping relationship between the original TOF data and the original temperature data TS, and then performing temperature drift correction on the conventional channel distance value TOF and the measured temperature data TS1 collected in S22 and S23. The formula is as follows, TOF TS = TOF-Cal_temp.

5. The calibration and correction method of the single-point DTOF lidar according to claim 4, wherein: The step S4 includes the following steps, S41. On the basis of temperature drift correction, subtract the true distance value of the corresponding calibration point from the TOF of the conventional channel distance measured at each calibration point distance to obtain the error value Bias, perform polynomial fitting using a quadratic function, and record the maximum value maxPeak1 and the minimum value minPeak1 of the black target and the white target at different calibration point distances; TS Subtract the true distance value of the corresponding calibration point from the TOF of the conventional channel distance measured at each calibration point distance to obtain the error value Bias, perform polynomial fitting using a quadratic function, and record the maximum value maxPeak1 and the minimum value minPeak1 of the black target and the white target at different calibration point distances; S42. Limit the peak Peak1 at all different fiducial point distances within the range of maxPeak1 and minPeak1, and then subtract the correction value corresponding to the corresponding Peak1 in the quadratic function curve from the TOF value of the conventional channel distance at all different fiducial point distances to complete the first global fitting calibration correction. TS The value is subtracted by the correction value corresponding to the corresponding Peak1 in the quadratic function curve to complete the first global fitting calibration correction. Cal_first = a * Peak1 2 + b * Peak1 + c TOF1 = TOF TS -Cal_first.

6. The calibration and correction method of the single-point DTOF lidar according to claim 5, wherein: The first segmented calibration linear correction includes the following steps, S51. On the basis of the first global fitting calibration and correction, fit the mapping relationships of Bias and peak Peak1 of black target - 1, black target, and white target at each different calibrated point distance, and take the average value of the peak Peak1 of the black target as the correction threshold th1. Record the maximum and minimum values among all the peak Peak1 values of black target - 1, black target, and white target at each different calibrated point distance, and the mean value MT of all TOF1 values of black target - 1, black target, and white target at different distances. Denote the mean value of all TOF1 values of the i-th calibrated point as MTi to complete the first stage calibration; S52. Calculate the TOF results of the first global fitting correction at the two calibration points MT before and after respectively i and MT i+1 After the Peak1 is restricted within the maximum and minimum values, the corresponding error values Cali and Cal i+1 And subtract the weighted sum of the correction values corresponding to Peak1 in the piecewise functions at the two calibration points before and after from the TOF1 values of all calibration data through the following formula TOF2 = TOF1 - Cal_second If the TOF1 value is less than or equal to the mean value MT1 of the first calibration point or greater than or equal to the last calibration point MT end , then set the correction value Cal_second at this point equal to Cal1 or Cal end .

7. The calibration and correction method of the single-point DTOF lidar according to claim 6, characterized in that: The second stage calibration linear correction includes the following steps, S53. On the basis of TOF2 after the first global fitting calibration correction, fit the mapping relationships of the Bias and the peak Peak2 of the attenuation channel for the black target, white target, and high-reflectivity target at each different calibrated point distance, and use the average value of the peak Peak2 of the attenuation channel of the white target as the calibration threshold th2. Record the maximum and minimum values among all the peak Peak2 of the attenuation channels of the black target, white target, and high-reflectivity target at each different calibrated point distance, and the mean value MT of all the TOF2 values of the black target, white target, and high-reflectivity target at each different calibrated point distance at different distances. Denote the mean value of all the TOF2 values of the j-th calibrated point as MT j , to complete the second-stage calibration; S54. Calculate the TOF results after the first piecewise fitting correction at the front and rear calibration points MT j and MT j+1 respectively. After the peak Peak2 of the decay channel is limited within the maximum and minimum values, the corresponding error value Cal j and Cal j+1 are obtained. Then, subtract the weighted sum of the correction values corresponding to Peak2 in the piecewise functions at the front and rear calibration points from the TOF2 values of all calibration data through the following formula TOF3 = TOF2 - Cal_third If the TOF2 value is less than or equal to the mean MT1 of the first calibration point or greater than or equal to the MT of the last calibration point end , then let the correction value Cal_third equal to Cal1 or Cal end .

8. The calibration and correction method of the single-point DTOF lidar according to claim 7, characterized in that: In both the first stage calibration linear correction and the second stage calibration linear correction, linear fitting is performed using two linear functions.

9. A test method for a single-point DTOF lidar, characterized in that: The testing method is carried out after the calibration and correction method described in any one of claims 1 - 8. The testing method includes the following steps, T1. Use the mapping relationship of temperature drift correction in the calibration method to perform temperature drift correction on the measured unknown TOF value; T2. After performing temperature drift correction on the measured unknown TOF value, limit the measured peak Peak1 within the range of maxPeak1 and minPeak1 in the calibration method, and then substitute it into the fitted quadratic function to calculate the global correction value and correct the TOF value to complete the first global fitting correction; T3. Substitute the peak Peak1 into the piecewise functions of the two adjacent calibrated points to calculate the correction values corresponding to the peak Peak1 at these two calibrated points. Then, calculate the weights of the correction values at the two calibrated points according to the position of the TOF value between the two calibrated points. Finally, perform weighted averaging on the two correction values to obtain the correction value of the first stage correction and correct the TOF to complete the first stage correction; T4. Then substitute the attenuation channel peak Peak2 into the piecewise functions of the two adjacent calibrated points to calculate the correction values corresponding to Peak2 at these two calibrated points. Then, calculate the weights of the correction values at the two calibrated points according to the position of the TOF between the two calibrated points. Finally, perform weighted averaging on the two correction values to obtain the correction value of the second stage correction and correct the TOF to complete the second stage correction.

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