A classification method and device for laser radar system

Abstract

The present application provides a grading method and device for a laser radar system, the method comprising: obtaining a target data set; removing invalid data from the target data set to obtain a target filtered data set; performing capture matrix statistics on the target filtered data set to obtain statistical results corresponding to the target filtered data set; determining, based on the statistical results corresponding to the target filtered data set, whether the number of statistical values ​​contained in the target filtered data set meets a preset quantity requirement; if so, determining, based on the statistical results corresponding to the target filtered data set, whether the target laser radar system is mature; if the target laser radar system is mature, calculating the uncertainty accuracy level of the target laser radar system based on the target filtered data set. Thus, the present application can calculate the uncertainty accuracy level of the target laser radar system.

Description

Technical Field

[0001] The present application relates to the technical field of laser radar systems, and in particular to a classification method and device for laser radar systems. Background Art

[0002] As offshore wind resources are depleted, developing offshore wind resources has become inevitable. The water depths in offshore waters are considerable, and erecting traditional wind towers is time-consuming and expensive. However, with the significant improvements in the reliability and performance of LiDAR systems, and the further reduction in maintenance time and cycle, LiDAR systems, as a new, fast and convenient offshore wind measurement device, offer significant economic, technical, and time advantages.

[0003] The uncertainty included in the classification of lidar systems can be used to characterize the difference between the meteorological data measured by the lidar system and the true value. The estimated range of this uncertainty is crucial to the profitability of the wind farm's subsequent operations. However, there is currently no method in the industry to calculate the uncertainty of lidar systems.

[0004] In summary, there is an urgent need for a classification method for lidar systems to determine the uncertainty accuracy level of lidar systems. Summary of the Invention

[0005] In view of this, the present application provides a classification method and device for a lidar system, which is used to calculate the uncertainty accuracy level of the lidar system. The technical solution is as follows:

[0006] A classification method for a laser radar system, comprising:

[0007] Obtaining a target data set, wherein the target data set includes at least three data sets consisting of statistical values ​​of data collected under set conditions by two lidar systems of the same model and wind towers located in two sea areas, the statistical values ​​at least including wind speed statistics, and the set conditions including at least one wave height;

[0008] Eliminate invalid data from the target data set to obtain the target filtered data set;

[0009] Performing capture matrix statistics on the target filtered data set to obtain statistical results corresponding to the target filtered data set, wherein the capture matrix is ​​used to count the number of statistical values ​​in which wave heights are within each preset wave height interval and wind speed statistical values ​​are within each preset wind speed interval, as well as the total number of statistical values ​​and the number of wave height intervals in each preset wind speed interval, wherein the number of wave height intervals in a preset wind speed interval refers to the number of preset wave height intervals in which the number of statistical values ​​in the preset wind speed interval is greater than or equal to a first number;

[0010] Determine whether the number of statistical values ​​contained in the target filtered data set meets the preset number requirement based on the statistical results corresponding to the target filtered data set;

[0011] If the requirements are met, the target LiDAR system is determined to be mature based on the statistical results of the target screening data set. The target LiDAR system includes at least two LiDAR systems of the same model.

[0012] If the target lidar system is mature, the uncertainty accuracy level of the target lidar system is calculated based on the target screening data set.

[0013] Optionally, also include:

[0014] Determine the data efficiency based on the target filtered data set and the target data set;

[0015] According to the data efficiency, it is determined whether the target lidar system is mature, so that when the target lidar system is mature, the capture matrix statistics of the target screened data set are performed to obtain the statistical results corresponding to the target screened data set.

[0016] Optionally, the target filtered data set includes at least filtered data sets corresponding to three data sets respectively;

[0017] Perform capture matrix statistics on the target filtered data set to obtain statistical results corresponding to the target filtered data set, including:

[0018] For each filtered data set included in the target filtered data set, performing capture matrix statistics on the filtered data set to obtain statistical results corresponding to the filtered data set; so as to obtain statistical results corresponding to each filtered data set included in the target filtered data set;

[0019] According to the statistical results corresponding to the target filtered data set, determine whether the number of statistical values ​​contained in the target filtered data set meets the preset quantity requirements, including:

[0020] For each filtered data set included in the target filtered data set, determining whether the number of statistical values ​​included in the filtered data set meets a preset number requirement based on the statistical result corresponding to the filtered data set;

[0021] Based on the statistical results of the target screening data set, determine whether the target lidar system is mature, including:

[0022] For each filtered data set included in the target filtered data set, determining whether the laser radar system corresponding to the filtered data set is mature according to the statistical results corresponding to the filtered data set; thereby obtaining whether the laser radar system corresponding to each filtered data set included in the target filtered data set is mature;

[0023] If the laser radar system corresponding to each filtered data set included in the target filtered data set is mature, it is determined that the target laser radar system is mature.

[0024] Optionally, the preset quantity requirement is that in the statistical results corresponding to the filtered data set, the total number of statistical values ​​under each preset wind speed interval is greater than or equal to a second number, and the number of wave height intervals under each preset wind speed interval is greater than or equal to a third number, and there are at least two preset wave height intervals that meet the preset quantity sub-requirements, and the preset quantity sub-requirements are that the number of statistical values ​​in the first wind speed interval and the second wind speed interval under a preset wave height interval is greater than or equal to a fourth number, and the total number of statistical values ​​under the preset wave height interval is greater than or equal to a fifth number.

[0025] Optionally, determining whether a lidar system corresponding to the filtered data set is mature based on statistical results corresponding to the filtered data set includes:

[0026] Establishing a first linear regression equation for the wind speed statistics in each preset wave height interval in the statistical results corresponding to the filtered data set, and establishing a second linear regression equation for the wind speed statistics in all preset wave height intervals, to obtain the slope and correlation coefficient corresponding to each first linear regression equation, as well as the slope and correlation coefficient corresponding to the second linear regression equation;

[0027] Based on the slopes and correlation coefficients corresponding to the first linear regression equations, and the slopes and correlation coefficients corresponding to the second linear regression equations, it is determined whether the lidar system corresponding to the filtered data set is mature.

[0028] Optionally, the wind speed statistical value is an average wind speed, and the setting condition further includes at least one height above the ground;

[0029] Based on the target screening data set, calculate the uncertainty accuracy level of the target lidar system, including:

[0030] For each filtered data set contained in the target filtered data set:

[0031] Classifying the filtered data set according to the height above the ground to obtain at least one statistical value set corresponding to each height above the ground;

[0032] Determining, based on a set of statistical values ​​corresponding to at least one ground clearance height, a final accuracy corresponding to at least one ground clearance height in the filtered data set;

[0033] To obtain the final accuracy corresponding to at least one ground clearance height under each filtered data set included in the target filtered data set;

[0034] The uncertainty accuracy level of the target lidar system is determined according to the final accuracy corresponding to at least one ground clearance height under each filtered data set contained in the target filtered data set.

[0035] Optionally, determining, based on a set of statistical values ​​corresponding to at least one ground clearance height, a final accuracy corresponding to at least one ground clearance height in the filtered data set includes:

[0036] Calculating, based on a set of statistical values ​​corresponding to at least one ground clearance, a value and a value range of a preset environmental factor corresponding to at least one ground clearance;

[0037] Determining a target environmental factor from the preset environmental factors based on an average wind speed included in a set of statistical values ​​corresponding to at least one ground clearance height and a value of at least one preset environmental factor corresponding to the at least one ground clearance height, wherein the target environmental factor has a significant impact on the uncertainty accuracy level of the target lidar system;

[0038] determining a maximum deviation of at least one ground clearance corresponding to the target environmental factor based on a slope and a value range of an equation in which at least one ground clearance corresponds to the target environmental factor;

[0039] For each of the at least one ground clearance height, calculating an initial precision corresponding to the ground clearance height based on a maximum deviation of the ground clearance height corresponding to the target environmental factor, to obtain an initial precision corresponding to the at least one ground clearance height;

[0040] The initial accuracy corresponding to the at least one height above the ground is divided by a preset value to obtain the final accuracy corresponding to the at least one height above the ground, which is used as the final accuracy corresponding to the at least one height above the ground in the filtered data set.

[0041] Optionally, determining the target environmental factor from the preset environmental factors according to the wind speed average value included in the statistical value set corresponding to at least one height above the ground and the value of the preset environmental factor corresponding to at least one height above the ground includes:

[0042] Calculating the wind speed deviation percentage corresponding to at least one height above the ground according to the wind speed average value included in the statistical value set corresponding to at least one height above the ground;

[0043] Establishing a third linear regression equation based on the value of the preset environmental factor corresponding to the at least one height above the ground and the wind speed deviation percentage corresponding to the at least one height above the ground, so as to obtain a third linear regression equation corresponding to the preset environmental factor for the at least one height above the ground;

[0044] Determining, according to a third linear regression equation in which at least one ground clearance height corresponds to the preset environmental factors, an equation slope, a standard deviation of the preset environmental factors, and a correlation coefficient as the equation slope, standard deviation, and correlation coefficient in which at least one ground clearance height corresponds to the preset environmental factors;

[0045] The target environmental factor is determined from the preset environmental factors according to a slope of an equation in which at least one height above the ground corresponds to the preset environmental factor, a standard deviation of the preset environmental factor, and a correlation coefficient.

[0046] Optionally, determining the uncertainty accuracy level of the target lidar system according to the final accuracy corresponding to at least one ground clearance height under each filtered data set included in the target filtered data set includes:

[0047] Calculate the sum of squares of the final accuracies corresponding to at least one ground clearance height in the target filtered data set;

[0048] Taking the square root of the sum of squares, we can obtain the uncertainty accuracy level of the target lidar system.

[0049] A grading device for a laser radar system, comprising: a target data set acquisition module, an invalid data elimination module, a capture matrix statistics module, a quantity requirement satisfaction judgment module, a radar maturity judgment module, and an uncertainty calculation module;

[0050] a target data set acquisition module, configured to acquire a target data set, wherein the target data set includes at least three data sets consisting of statistical values ​​of data collected under set conditions by two lidar systems of the same model and wind towers located in two sea areas, wherein the statistical values ​​include at least wind speed statistics, and the set conditions include at least one wave height;

[0051] The invalid data elimination module is used to eliminate invalid data in the target data set to obtain the target filtered data set;

[0052] a capture matrix statistics module, configured to perform capture matrix statistics on the target filtered data set to obtain statistical results corresponding to the target filtered data set, wherein the capture matrix is ​​used to count the number of statistical values ​​in which the wave height is within each preset wave height interval and the wind speed statistical value is within each preset wind speed interval, as well as the total number of statistical values ​​and the number of wave height intervals in each preset wind speed interval, wherein the number of wave height intervals in a preset wind speed interval refers to the number of preset wave height intervals in which the number of statistical values ​​in the preset wind speed interval is greater than or equal to a first number;

[0053] A quantity requirement satisfaction judgment module is used to determine whether the number of statistical values ​​contained in the target filtered data set meets the preset quantity requirement based on the statistical results corresponding to the target filtered data set;

[0054] A radar maturity judgment module is configured to determine whether the target lidar system is mature based on the statistical results corresponding to the target screened data set if the quantity requirement satisfaction judgment module determines that the number of statistical values ​​contained in the target screened data set meets the preset quantity requirement, wherein the target lidar system includes at least two lidar systems of the same model;

[0055] The uncertainty calculation module is used to calculate the uncertainty accuracy level of the target lidar system based on the target screened data set if the radar maturity judgment module determines that the target lidar system is mature.

[0056] Through the above technical solution, it can be known that the grading method of the laser radar system provided by the present application first obtains the target data set, then eliminates the invalid data in the target data set to obtain the target filtered data set, and then performs capture matrix statistics on the target filtered data set to obtain the statistical results corresponding to the target filtered data set. Then, based on the statistical results corresponding to the target filtered data set, it is determined whether the number of statistical values ​​contained in the target filtered data set meets the preset number requirements. If so, it is determined whether the target laser radar system is mature based on the statistical results corresponding to the target filtered data set. If the target laser radar system is mature, the uncertainty accuracy level of the target laser radar system is calculated based on the target filtered data set. It can be seen from this that the present application can determine whether the number of statistical values ​​contained in the target filtered data set meets the preset number requirements based on the statistical results after performing capture matrix statistics on the target filtered data set, and can determine whether the target laser radar system is mature. When the target laser radar system is mature, the present application can calculate the uncertainty accuracy level of the target laser radar system based on the target filtered data set. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without any creative work.

[0058] Figure 1 A schematic diagram of a flow chart of a classification method for a laser radar system provided in an embodiment of the present application;

[0059] Figure 2 Schematic diagram of the test scene consisting of the lidar system and the wind tower;

[0060] Figure 3 A schematic diagram of the structure of a grading device for a laser radar system according to an embodiment of the present application;

[0061] Figure 4 This is a block diagram of the hardware structure of the grading device of the lidar system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0062] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0063] The present application provides a classification method and device for a laser radar system. The classification method for the laser radar system provided in the present application is described in detail through the following embodiments.

[0064] See also Figure 1 , shows a schematic flow chart of a classification method for a laser radar system provided in an embodiment of the present application. The classification method for a laser radar system may include:

[0065] Step S101: Acquire a target data set.

[0066] Among them, the target data set includes at least three data sets consisting of statistical values ​​of data collected under set conditions by two lidar systems of the same model and wind towers located in two sea areas. The statistical values ​​include at least wind speed statistics, and the set conditions include at least one wave height.

[0067] The embodiment of the present application can collect data under set conditions based on two lidar systems of the same model and wind towers located in two sea areas to perform graded testing on the lidar systems.

[0068] Here, the wind tower is equipped with sensors for wind speed, wind direction, temperature and humidity, air pressure, etc., as well as a wave profile current meter, which is used to collect wave height data. In this step, considering that different LiDAR systems may have different requirements for water depth and waves, it is necessary to select appropriate offshore wind towers for comparative testing based on different types of LiDAR systems. In order to ensure that the calculated uncertainty accuracy level is more accurate, this step requires at least two offshore wind towers, and the weather and wave conditions in the sea area where the two offshore wind towers are located are preferably different, so that the impact of these conditions on the LiDAR system can be better tested.

[0069] Optionally, the laser radar system can be a floating laser radar system. In this step, at least two laser radar systems of the same model are required, wherein the two laser radar systems are graded and tested in the same sea area, and one of the two laser radar systems is required to be graded and tested again in another sea area. Taking the floating laser radar system as an example, please refer to Figure 2 As shown, the floating radar system 1 and the floating radar system 2 collect data in the test sea area 1 , and the floating radar system 1 also collects data in the test sea area 2 .

[0070] In this embodiment, the data storage requirement for the LiDAR system and the wind tower is statistical values ​​within a set time period. That is, after data collection, both the LiDAR system and the wind tower will collect statistics for the data collected during the set time period at set intervals, obtain statistical values ​​for the set time period, and store these statistics. Optionally, the set time period is 10 minutes, and the statistical values ​​include, but are not limited to, maximum value, minimum value, standard deviation, and statistical value.

[0071] In this step, the statistical values ​​of the data collected by the wind tower and the lidar system in the same sea area constitute a data set. Therefore, the statistical values ​​of the data collected by two lidar systems of the same model and the wind towers in two sea areas constitute three data sets in total. For example, Figure 2 For example, the statistical values ​​of the data collected by the floating radar system 1 and the wind tower located in the test sea area 1 constitute a first data set, the statistical values ​​of the data collected by the floating radar system 2 and the wind tower located in the test sea area 1 constitute a second data set, and the statistical values ​​of the data collected by the floating radar system 1 and the wind tower located in the test sea area 2 constitute a third data set; then, the target data set obtained in this step includes at least these three data sets, that is, the graded test is performed at least based on these three data sets, which can make the uncertainty accuracy level finally calculated by this embodiment more accurate.

[0072] It's worth noting that the timing error between the lidar system and the wind tower collector in this embodiment must be within 6 seconds. Otherwise, the calculated uncertainty level of accuracy may be inaccurate. Therefore, the collectors can be calibrated weekly to ensure that the timing error between the lidar system and the wind tower collector is consistently within 6 seconds.

[0073] It should also be noted that the data collected by the above-mentioned lidar system and wind tower are carried out under set conditions. Optionally, the set conditions include at least one wave height, that is, the data collected by the lidar system and wind tower refer to data corresponding to at least one wave height.

[0074] In addition, optionally, the data collected by the lidar system and the wind tower may include wind speed data, and the above-mentioned statistical values ​​specifically refer to wind speed statistical values; of course, the data collected by the lidar system and the wind tower may also include other data, such as wind direction, temperature, humidity, etc., which is not limited in this application.

[0075] Step S102: Eliminate invalid data from the target data set to obtain a target filtered data set.

[0076] It is understandable that the statistical values ​​of the data collected by the lidar system and the wind tower may contain some invalid data. In order to prevent the invalid data from affecting the calculated uncertainty accuracy level, the invalid data needs to be eliminated.

[0077] Optionally, invalid data refers to the following data: first, data within the sector affected by surrounding obstacles; second, data when the reference anemometer is affected by the wind tower body, bracket and other equipment; third, data when the lidar system or offshore wind tower instrument is damaged; fourth, data when conditions such as waves exceed the allowable range of the lidar system.

[0078] Step S103: Perform capture matrix statistics on the target filtered data set to obtain statistical results corresponding to the target filtered data set.

[0079] First, the capture matrix is ​​introduced.

[0080] In this step, the capture matrix can count the number of statistical values ​​contained in each filtered data set according to the preset wind speed interval and the preset wave height interval. Specifically, the capture matrix is ​​used to count the number of statistical values ​​whose wave height is in each preset wave height interval and the wind speed statistical value is in each preset wind speed interval, as well as the total number of statistical values ​​and the number of wave height intervals under each preset wind speed interval. The number of wave height intervals under a preset wind speed interval refers to the number of preset wave height intervals whose number of statistical values ​​under the preset wind speed interval is greater than or equal to the first number.

[0081] It should be noted that this application does not limit the first quantity, and the specific quantity can be determined according to actual conditions. For example, the first quantity can be set to 3.

[0082] To facilitate understanding of the capture matrix, an exemplary capture matrix is ​​given below. It should be noted that the preset wind speed intervals and preset wave height intervals included in the capture matrix shown in Table 1 are only examples and are not intended to limit the present application.

[0083] Table 1. Statistics of capture matrix

[0084]

[0085] As introduced in the above steps, the target filtered data set includes at least three data sets, and the target filtered data set in this step includes the filtered data sets corresponding to at least three data sets respectively. Based on this, this step of "performing capture matrix statistics on the target filtered data set" is actually performing capture matrix statistics on each filtered data set contained in the target filtered data set. That is, the process of this step includes: for each filtered data set contained in the target filtered data set, performing capture matrix statistics on the filtered data set to obtain the statistical results corresponding to the filtered data set; so as to obtain the statistical results corresponding to each filtered data set contained in the target filtered data set.

[0086] Step S104: Determine, based on the statistical results corresponding to the target filtered data set, whether the number of statistical values ​​included in the target filtered data set meets a preset number requirement.

[0087] In this embodiment, one of the functions of the capture matrix is ​​to determine whether the number of statistical values ​​contained in the target data set after screening is sufficient for grading testing. Based on this, this step can determine whether the number of statistical values ​​contained in the target data set after screening meets the preset quantity requirements based on the statistical results corresponding to the target data set after screening.

[0088] It has been explained above that "the target filtered data set includes filtered data sets corresponding to at least three data sets respectively", so the process of this step may include: for each filtered data set included in the target filtered data set, based on the statistical results corresponding to the filtered data set, determining whether the number of statistical values ​​contained in the filtered data set meets the preset quantity requirement.

[0089] Optionally, the preset quantity requirement may be: in the statistical results corresponding to the filtered data set, the total number of statistical values ​​under each preset wind speed interval is greater than or equal to the second number, and the number of wave height intervals under each preset wind speed interval is greater than or equal to the third number, and there are at least two preset wave height intervals that meet the preset quantity sub-requirement, and the preset quantity sub-requirement is that the number of statistical values ​​in the first wind speed interval and the second wind speed interval under a preset wave height interval is greater than or equal to the fourth number, and the total number of statistical values ​​under the preset wave height interval is greater than or equal to the fifth number.

[0090] Table 1 above is used as an example to illustrate the preset quantity requirements.

[0091] If, in Table 1, each value contained in the row for the total number of statistical values ​​is greater than or equal to the second number, and each value contained in the row for the number of wave height intervals is greater than or equal to the third number, and at least two preset wave height intervals meet the preset number sub-requirement, then the number of statistical values ​​contained in the filtered data set corresponding to Table 1 meets the preset number requirement. Specifically, with respect to the preset number sub-requirement, if the number of statistical values ​​within a first wind speed interval within a preset wave height interval is greater than or equal to a fourth number, and the number of statistical values ​​within a second wind speed interval within the preset wave height interval is greater than or equal to a fourth number, and the total number of statistical values ​​within the preset wave height interval is greater than or equal to a fifth number, then the preset wave height interval meets the preset number sub-requirement.

[0092] Here, the number of statistical values ​​in the first wind speed interval under a preset wave height interval refers to the sum of the values ​​in the first wind speed interval in this row of the preset wave height interval, the number of statistical values ​​in the second wind speed interval under a preset wave height interval refers to the sum of the values ​​in the second wind speed interval in this row of the preset wave height interval, and the total number of statistical values ​​under a preset wave height interval refers to the sum of all values ​​in this row of the preset wave height interval.

[0093] It should be noted that the above-mentioned second number, third number, fourth number and fifth number can all be determined according to actual conditions, and this application does not limit this. For example, the second number can be 10, the third number can be 2, the fourth number can be 36, and the fifth number can be 144; the sum of the above-mentioned first wind speed interval and the second wind speed interval is equal to the sum of all preset wind speed intervals. For example, for Table 1, the first wind speed interval refers to [4,8) and the second wind speed interval refers to [8,16.5).

[0094] Step S105: If satisfied, determine whether the target lidar system is mature based on the statistical results corresponding to the target filtered data set.

[0095] Among them, the target lidar system includes at least two lidar systems of the same model.

[0096] In this embodiment, another function of the capture matrix is ​​to determine whether the target lidar system is mature enough for classification testing.

[0097] Optionally, for each filtered data set included in the target filtered data set, if the number of statistical values ​​included in the filtered data set is determined to meet a preset number requirement in the previous step, the maturity of the lidar system corresponding to the filtered data set can be determined based on the statistical results corresponding to the filtered data set. This determination process is performed for each filtered data set, thereby determining whether the lidar system corresponding to each filtered data set included in the target filtered data set is mature.

[0098] In this step, if the laser radar systems corresponding to each filtered data set included in the target filtered data set are all mature, it is determined that the target laser radar system is mature.

[0099] For example, for Figure 2 If, according to the statistical results corresponding to the filtered data set corresponding to the "first data set" mentioned in step S101, floating radar system 1 is determined to be mature, and according to the statistical results corresponding to the filtered data set corresponding to the "second data set" mentioned in step S101, floating radar system 2 is determined to be mature, and according to the statistical results corresponding to the filtered data set corresponding to the "third data set" mentioned in step S101, floating radar system 1 is determined to be mature, then both floating radar systems 1 and 2 are determined to be mature; if, according to the statistical results corresponding to the filtered data set corresponding to the "first data set" mentioned in step S101, floating radar system 1 is determined to be mature, and according to the statistical results corresponding to the filtered data set corresponding to the "third data set" mentioned in step S101, floating radar system 1 is determined to be immature, then floating radar system 1 is determined to be immature.

[0100] Optionally, when this step determines that a certain laser radar system included in the target laser radar system is immature, the target screening data set and the above-mentioned judgment process can also be analyzed to further analyze whether the laser radar system is really immature. If further analysis finds that the laser radar system is mature, the target laser radar system can still be considered mature. If further analysis finds that the laser radar system is indeed immature, the target laser radar system is considered immature.

[0101] Step S106: If the target lidar system is mature, calculate the uncertainty accuracy level of the target lidar system based on the target screened data set.

[0102] In this step, graded testing can be performed when the target lidar system is mature. If the target lidar system is not mature, even if the uncertainty accuracy level of the target lidar system can be calculated based on the target screened data set, the calculated uncertainty accuracy level of the target lidar system will not be accurate.

[0103] The grading method of the laser radar system provided by the present application first obtains the target data set, then eliminates the invalid data in the target data set to obtain the target filtered data set, then performs capture matrix statistics on the target filtered data set to obtain the statistical results corresponding to the target filtered data set, and then determines whether the number of statistical values ​​contained in the target filtered data set meets the preset number requirements based on the statistical results corresponding to the target filtered data set. If so, then determine whether the target laser radar system is mature based on the statistical results corresponding to the target filtered data set. If the target laser radar system is mature, then calculate the uncertainty accuracy level of the target laser radar system based on the target filtered data set. It can be seen from this that the present application can determine whether the number of statistical values ​​contained in the target filtered data set meets the preset number requirements based on the statistical results after performing capture matrix statistics on the target filtered data set, and can determine whether the target laser radar system is mature. When the target laser radar system is mature, the present application can calculate the uncertainty accuracy level of the target laser radar system based on the target filtered data set.

[0104] In one embodiment of the present application, if a large amount of invalid data is removed during step S102, for example, 4 out of 10 statistical values ​​are invalid data, it indicates that the maturity of the LiDAR system needs to be improved. In this case, the grading test is not performed, and it is necessary to wait until the LiDAR system is sufficiently mature before grading the test. In other words, this embodiment determines the data efficiency based on the target post-screening data set and the target data set, and then determines whether the target LiDAR system is mature based on the data efficiency. If the target LiDAR system is mature, the above-mentioned step S103 is executed. If the target LiDAR system is not mature, step S103 and subsequent steps are not executed.

[0105] Optionally, the process of "determining the data efficiency based on the target filtered data set and the target data set" may include: for each filtered data set contained in the target filtered data set and the corresponding data set in the target data set, dividing the number of statistical values ​​contained in the filtered data set by the number of statistical values ​​contained in the corresponding data set, and the quotient obtained is the data efficiency corresponding to the filtered data set.

[0106] Correspondingly, the process of "determining whether the target lidar system is mature based on data efficiency" may include: for each filtered data set contained in the target filtered data set, if the data efficiency corresponding to the filtered data set is greater than or equal to the preset efficiency threshold, then the lidar system corresponding to the filtered data set is determined to be mature; otherwise, the lidar system corresponding to the filtered data set is determined to be immature; if the lidar systems corresponding to each filtered data set contained in the target filtered data set are mature, then the target lidar system is determined to be mature.

[0107] Optionally, the above-mentioned preset efficiency threshold may be 95%. Of course, the preset efficiency threshold may also be set to other values ​​according to actual conditions, which is not limited in this application.

[0108] After eliminating invalid data, this embodiment will first determine whether the target lidar system is mature based on the data efficiency. If it is not mature, the subsequent steps will not be executed, which improves the efficiency of the graded test to a certain extent.

[0109] An embodiment of the present application introduces the process of "determining whether the lidar system corresponding to the filtered data set is mature based on the statistical results corresponding to the filtered data set" mentioned in the above step S105.

[0110] Optionally, the process of “determining whether the lidar system corresponding to the filtered data set is mature based on the statistical results corresponding to the filtered data set” may include:

[0111] A1. In the statistical results corresponding to the filtered data set, a first linear regression equation is established for the wind speed statistical values ​​in each preset wave height interval, and a second linear regression equation is established for the wind speed statistical values ​​in all preset wave height intervals, so as to obtain the slope and correlation coefficient corresponding to each first linear regression equation, as well as the slope and correlation coefficient corresponding to the second linear regression equation.

[0112] Table 1 is used as an example for explanation.

[0113] First, this step can establish a first linear regression equation based on the wind speed statistical values ​​in the row with the preset wave height interval of "<1", establish a first linear regression equation based on the wind speed statistical values ​​in the row with the preset wave height interval of "[1,2)",..., and so on, establish a first linear regression equation based on the wind speed statistical values ​​in the row with the preset wave height interval of ">7", thus establishing a total of 8 first linear regression equations.

[0114] Then, in this step, a second linear regression equation may be established based on the wind speed statistical values ​​in the preset wave height range of 8 rows from "<1" to ">7".

[0115] Finally, regression analysis was performed on the eight first linear regression equations and one second linear regression equation established above, and the slopes and correlation coefficients (i.e., R 2 ).

[0116] It should be noted that the formats of the first linear regression equation and the second linear regression equation are both y=kx+b, where x is the wind speed statistical value collected by the lidar system, and y is the wind speed statistical value collected by the wind measurement tower.

[0117] A2. Determine whether the lidar system corresponding to the filtered data set is mature based on the slopes and correlation coefficients corresponding to the first linear regression equations and the slopes and correlation coefficients corresponding to the second linear regression equations.

[0118] Optionally, if the slopes corresponding to the first linear regression equations and the slopes corresponding to the second linear regression equations are both within a first preset slope range, and the correlation coefficients corresponding to the first linear regression equations and the correlation coefficients corresponding to the second linear regression equations are both greater than or equal to a preset correlation coefficient threshold, then it is determined that the lidar system corresponding to the filtered data set is mature.

[0119] Optionally, the above process of "judging whether the laser radar system corresponding to the filtered data set is mature based on the statistical results corresponding to the filtered data set" not only needs to determine whether the laser radar system is mature based on the wind speed statistics, but also needs to make a judgment based on the wind direction, that is, to judge whether the laser radar system is mature based on both the wind speed statistics and the wind direction. In this case, in addition to the above conditions, this step also needs to meet the following requirements: the slopes corresponding to the first linear regression equations established based on wind direction (the specific establishment process can refer to the establishment process based on wind speed statistics), and the slopes corresponding to the second linear regression equations established based on wind direction (the specific establishment process can refer to the establishment process based on wind speed statistics) are all within the second preset slope range, and the correlation coefficients corresponding to the first linear regression equations established based on wind direction, and the correlation coefficients corresponding to the second linear regression equations established based on wind direction are all greater than or equal to the preset correlation coefficient threshold. Only then can the laser radar system be determined to be mature. Otherwise, it is considered that the maturity of the laser radar system needs to be improved, and it is not recommended to conduct graded testing at this stage.

[0120] It should be noted that this application does not limit the above-mentioned first preset slope range, second preset slope range and preset correlation coefficient threshold, which can be determined according to actual conditions. For example, the above-mentioned first preset slope range can be 0.98~1.02, the above-mentioned second preset slope range can be 0.95~1.05, and the above-mentioned preset correlation coefficient threshold can be 0.98.

[0121] This embodiment can determine whether the lidar system corresponding to the filtered data set is mature based on the capture matrix statistics. If it is not mature, the subsequent steps will not be executed, further improving the efficiency of the hierarchical test.

[0122] The following embodiment illustrates the above-mentioned "step S106, calculating the uncertainty accuracy level of the target lidar system based on the target filtered data set".

[0123] Optionally, the wind speed statistical value is an average wind speed value, and the set condition may further include at least one height above the ground. Based on this, the process of "step S106, calculating the uncertainty accuracy level of the target lidar system according to the target filtered data set" may include B1 to B2:

[0124] B1. For each filtered data set included in the target filtered data set: classify the filtered data set according to the height above the ground to obtain a statistical value set corresponding to at least one height above the ground; determine the final accuracy corresponding to at least one height above the ground in the filtered data set based on the statistical value set corresponding to the at least one height above the ground; so as to obtain the final accuracy corresponding to at least one height above the ground in each filtered data set included in the target filtered data set.

[0125] During the tiered test, the final accuracy of the LiDAR system and the reference sensor (i.e., the sensor mounted on the wind tower) must be calculated at the same height. Therefore, for each filtered data set included in the target filtered data set, this step first categorizes the filtered data set by height above the ground, obtaining at least one statistical value set corresponding to each height above the ground. The final accuracy is then calculated based on the statistical value set obtained for each height above the ground.

[0126] Optionally, in the step of "determining, based on a set of statistical values ​​corresponding to at least one ground clearance, a final accuracy corresponding to at least one ground clearance in the filtered data set," the specific process may include B11 to B15:

[0127] B11. Calculate, based on a set of statistical values ​​corresponding to at least one ground clearance, a value and a value range of a preset environmental factor corresponding to at least one ground clearance.

[0128] At present, the known environmental variables that affect the lidar system include: wind shear, inflow angle and wind direction. In order to improve the accuracy of the uncertainty precision level calculated by this application, environmental factors such as wave height, turbulence intensity, precipitation, wind direction, temperature, air density, temperature difference between two different heights and cloud cover can also be analyzed. Based on this, the "preset environmental factors" in this step can be one or more of the above-mentioned environmental factors.

[0129] It can be understood that the value of each environmental factor included in the preset environmental factors can be determined based on the statistical value set corresponding to the corresponding ground clearance. That is, for each ground clearance, this step can calculate the value of the preset environmental factor corresponding to the ground clearance based on the statistical value set corresponding to the ground clearance. Here, the value of the preset environmental factor corresponding to the ground clearance refers to the value of the preset environmental factor determined based on the statistical value set corresponding to the ground clearance.

[0130] After determining that at least one height above the ground corresponds to a value of the preset environmental factor, it is also possible to determine a value range of the at least one height above the ground corresponding to the preset environmental factor.

[0131] B12. Determine the target environmental factor from the preset environmental factors based on the average wind speed value contained in the statistical value set corresponding to at least one height above the ground and the value of at least one preset environmental factor corresponding to the height above the ground, wherein the target environmental factor has a significant impact on the uncertainty accuracy level of the target lidar system.

[0132] In this step, it is necessary to determine the environmental factors that have a significant impact on the calculation of the uncertainty accuracy level from the preset environmental factors as target environmental factors.

[0133] Optionally, after determining the "environmental factors with significant influence", if there is a correlation between the determined environmental factors, for example, environmental factors A and B both have a significant influence on the calculation of the uncertainty precision level, and there is a correlation between A and B, then it is necessary to consider whether the influence of A on the uncertainty precision level is caused by B. If so, A is not included in the target environmental factors; similarly, if the influence of B on the uncertainty precision level is caused by A, B is not included in the target environmental factors. Based on this, after determining the "environmental factors with significant influence", only the environmental variables that directly affect the uncertainty precision level are retained, and the environmental variables that do not directly affect the uncertainty precision level are excluded to obtain the target environmental factors.

[0134] In an optional embodiment, the specific implementation process of this step may include the following B121 to B123:

[0135] B121. Calculate the wind speed deviation percentage corresponding to at least one height above the ground based on the wind speed average value included in the statistical value set corresponding to at least one height above the ground.

[0136] It can be understood that the average wind speed included in the statistical value set corresponding to a certain height above the ground includes the average wind speed corresponding to the wind speed collected by the lidar system and the average wind speed corresponding to the wind speed collected by the wind measurement tower. This step can calculate the wind speed deviation percentage corresponding to the height above the ground based on the average wind speed corresponding to the wind speed collected by the lidar system and the average wind speed corresponding to the wind speed collected by the wind measurement tower at a certain height above the ground.

[0137] Optionally, for each of the at least one ground clearance height, a calculation formula for the wind speed deviation percentage corresponding to the ground clearance height is:

[0138]

[0139] Among them, v RSD Refers to the average wind speed corresponding to the wind speed collected by the lidar system, v reference It refers to the average wind speed corresponding to the wind speed collected by the wind tower.

[0140] B122. Establish a third linear regression equation based on the value of the preset environmental factor corresponding to at least one height above the ground and the wind speed deviation percentage corresponding to at least one height above the ground, to obtain a third linear regression equation corresponding to the preset environmental factor for at least one height above the ground.

[0141] In this step, for each of the at least one height above the ground, the wind speed deviation percentage corresponding to the height above the ground zone can be used as the dependent variable, and the value of the preset environmental factor corresponding to the height above the ground can be used as the independent variable. A one-dimensional, two-parameter third linear regression equation is established based on the independent variable and the dependent variable.

[0142] B123. Determine, based on a third linear regression equation in which at least one ground clearance height corresponds to a preset environmental factor, the slope of the equation, the standard deviation of the preset environmental factor, and the correlation coefficient, as the slope of the equation in which at least one ground clearance height corresponds to the preset environmental factor, the standard deviation of the preset environmental factor, and the correlation coefficient.

[0143] For each of the at least one ground clearance height, this step can perform regression analysis based on the third linear regression equation of the ground clearance height corresponding to the preset environmental factor to obtain the equation slope (represented by m), the standard deviation of the preset environmental factor (represented by std) and the correlation coefficient (represented by R 2 Of course, by performing regression analysis, the deviation (represented by C) and the average value of the preset environmental factors (represented by avg) can also be calculated.

[0144] B124. Determine a target environmental factor from the preset environmental factors based on the slope of the equation corresponding to at least one height above the ground, the standard deviation of the preset environmental factor, and the correlation coefficient.

[0145] Specifically, for each of the at least one ground clearance heights, this step can first calculate the sensitivity of the ground clearance to the preset environmental factor based on the slope m of the equation corresponding to the preset environmental factor and the standard deviation std of the preset environmental factor; and then determine the target environmental factor from the preset environmental factors based on the sensitivity and correlation coefficient of the at least one ground clearance height to the preset environmental factor.

[0146] See Table 2 below for a clearer understanding of the relationship between the height above the ground, the preset environmental factors (i.e., independent variables), and the parameters and sensitivities calculated through regression analysis.

[0147] Table 2 Statistics of parameters and sensitivities calculated by regression analysis

[0148]

[0149] Optionally, the slope m of the equation of the height above the ground corresponding to the preset environmental factor and the standard deviation std of the preset environmental factor may be multiplied together, and the product is the sensitivity of the height above the ground corresponding to the preset environmental factor.

[0150] Optionally, the process of "determining the target environmental factor from the preset environmental factors based on the sensitivity and correlation coefficient of at least one height above the ground corresponding to the preset environmental factor" may include: for each environmental factor included in the preset environmental factors, as long as there is a height above the ground that meets the first condition or the second condition, the environmental factor is used as the target environmental factor. Here, the first condition is: the sensitivity of the height above the ground corresponding to the environmental factor is greater than or equal to the sensitivity threshold, and the second condition is: the product of the sensitivity of the height above the ground corresponding to the environmental factor and R (i.e., the square root of the correlation coefficient) is greater than or equal to the set product threshold. Optionally, the above-mentioned sensitivity threshold can be 0.5, and the above-mentioned set product threshold can be 0.1.

[0151] B13. Determine the maximum deviation of at least one ground clearance corresponding to the target environmental factor based on the slope and value range of the equation of at least one ground clearance corresponding to the target environmental factor.

[0152] Optionally, for each of at least one ground clearance height, the slope of the equation corresponding to the target environmental factor of the ground clearance is denoted as m, and the value range of the ground clearance corresponding to the target environmental factor is denoted as range, then the maximum deviation of the ground clearance corresponding to the target environmental factor is m*range.

[0153] In this step, the slope, value range, and maximum deviation of the equation corresponding to the target environmental factor at at least one height above the ground may be statistically analyzed to obtain the following Table 3 (taking the target environmental factors including wind shear index, inflow angle, vertical wind direction change, and wave height as an example).

[0154] Table 3 Statistics of equation slope, value range and maximum deviation of target environmental factors

[0155]

[0156] B14. For each of the at least one ground clearance height, calculate the initial precision corresponding to the ground clearance height based on the maximum deviation of the ground clearance height corresponding to the target environmental factor, to obtain the initial precision corresponding to the at least one ground clearance height.

[0157] Optionally, for each of the at least one ground clearance height, the square root of the sum of the squares of the maximum deviations of the ground clearance height from the target environmental factor may be used as the initial accuracy corresponding to the ground clearance height. For example, if the maximum deviations of the wind shear index, inflow angle, vertical wind direction change, and wave height corresponding to ground clearance height m1 are a, b, c, and d, respectively, then the initial accuracy corresponding to ground clearance height m1 is:

[0158] B15. Divide the initial accuracy corresponding to the at least one ground clearance by a preset value to obtain the final accuracy corresponding to the at least one ground clearance, and use the final accuracy corresponding to the at least one ground clearance in the filtered data set as the final accuracy corresponding to the at least one ground clearance.

[0159] In this step, the preset value can be For each of the at least one ground clearance height, the initial accuracy corresponding to the ground clearance height can be divided by Get the final accuracy corresponding to the height above the ground.

[0160] It is worth noting that for each filtered data set included in the target filtered data set, calculations can be performed according to steps B11 to B15 above, thereby obtaining the final accuracy corresponding to at least one ground clearance height under each filtered data set.

[0161] For example, if the target filtered data set includes four filtered data sets, and at least one of the heights above the ground is m1, m2, and m3, then a total of 12 final accuracies can be obtained through the calculation of B1.

[0162] B2. Determine the uncertainty accuracy level of the target lidar system based on the final accuracy corresponding to at least one ground clearance height under each filtered data set contained in the target filtered data set.

[0163] Optionally, this step may specifically include the following steps: calculating the sum of squares of the final accuracies corresponding to at least one height above the ground in the data set after target screening, and taking the square root of the sum of squares to obtain the uncertainty accuracy level of the target lidar system.

[0164] For example, as in the previous example, if the target filtered data set includes 4 filtered data sets, and at least one height above the ground is m1, m2 and m3, then 12 final accuracies can be obtained. The uncertainty accuracy level of the target lidar system obtained in this step refers to: the square root of the sum of the squares of the 12 final accuracies.

[0165] In summary, the embodiments of the present application can calculate the uncertainty accuracy level of the target LiDAR system. It is worth noting that this uncertainty accuracy level can only represent the uncertainty accuracy level of the same model LiDAR system as the target LiDAR system. If you need to determine the uncertainty accuracy level of other models of LiDAR systems, you can follow the steps provided in the embodiments of the present application to calculate the uncertainty accuracy level of other models of LiDAR systems.

[0166] An embodiment of the present application also provides a grading device for a laser radar system. The grading device for a laser radar system provided in an embodiment of the present application is described below. The grading device for a laser radar system described below and the grading method for a laser radar system described above can be referenced to each other.

[0167] See also Figure 3 , shows a schematic structural diagram of a grading device of a laser radar system provided in an embodiment of the present application, such as Figure 3 As shown, the grading device of the lidar system may include: a target data set acquisition module 301, an invalid data elimination module 302, a capture matrix statistics module 303, a quantity requirement satisfaction judgment module 304, a radar maturity judgment module 305 and an uncertainty calculation module 306.

[0168] The target data set acquisition module 301 is used to acquire a target data set, wherein the target data set includes at least three data sets consisting of statistical values ​​of data collected under set conditions by two lidar systems of the same model and wind towers located in two sea areas, the statistical values ​​at least including wind speed statistics, and the set conditions include at least one wave height.

[0169] The invalid data elimination module 302 is used to eliminate invalid data in the target data set to obtain a target filtered data set.

[0170] The capture matrix statistics module 303 is used to perform capture matrix statistics on the target filtered data set to obtain statistical results corresponding to the target filtered data set, wherein the capture matrix is ​​used to count the number of statistical values ​​in which the wave height is in each preset wave height interval and the wind speed statistical value is in each preset wind speed interval, as well as the total number of statistical values ​​and the number of wave height intervals in each preset wind speed interval. The number of wave height intervals in a preset wind speed interval refers to the number of preset wave height intervals in which the number of statistical values ​​in the preset wind speed interval is greater than or equal to the first number.

[0171] The quantity requirement satisfaction determination module 304 is configured to determine whether the quantity of statistical values ​​included in the target filtered data set meets a preset quantity requirement based on the statistical result corresponding to the target filtered data set.

[0172] The radar maturity judgment module 305 is used to determine whether the target lidar system is mature based on the statistical results corresponding to the target filtered data set if the quantity requirement is met and the situation judgment module determines that the number of statistical values ​​contained in the target filtered data set meets the preset quantity requirement, wherein the target lidar system includes at least two lidar systems of the same model.

[0173] The uncertainty calculation module 306 is used to calculate the uncertainty accuracy level of the target lidar system based on the target screened data set if the radar maturity judgment module determines that the target lidar system is mature.

[0174] The grading device of the laser radar system provided by the present application first obtains the target data set, then eliminates the invalid data in the target data set to obtain the target filtered data set, then performs capture matrix statistics on the target filtered data set to obtain the statistical results corresponding to the target filtered data set, and then determines whether the number of statistical values ​​contained in the target filtered data set meets the preset number requirements based on the statistical results corresponding to the target filtered data set. If so, it determines whether the target laser radar system is mature based on the statistical results corresponding to the target filtered data set. If the target laser radar system is mature, it calculates the uncertainty accuracy level of the target laser radar system based on the target filtered data set. It can be seen from this that the present application can determine whether the number of statistical values ​​contained in the target filtered data set meets the preset number requirements based on the statistical results after performing capture matrix statistics on the target filtered data set, and can determine whether the target laser radar system is mature. When the target laser radar system is mature, the present application can calculate the uncertainty accuracy level of the target laser radar system based on the target filtered data set.

[0175] In a possible implementation, the grading device of the lidar system provided in the present application may further include: an efficiency calculation module and an efficiency reference module.

[0176] The efficiency calculation module is used to determine the data efficiency based on the target filtered data set and the target data set.

[0177] The efficiency reference module is used to determine whether the target lidar system is mature based on the data efficiency, so as to perform capture matrix statistics on the target screened data set when the target lidar system is mature, and obtain the statistical results corresponding to the target screened data set.

[0178] In a possible implementation, the target filtered data set includes at least filtered data sets corresponding to three data sets.

[0179] Based on this, the capture matrix statistics module 303 can be specifically used to perform capture matrix statistics on each filtered data set included in the target filtered data set to obtain the statistical results corresponding to the filtered data set; so as to obtain the statistical results corresponding to each filtered data set included in the target filtered data set.

[0180] The quantity requirement satisfaction judgment module 304 can be specifically used to determine whether the number of statistical values ​​contained in each filtered data set contained in the target filtered data set meets the preset quantity requirement based on the statistical results corresponding to the filtered data set.

[0181] The radar maturity judgment module 305 can be specifically used to determine whether the lidar system corresponding to each filtered data set contained in the target filtered data set is mature according to the statistical results corresponding to the filtered data set, so as to obtain whether the lidar system corresponding to each filtered data set contained in the target filtered data set is mature. If the lidar systems corresponding to each filtered data set contained in the target filtered data set are all mature, then the target lidar system is determined to be mature.

[0182] In one possible implementation, the above-mentioned preset quantity requirement is that in the statistical results corresponding to the filtered data set, the total number of statistical values ​​under each preset wind speed interval is greater than or equal to the second number, and the number of wave height intervals under each preset wind speed interval is greater than or equal to the third number, and there are at least two preset wave height intervals that meet the preset quantity sub-requirements, and the preset quantity sub-requirements are that the number of statistical values ​​in the first wind speed interval and the second wind speed interval under a preset wave height interval is greater than or equal to the fourth number, and the total number of statistical values ​​under the preset wave height interval is greater than or equal to the fifth number.

[0183] In one possible implementation, when the radar maturity judgment module 305 determines whether the lidar system corresponding to the filtered data set is mature based on the statistical results corresponding to the filtered data set, it may include: a first equation establishment submodule and a radar maturity judgment submodule.

[0184] Among them, the first equation establishment submodule is used to establish a first linear regression equation for the wind speed statistical values ​​in each preset wave height interval in the statistical results corresponding to the filtered data set, and to establish a second linear regression equation for the wind speed statistical values ​​in all preset wave height intervals, so as to obtain the slope and correlation coefficient corresponding to each first linear regression equation, as well as the slope and correlation coefficient corresponding to the second linear regression equation.

[0185] The radar maturity judgment submodule is used to determine whether the lidar system corresponding to the filtered data set is mature based on the slopes and correlation coefficients corresponding to the first linear regression equations and the slopes and correlation coefficients corresponding to the second linear regression equations.

[0186] In a possible implementation, the wind speed statistic is an average wind speed value, and the set condition further includes at least one height above the ground. Then the uncertainty calculation module 306 may include: a final accuracy calculation submodule and an uncertainty calculation submodule.

[0187] Among them, the final accuracy calculation submodule is used to classify each filtered data set contained in the target filtered data set according to the height above the ground, obtain a statistical value set corresponding to at least one height above the ground, and determine the final accuracy corresponding to at least one height above the ground in the filtered data set based on the statistical value set corresponding to at least one height above the ground, so as to obtain the final accuracy corresponding to at least one height above the ground in each filtered data set contained in the target filtered data set.

[0188] The uncertainty calculation submodule is used to determine the uncertainty accuracy level of the target lidar system based on the final accuracy corresponding to at least one ground clearance height under each filtered data set contained in the target filtered data set.

[0189] In one possible implementation, the above-mentioned final accuracy calculation submodule may include: a first calculation submodule, a target environmental factor determination submodule, a second calculation submodule, a third calculation submodule and a fourth calculation submodule when determining the final accuracy corresponding to at least one height above the ground in the filtered data set based on a set of statistical values ​​corresponding to at least one height above the ground.

[0190] The first calculation submodule is configured to calculate a value and a value range of at least one height above the ground corresponding to a preset environmental factor based on a set of statistical values ​​corresponding to at least one height above the ground.

[0191] The target environmental factor determination submodule is used to determine the target environmental factor from the preset environmental factors based on the wind speed average value contained in the statistical value set corresponding to at least one height above the ground and the value of at least one preset environmental factor corresponding to the height above the ground, wherein the target environmental factor has a significant impact on the uncertainty accuracy level of the target lidar system.

[0192] The second calculation submodule is configured to determine a maximum deviation of at least one ground clearance corresponding to the target environmental factor according to a slope and a value range of an equation in which at least one ground clearance corresponds to the target environmental factor.

[0193] The third calculation submodule is configured to calculate, for each of the at least one ground clearance heights, an initial precision corresponding to the ground clearance height based on a maximum deviation of the ground clearance height corresponding to the target environmental factor, so as to obtain an initial precision corresponding to the at least one ground clearance height.

[0194] The fourth calculation submodule is used to divide the initial accuracy corresponding to the at least one height above the ground by a preset value to obtain the final accuracy corresponding to the at least one height above the ground as the final accuracy corresponding to the at least one height above the ground in the filtered data set.

[0195] In a possible implementation, the target environmental factor determination submodule may include: a wind speed deviation calculation submodule, a second equation establishment submodule, a target parameter determination submodule, and a target parameter reference submodule.

[0196] The wind speed deviation calculation submodule is configured to calculate the wind speed deviation percentage corresponding to at least one height above the ground based on the wind speed average value contained in the statistical value set corresponding to at least one height above the ground.

[0197] The second equation establishment submodule is used to establish a third linear regression equation based on the value of the preset environmental factor corresponding to at least one height above the ground and the wind speed deviation percentage corresponding to at least one height above the ground, so as to obtain a third linear regression equation in which at least one height above the ground corresponds to the preset environmental factor.

[0198] The target parameter determination submodule is used to determine the slope of the equation, the standard deviation of the preset environmental factors, and the correlation coefficient according to the third linear regression equation in which at least one ground clearance height corresponds to the preset environmental factors, as the slope of the equation in which at least one ground clearance height corresponds to the preset environmental factors, the standard deviation of the preset environmental factors, and the correlation coefficient.

[0199] The target parameter reference submodule is used to determine the target environmental factor from the preset environmental factors according to the slope of the equation corresponding to the preset environmental factor, the standard deviation of the preset environmental factor and the correlation coefficient of at least one height above the ground.

[0200] In a possible implementation, the uncertainty calculation submodule may include: a square sum calculation module and a square root module.

[0201] The square sum calculation module is used to calculate the square sum of the final precision corresponding to at least one height above the ground in the target filtered data set.

[0202] The square root module is used to perform square root on the sum of squares to obtain the uncertainty accuracy level of the target lidar system.

[0203] The embodiment of the present application also provides a classification device for a laser radar system. Optionally, Figure 4 The hardware structure diagram of the hierarchical device of the laser radar system is shown. Figure 4 , the hardware structure of the hierarchical device of the laser radar system may include: at least one processor 401, at least one communication interface 402, at least one memory 403 and at least one communication bus 404;

[0204] In the embodiment of the present application, the number of the processor 401, the communication interface 402, the memory 403, and the communication bus 404 is at least one, and the processor 401, the communication interface 402, and the memory 403 communicate with each other through the communication bus 404;

[0205] The processor 401 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention;

[0206] The memory 403 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory;

[0207] The memory 403 stores a program, and the processor 401 can call the program stored in the memory 403, and the program is used to:

[0208] Obtaining a target data set, wherein the target data set includes at least three data sets consisting of statistical values ​​of data collected under set conditions by two lidar systems of the same model and wind towers located in two sea areas, the statistical values ​​at least including wind speed statistics, and the set conditions including at least one wave height;

[0209] Eliminate invalid data from the target data set to obtain the target filtered data set;

[0210] Performing capture matrix statistics on the target filtered data set to obtain statistical results corresponding to the target filtered data set, wherein the capture matrix is ​​used to count the number of statistical values ​​in which wave heights are within each preset wave height interval and wind speed statistical values ​​are within each preset wind speed interval, as well as the total number of statistical values ​​and the number of wave height intervals in each preset wind speed interval, wherein the number of wave height intervals in a preset wind speed interval refers to the number of preset wave height intervals in which the number of statistical values ​​in the preset wind speed interval is greater than or equal to a first number;

[0211] Determine whether the number of statistical values ​​contained in the target filtered data set meets the preset number requirement based on the statistical results corresponding to the target filtered data set;

[0212] If the conditions are met, the target LiDAR system is determined to be mature based on the statistical results of the target screening data set. The target LiDAR system includes at least two LiDAR systems of the same model.

[0213] If the target lidar system is mature, the uncertainty accuracy level of the target lidar system is calculated based on the target screening data set.

[0214] Optionally, the detailed functions and extended functions of the program may refer to the above description.

[0215] An embodiment of the present application also provides a readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the classification method of the laser radar system as described above is implemented.

[0216] Optionally, the detailed functions and extended functions of the program may refer to the above description.

[0217] Finally, it should be noted that, in this document, relational terms such as and and the like are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus comprising the element.

[0218] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0219] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A classification method for a laser radar system, characterized in that: include: Obtaining a target data set, wherein the target data set includes at least three data sets consisting of statistical values ​​of data collected under set conditions by two lidar systems of the same model and wind towers located in two sea areas, the statistical values ​​at least including wind speed statistics, and the set conditions including at least one wave height; Eliminate invalid data from the target data set to obtain a target filtered data set; Performing capture matrix statistics on the target filtered data set to obtain statistical results corresponding to the target filtered data set, wherein the capture matrix is ​​used to count the number of statistical values ​​whose wave heights are within each preset wave height interval and whose wind speed statistical values ​​are within each preset wind speed interval, as well as the total number of statistical values ​​and the number of wave height intervals in each preset wind speed interval, wherein the number of wave height intervals in a preset wind speed interval refers to the number of preset wave height intervals whose number of statistical values ​​in the preset wind speed interval is greater than or equal to a first number; Determining, based on the statistical results corresponding to the target filtered data set, whether the number of statistical values ​​included in the target filtered data set meets a preset number requirement; If satisfied, a first linear regression equation is established for the wind speed statistical values ​​in each preset wave height interval in the statistical results corresponding to the target filtered data set, and a second linear regression equation is established for the wind speed statistical values ​​in all preset wave height intervals, so as to obtain the slope and correlation coefficient corresponding to each of the first linear regression equations, as well as the slope and correlation coefficient corresponding to the second linear regression equation, wherein the independent variables of the first linear regression equation and the second linear regression equation are the wind speed statistical values ​​collected by the laser radar system, and the dependent variables are the wind speed statistical values ​​collected by the wind measurement tower; If the slopes corresponding to the first linear regression equations and the slopes corresponding to the second linear regression equations are both within a first preset slope range, and the correlation coefficients corresponding to the first linear regression equations and the correlation coefficients corresponding to the second linear regression equations are both greater than or equal to a preset correlation coefficient threshold, then the laser radar system corresponding to the screened data set is determined to be mature; otherwise, the laser radar system corresponding to the screened data set is determined to be immature; if the laser radar system corresponding to each screened data set included in the target screened data set is mature, then the target laser radar system is determined to be mature, wherein the target laser radar system includes at least the two laser radar systems of the same model; If the target lidar system is mature, each filtered data set contained in the target filtered data set is classified according to the height above the ground and the final accuracy corresponding to each height above the ground is calculated. The square root of the sum of the squares of the final accuracy corresponding to each height above the ground under all filtered data sets is taken to obtain the uncertainty accuracy level of the target lidar system. The final accuracy is obtained by calculating the initial accuracy corresponding to each height above the ground and dividing it by a preset value. The initial accuracy is calculated using the maximum deviation of the target environmental factors.

2. The classification method of the laser radar system according to claim 1, characterized in that: Also includes: When the target laser radar system is mature, the capture matrix statistics of the target filtered data set are performed to obtain statistical results corresponding to the target filtered data set.

3. The classification method of the laser radar system according to claim 2, characterized in that: The target filtered data set at least includes the filtered data sets corresponding to the three data sets respectively; Performing capture matrix statistics on the target screened data set to obtain statistical results corresponding to the target screened data set includes: For each filtered data set included in the target filtered data set, performing capture matrix statistics on the filtered data set to obtain statistical results corresponding to the filtered data set; so as to obtain statistical results corresponding to each filtered data set included in the target filtered data set; The determining, based on the statistical results corresponding to the target filtered data set, whether the number of statistical values ​​included in the target filtered data set meets a preset number requirement includes: For each filtered data set included in the target filtered data set, determining, based on the statistical results corresponding to the filtered data set, whether the number of statistical values ​​included in the filtered data set meets the preset number requirement; Determining whether the target lidar system is mature based on the statistical results corresponding to the target screening data set includes: For each filtered data set included in the target filtered data set, determining whether the laser radar system corresponding to the filtered data set is mature according to the statistical results corresponding to the filtered data set; so as to obtain whether the laser radar system corresponding to each filtered data set included in the target filtered data set is mature; If the laser radar system corresponding to each filtered data set included in the target filtered data set is mature, it is determined that the target laser radar system is mature.

4. The classification method of the laser radar system according to claim 3, characterized in that: The preset quantity requirement is that in the statistical results corresponding to the filtered data set, the total number of statistical values ​​under each preset wind speed interval is greater than or equal to the second number, and the number of wave height intervals under each preset wind speed interval is greater than or equal to the third number, and there are at least two preset wave height intervals that meet the preset quantity sub-requirements. The preset quantity sub-requirements are that the number of statistical values ​​in the first wind speed interval and the second wind speed interval under a preset wave height interval is greater than or equal to the fourth number, and the total number of statistical values ​​under the preset wave height interval is greater than or equal to the fifth number.

5. The classification method of the laser radar system according to claim 1, characterized in that: The wind speed statistic value is the average wind speed value, and the setting condition further includes at least one height above the ground; For each filtered data set included in the target filtered data set, classify it according to the height above the ground and calculate the final accuracy corresponding to each height above the ground. Take the square root of the sum of the squares of the final accuracy corresponding to each height above the ground in all filtered data sets to obtain the uncertainty accuracy level of the target lidar system, including: For each filtered data set included in the target filtered data set: Classifying the filtered data set according to the height above the ground to obtain at least one statistical value set corresponding to each height above the ground; Determining, based on a set of statistical values ​​corresponding to the at least one height above the ground, a final accuracy corresponding to the at least one height above the ground in the filtered data set; To obtain the final accuracy corresponding to the at least one height above the ground in each filtered data set included in the target filtered data set; Calculating the sum of squares of the final accuracies corresponding to the at least one height above the ground in the target filtered data set; Taking the square root of the sum of squares, the uncertainty accuracy level of the target lidar system is obtained.

6. The classification method of the laser radar system according to claim 5, characterized in that: The determining, based on the statistical value set corresponding to the at least one ground clearance height, the final accuracy corresponding to the at least one ground clearance height in the filtered data set includes: Calculating, based on the statistical value sets corresponding to the at least one ground clearance, the value and value range of the preset environmental factor corresponding to the at least one ground clearance; Based on the average wind speed included in the statistical value set corresponding to the at least one ground clearance height and the value of the preset environmental factor corresponding to the at least one ground clearance height, a target environmental factor is screened from the preset environmental factors, wherein the slope of the equation of the preset environmental factor is obtained based on a third linear regression equation established with the wind speed deviation percentage corresponding to each ground clearance height as a dependent variable and the value of the corresponding preset environmental factor as an independent variable, wherein the target environmental factor has a significant impact on the uncertainty accuracy level of the target lidar system; Determining, based on the value range of the target environmental factor corresponding to the at least one ground clearance and the slope of the equation of the preset environmental factor corresponding to the target environmental factor, the maximum deviation of the at least one ground clearance corresponding to the target environmental factor, the maximum deviation being the product of the slope of the equation of the preset environmental factor corresponding to each target environmental factor and the value range thereof; For each of the at least one ground clearance height, calculating an initial precision corresponding to the ground clearance height based on a maximum deviation of the ground clearance height corresponding to the target environmental factor, to obtain an initial precision corresponding to each of the at least one ground clearance heights; The initial precision corresponding to the at least one ground clearance height is divided by a preset value to obtain a final precision corresponding to the at least one ground clearance height, which is used as the final precision corresponding to the at least one ground clearance height in the filtered data set.

7. The classification method of the laser radar system according to claim 6, characterized in that: The step of filtering the target environmental factor from the preset environmental factors based on the wind speed average value included in the statistical value set corresponding to the at least one height above the ground and the value of the preset environmental factor corresponding to the at least one height above the ground comprises: The wind speed deviation percentage corresponding to the at least one height above the ground is calculated based on the wind speed average value included in the statistical value set corresponding to the at least one height above the ground. The calculation formula for the wind speed deviation percentage is: Among them, v RSD Refers to the average wind speed corresponding to the wind speed collected by the lidar system, v reference Refers to the average wind speed corresponding to the wind speed collected by the wind tower; Establishing a third linear regression equation based on the value of the preset environmental factor corresponding to the at least one height above the ground and the wind speed deviation percentage corresponding to the at least one height above the ground, so as to obtain a third linear regression equation corresponding to the preset environmental factor for the at least one height above the ground; Determining, according to a third linear regression equation in which the at least one ground clearance height corresponds to the preset environmental factors, an equation slope, a preset environmental factor standard deviation, and a correlation coefficient as the equation slope, the preset environmental factor standard deviation, and the correlation coefficient in which the at least one ground clearance height corresponds to the preset environmental factors; The target environmental factor is determined from the preset environmental factors according to the slope of the equation in which the at least one height above the ground corresponds to the preset environmental factor, the standard deviation of the preset environmental factor, and the correlation coefficient.

8. A classification device for a laser radar system, characterized in that: include: Target data set acquisition module, invalid data elimination module, capture matrix statistics module, quantity requirement satisfaction judgment module, radar maturity judgment module and uncertainty calculation module; The target data set acquisition module is configured to acquire a target data set, wherein the target data set includes at least three data sets consisting of statistical values ​​of data collected under set conditions by two lidar systems of the same model and wind towers located in two sea areas, wherein the statistical values ​​include at least wind speed statistics, and the set conditions include at least one wave height; The invalid data elimination module is used to eliminate invalid data in the target data set to obtain a target filtered data set; The capture matrix statistics module is used to perform capture matrix statistics on the target filtered data set to obtain statistical results corresponding to the target filtered data set, wherein the capture matrix is ​​used to count the number of statistical values ​​in which the wave height is within each preset wave height interval and the wind speed statistical value is within each preset wind speed interval, as well as the total number of statistical values ​​and the number of wave height intervals in each preset wind speed interval, wherein the number of wave height intervals in a preset wind speed interval refers to the number of preset wave height intervals in which the number of statistical values ​​in the preset wind speed interval is greater than or equal to a first number; A quantity requirement satisfaction judgment module is used to determine whether the number of statistical values ​​contained in the target filtered data set meets the preset quantity requirement based on the statistical results corresponding to the target filtered data set; The radar maturity judgment module is used to determine if the quantity requirement is met and the situation judgment module determines that the number of statistical values ​​contained in the target filtered data set meets the preset quantity requirement, establish a first linear regression equation for the wind speed statistical values ​​in each preset wave height interval in the statistical results corresponding to the filtered data set, and establish a second linear regression equation for the wind speed statistical values ​​in all preset wave height intervals to obtain the slopes and correlation coefficients corresponding to each of the first linear regression equations, as well as the slopes and correlation coefficients corresponding to the second linear regression equations, wherein the independent variables of the first linear regression equation and the second linear regression equation are the wind speed statistical values ​​collected by the laser radar system, and the dependent variables are the wind speed statistical values ​​collected by the laser radar system. Wind speed statistics collected by the tower; if the slopes corresponding to the first linear regression equations and the slopes corresponding to the second linear regression equations are both within a first preset slope range, and the correlation coefficients corresponding to the first linear regression equations and the correlation coefficients corresponding to the second linear regression equations are both greater than or equal to a preset correlation coefficient threshold, then it is determined that the laser radar system corresponding to the filtered data set is mature; otherwise, it is determined that the laser radar system corresponding to the filtered data set is immature; if the laser radar systems corresponding to each filtered data set contained in the target filtered data set are mature, then it is determined that the target laser radar system is mature, wherein the target laser radar system includes at least the two laser radar systems of the same model; The uncertainty calculation module is used to classify each filtered data set contained in the target filtered data set according to the height above the ground and calculate the final accuracy corresponding to each height above the ground, if the radar maturity judgment module determines that the target lidar system is mature, and to take the square root of the sum of the squares of the final accuracy corresponding to each height above the ground in all filtered data sets to obtain the uncertainty accuracy level of the target lidar system. The final accuracy is obtained by calculating the initial accuracy corresponding to each height above the ground and dividing it by a preset value. The initial accuracy is calculated using the maximum deviation of the target environmental factors.

Images