Parameter tuning method, device, equipment, medium and product

Abstract

The invention discloses a parameter tuning method, device and equipment, a medium and a product, and relates to the technical field of data processing, and the method comprises the steps: receiving radar collection parameters, video data and mode conversion ADC data sent by data collection equipment; generating final upgrading firmware according to the radar acquisition parameters, the video data and the ADC data; and sending the final upgrading firmware to the data acquisition equipment, and performing parameter upgrading on the millimeter wave radar of the data acquisition equipment by the data acquisition equipment according to the final upgrading firmware to realize tuning, thereby obtaining a tuning result. Therefore, the problem that the accuracy and efficiency of manual debugging are not high enough in the existing millimeter wave radar signal processing parameter tuning process is solved, and the parameter tuning efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a parameter tuning method, device, equipment, medium and product. Background Art

[0002] With the rapid development of autonomous driving, intelligent transportation and industrial automation technologies, millimeter-wave radar, as an important sensor that can realize target detection and tracking in complex environments, is widely used in many fields such as automobile collision avoidance, lane keeping, and drone obstacle avoidance. Millimeter-wave radar has strong penetration ability and can work in severe weather conditions such as fog, rain and snow. Therefore, its importance in autonomous driving systems is becoming more and more prominent.

[0003] In the application of millimeter-wave radar, the signal processing algorithm has an important influence on the detection performance of the radar. The signal processing parameters of millimeter-wave radar include filtering, detection threshold, etc. The selection of these parameters is directly related to the detection capability, false detection rate and target positioning accuracy of the radar. The traditional parameter setting relies on manual experience and a large number of experimental debugging to determine the optimal parameters. In addition, data feedback relies on repeated manual operations. This manual debugging process is not only time-consuming and labor-intensive, but also difficult to obtain the optimal parameter combination in complex scenarios, resulting in the inability to fully utilize the detection performance of the millimeter-wave radar. In addition, due to the lack of effective true values ​​of the experimental results in real scenarios, the results cannot be effectively evaluated.

[0004] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of this application is to provide a parameter tuning method, device, equipment, medium and product, aiming to solve the technical problems of insufficient accuracy and efficiency of manual debugging in the existing millimeter-wave radar signal processing parameter tuning process.

[0006] To achieve the above purpose, the present application proposes a parameter tuning method, which is applied to a host computer and includes:

[0007] Receive radar acquisition parameters, video data and mode conversion ADC data sent by the data acquisition device;

[0008] Generate final upgrade firmware according to the radar acquisition parameters, video data and ADC data;

[0009] The final upgraded firmware is sent to the data acquisition device, and the data acquisition device upgrades the parameters of the millimeter-wave radar of the data acquisition device according to the final upgraded firmware to achieve tuning and obtain the tuning result.

[0010] In one embodiment, the step of generating the final upgrade firmware according to the radar acquisition parameters, video data and ADC data includes:

[0011] According to the radar acquisition parameters, generating a plurality of tuning parameter value groups by optimizing the parameters;

[0012] Extracting frames from the video data to obtain an image set, and annotating the image set to obtain a true value of a scene target;

[0013] Writing the plurality of tuning parameter value groups into a configuration file, and compiling based on the configuration file to obtain a plurality of upgrade firmwares;

[0014] Sending the several upgraded firmwares to the data acquisition device;

[0015] The millimeter-wave radar is upgraded according to the several upgraded firmwares, and the ADC data is fed back to the millimeter-wave radar after each upgrade, and the millimeter-wave radar is used to feed back the ADC data to obtain several millimeter-wave radar point cloud data groups;

[0016] Receiving a plurality of millimeter-wave radar point cloud data groups sent by the data acquisition device, and performing matching according to the plurality of millimeter-wave radar point cloud data groups by using the scene target true value to obtain a plurality of matching results;

[0017] The plurality of matching results are evaluated to obtain a plurality of evaluation results, and a final upgrade firmware is determined based on the plurality of evaluation results.

[0018] In one embodiment, the step of extracting frames from the video data to obtain an image set, and annotating the image set to obtain a true value of a scene target includes:

[0019] Extracting frames from the video data based on a preset frame rate to obtain an image set;

[0020] Annotating the image set by using an annotation tool to obtain annotation information, wherein the annotation information includes detection target, object bounding box, object category and spatial position information;

[0021] A scene target true value is generated according to the annotation information.

[0022] In one embodiment, the step of performing matching according to the plurality of millimeter wave radar point cloud data sets through the scene target true value to obtain a plurality of matching results comprises:

[0023] Projecting the scene target true value to the radar coordinate system through coordinate system change to obtain position information of the scene target true value in the radar coordinate system;

[0024] According to the position information, the plurality of millimeter radar point cloud data groups are matched by maximum weight matching until each group of millimeter radar point cloud data in the plurality of millimeter radar point cloud data groups is matched, thereby obtaining a plurality of matching results.

[0025] In one embodiment, the step of evaluating the plurality of matching results to obtain a plurality of evaluation results, and determining the final upgrade firmware based on the plurality of evaluation results includes:

[0026] Calculating the plurality of matching results to obtain a detection rate, a false detection rate, and a distance cost of each matching result;

[0027] Based on the detection rate, false detection rate and distance cost of the plurality of matching results, the plurality of matching results are evaluated by using preset evaluation weights to obtain a plurality of evaluation results;

[0028] A final upgrade firmware among the plurality of upgrade firmwares is determined based on the plurality of evaluation results.

[0029] In addition, to achieve the above purpose, the present application also proposes a parameter tuning method, which is applied to a data acquisition device, wherein the data acquisition device includes a millimeter wave radar and a camera device, and the method includes:

[0030] Based on the radar acquisition parameters of the millimeter wave radar, converting ADC data through the millimeter wave radar acquisition mode, and acquiring video data through the camera device;

[0031] Sending the radar acquisition parameters, video data and ADC data to a host computer, which generates a final upgrade firmware according to the radar acquisition parameters, video data and ADC data, and sends the final upgrade firmware to the data acquisition device;

[0032] According to the final upgraded firmware, the parameters of the millimeter wave radar are upgraded to achieve tuning and obtain a tuning result.

[0033] In addition, to achieve the above-mentioned purpose, the present application also proposes a parameter tuning device, which is applied to a host computer and includes:

[0034] A receiving module, used for receiving radar acquisition parameters, video data and ADC data sent by the data acquisition device;

[0035] A generation module, used to generate final upgrade firmware according to the radar acquisition parameters, video data and ADC data;

[0036] The tuning module is used to send the final upgraded firmware to the data acquisition device, and the data acquisition device upgrades the parameters of the millimeter-wave radar of the data acquisition device according to the upgraded firmware to achieve tuning and obtain a tuning result.

[0037] In addition, to achieve the above objectives, the present application also proposes a parameter tuning device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the parameter tuning method described above.

[0038] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the parameter tuning method described above are implemented.

[0039] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the parameter tuning method described above are implemented.

[0040] One or more technical solutions proposed in this application have at least the following technical effects:

[0041] A parameter tuning method, device, equipment, storage medium and computer program product proposed in the embodiment of the present application, by receiving radar acquisition parameters, video data and mode conversion ADC data sent by a data acquisition device; generating a final upgrade firmware according to the radar acquisition parameters, video data and ADC data; sending the final upgrade firmware to the data acquisition device, and the data acquisition device performs parameter upgrade on the millimeter-wave radar of the data acquisition device according to the final upgrade firmware to achieve tuning and obtain a tuning result. Thus, the host computer uses the radar acquisition parameters, video data and ADC data sent by the data acquisition device to analyze and verify, obtains the final upgrade firmware with the best effect, and then sends the final upgrade firmware to the data acquisition device, and performs parameter upgrade on the millimeter-wave radar through the data acquisition device to achieve tuning and obtain a tuning result, which solves the problem of accuracy and efficiency of manual debugging in the existing millimeter-wave radar signal processing parameter tuning process, and improves the efficiency of parameter tuning. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0044] Figure 1 A flow chart of the first embodiment of the parameter tuning method of the present application;

[0045] Figure 2 A schematic diagram of image true value annotation related to the parameter tuning method of this application;

[0046] Figure 3 The parameter tuning method for this application involves a schematic diagram of projecting the coordinates of the point cloud data in the radar coordinate system onto a 2D image plane;

[0047] Figure 4 A schematic diagram of the projection of a 2D true value bounding box to a radar coordinate system is shown in the parameter tuning method of this application;

[0048] Figure 5 A flow chart of the second embodiment of the parameter tuning method of the present application;

[0049] Figure 6 A brief flow chart of the parameter tuning method provided in Example 2 of the present application;

[0050] Figure 7 This is a schematic diagram of the module structure of the parameter tuning device according to an embodiment of the present application;

[0051] Figure 8 Schematic diagram of the device structure of the hardware operating environment involved in the parameter tuning method in the embodiment of the present application.

[0052] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0053] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0054] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0055] The main solution of the embodiment of the present application is: according to the radar acquisition parameters, generate several tuning parameter value groups by optimizing parameters; extract frames of the video data to obtain an image set, and annotate the image set to obtain the scene target true value; write the several tuning parameter value groups into a configuration file, and compile based on the configuration file to obtain several upgrade firmware; send the several upgrade firmware to the data acquisition device; upgrade the millimeter wave radar according to the several upgrade firmware, and after each upgrade, feed the ADC data back to the millimeter wave radar, and obtain several millimeter wave radar point cloud data groups by feeding back the ADC data through the millimeter wave radar; receive several millimeter wave radar point cloud data groups sent by the data acquisition device, and match them according to the several millimeter wave radar point cloud data groups through the scene target true value to obtain several matching results; evaluate the several matching results to obtain several evaluation results, and determine the final upgrade firmware based on the several evaluation results. The video data is framed based on a preset frame rate to obtain an image set; the image set is annotated by an annotation tool to obtain annotation information, the annotation information including detection target, object bounding box, object category and spatial position information; the scene target true value is generated according to the annotation information. The scene target true value is projected to the radar coordinate system by coordinate system change to obtain the position information of the scene target true value in the radar coordinate system; according to the position information, the plurality of millimeter radar point cloud data groups are matched by maximum weight matching until each group of millimeter radar point cloud data in the plurality of millimeter radar point cloud data groups is matched, and a plurality of matching results are obtained. The plurality of matching results are calculated to obtain the detection rate, false detection rate and distance cost of each matching result; based on the detection rate, false detection rate and distance cost of the plurality of matching results, the plurality of matching results are evaluated by a preset evaluation weight to obtain a plurality of evaluation results; based on the plurality of evaluation results, the final upgrade firmware among the plurality of upgrade firmware is determined. Based on the radar acquisition parameters of the millimeter-wave radar, the ADC data is converted through the millimeter-wave radar acquisition mode, and the video data is collected through the camera device; the radar acquisition parameters, video data and ADC data are sent to the host computer, and the host computer generates the final upgrade firmware according to the radar acquisition parameters, video data and ADC data, and sends the final upgrade firmware to the data acquisition device; according to the final upgrade firmware, the millimeter-wave radar is parameter upgraded to achieve tuning and obtain the tuning result. This solves the problem of accuracy and low efficiency of manual debugging in the existing millimeter-wave radar signal processing parameter tuning process, realizes parameter tuning, and improves the efficiency of parameter tuning.Based on the scheme of the present invention, a parameter tuning method is designed based on the problem that traditional parameter settings rely on manual experience, and the optimal parameters are determined through a large number of experimental debugging, and data re-injection relies on repeated manual operations by people. This method is difficult to obtain the optimal parameter combination, thus leading to low efficiency. The effectiveness of the parameter tuning method of the present invention is verified when the parameters are tuned. Finally, the efficiency of parameter tuning performed by the method of the present invention is significantly improved.

[0056] In this embodiment, for the convenience of description, the following description is made with the parameter tuning device as the execution subject.

[0057] Due to the rapid development of autonomous driving, intelligent transportation and industrial automation technologies in the existing technology, millimeter wave radar, as an important sensor that can realize target detection and tracking in complex environments, is widely used in many fields such as automobile collision avoidance, lane keeping, and drone obstacle avoidance. Millimeter wave radar has strong penetration ability and can work in severe weather conditions, such as fog, rain and snow. Therefore, its importance in autonomous driving systems is becoming more and more prominent. In the application process of millimeter wave radar, the signal processing algorithm has an important influence on the detection performance of the radar. The signal processing parameters of millimeter wave radar include filtering, detection threshold, etc. The selection of these parameters is directly related to the detection capability, false detection rate and target positioning accuracy of the radar. The traditional parameter setting relies on manual experience and determines the optimal parameters through a large number of experimental debugging. In addition, the data re-injection relies on repeated manual operations by people. This manual debugging process is not only time-consuming and labor-intensive, but also difficult to obtain the optimal parameter combination in complex scenarios, resulting in the inability to give full play to the detection performance of the millimeter wave radar. In addition, since the experimental results in real scenarios lack effective true values, the results cannot be effectively evaluated, resulting in a decrease in the efficiency of radar detection.

[0058] The present application provides a solution, in which radar acquisition parameters, video data and mode conversion ADC data sent by a data acquisition device are received in a host computer. At the same time, the obtained parameters and data are used to determine the optimal parameters, and the parameters are generated into a final upgrade firmware. The data acquisition device performs parameter upgrades on the millimeter-wave radar based on the final upgrade firmware to achieve tuning, obtain the tuning results, and provide users with better services.

[0059] It can be seen from the above embodiments that the present application receives radar acquisition parameters, video data, and mode conversion ADC data sent by a data acquisition device; generates a final upgrade firmware according to the radar acquisition parameters, video data, and ADC data; sends the final upgrade firmware to the data acquisition device, and the data acquisition device performs parameter upgrades on the millimeter-wave radar of the data acquisition device according to the final upgrade firmware to achieve tuning and obtain a tuning result. Thus, the host computer uses the radar acquisition parameters, video data, and ADC data sent by the data acquisition device to analyze and verify, obtains the final upgrade firmware with the best effect, and then sends the final upgrade firmware to the data acquisition device, and performs parameter upgrades on the millimeter-wave radar through the data acquisition device to achieve tuning and obtain a tuning result, which solves the problem of accuracy and inefficiency of manual debugging in the existing millimeter-wave radar signal processing parameter tuning process, and improves the efficiency of parameter tuning.

[0060] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a parameter tuning device, etc. The following takes the parameter tuning device as an example to illustrate this embodiment and the following embodiments.

[0061] Based on this, the present application embodiment provides a parameter tuning method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the parameter tuning method of the present application.

[0062] In this embodiment, the parameter tuning method is applied to a host computer, and the method includes steps S01 to S03:

[0063] Step S01, receiving radar acquisition parameters, video data and mode conversion ADC data sent by a data acquisition device;

[0064] Before explaining this embodiment, it should be clear that in the prior art, with the rapid development of autonomous driving, intelligent transportation and industrial automation technologies, millimeter wave radar, as an important sensor capable of detecting and tracking targets in complex environments, is widely used in many fields such as automobile collision avoidance, lane keeping, and drone obstacle avoidance. Millimeter wave radar has strong penetration capabilities and can work in adverse weather conditions, such as fog, rain and snow, so its importance in autonomous driving systems is becoming increasingly prominent.

[0065] In the actual use of millimeter-wave radar, the signal processing algorithm has an important impact on the detection performance of the radar. The signal processing parameters of millimeter-wave radar include filtering, detection threshold, etc. The selection of these parameters is directly related to the radar's detection capability, false detection rate and target positioning accuracy. The traditional parameter setting relies on manual experience and a large number of experimental debugging to determine the optimal parameters, and the data feedback relies on repeated manual operations. This manual debugging process is not only time-consuming and labor-intensive, but also difficult to obtain the optimal parameter combination in complex scenarios, resulting in the inability to fully utilize the detection performance of the millimeter-wave radar. In addition, due to the lack of effective true values ​​of the experimental results in real scenarios, the results cannot be effectively evaluated.

[0066] Therefore, in this embodiment, the radar acquisition parameters, video data and mode conversion ADC data sent by the data acquisition device are received by the host computer, wherein the host computer refers to the central computer or control unit in the vehicle system for managing and monitoring various on-board devices, control systems and data processing. It is responsible for coordinating and processing the operations between different subsystems in the vehicle to ensure the efficient and safe operation of the vehicle system, and the data acquisition device is a specific variety of sensors in the vehicle. The data acquisition device in this embodiment also specifically includes millimeter-wave radar, data acquisition board and camera equipment, and in the vehicle system, the host computer and the data acquisition device establish a normal two-way communication link (a two-way communication link refers to a communication method in which two devices can transmit data to each other. In the vehicle system, a two-way communication link is usually used between various electronic control units (ECU) of the vehicle to ensure that data can be transmitted bidirectionally between the host computer and the slave computer).

[0067] Step S02, generating final upgrade firmware according to the radar acquisition parameters, video data and ADC data;

[0068] After obtaining the radar acquisition parameters, video data and ADC data of the data acquisition equipment, corresponding analysis can be performed. Among them, the application of radar acquisition parameters in vehicle systems is mainly used for environmental perception and obstacle detection, especially in autonomous driving and advanced driver assistance systems (ADAS). Radar is a key technology. Radar sensors acquire information about the surrounding environment by emitting electromagnetic waves and receiving return signals. The parameters they collect are crucial for subsequent decision-making and control. The focus of this embodiment is to achieve the tuning of radar acquisition parameters, while video data and ADC data are used for subsequent verification of the effectiveness of radar acquisition parameters.

[0069] Before obtaining the above-mentioned final upgrade firmware, this embodiment also needs to generate a large number of tuning parameter value groups to generate the upgrade firmware, and use the generated several upgrade firmware to iteratively test the millimeter-wave radar. After all the upgrade firmware tests are completed, the final upgrade firmware with the best effect can be obtained.

[0070] Step S03, sending the final upgraded firmware to the data acquisition device, and the data acquisition device performing parameter upgrade on the millimeter-wave radar of the data acquisition device according to the final upgraded firmware to achieve tuning and obtain a tuning result.

[0071] After the final upgrade firmware has been determined, it is sent to the data acquisition device, and the millimeter wave radar is upgraded according to the final upgrade firmware through the data acquisition device to achieve tuning, and the tuning result is obtained. Among them, the millimeter wave radar (Millimeter Wave Radar, MMW radar for short) is a radar system operating in the millimeter wave frequency band (usually between 30GHz and 300GHz). Due to its shorter wavelength, the millimeter wave radar can provide higher resolution, so it is widely used in autonomous driving, vehicle assisted driving system (ADAS), radar imaging, object detection and tracking and other fields. The working principle of the millimeter wave radar is similar to that of the traditional radar. It detects the position, speed and distance of the target by emitting high-frequency electromagnetic waves (usually millimeter waves) and receiving the signal reflected from the target. Due to the high frequency of the millimeter wave radar, its wavelength is very short (usually between 1 mm and 10 mm), which makes it have a higher spatial resolution and can more accurately identify small objects, details and targets in complex environments.

[0072] Specifically, the above step S02, the step of generating the final upgrade firmware according to the radar acquisition parameters, video data and ADC data includes:

[0073] Step S021, generating a plurality of tuning parameter value groups by optimizing parameters according to the radar acquisition parameters;

[0074] Step S022, extracting frames from the video data to obtain an image set, and annotating the image set to obtain a true value of a scene target;

[0075] Step S023, writing the plurality of tuning parameter value groups into a configuration file, and compiling based on the configuration file to obtain a plurality of upgrade firmwares;

[0076] Step S024, sending the several upgraded firmware to the data acquisition device;

[0077] Step S025, upgrading the millimeter-wave radar according to the plurality of upgraded firmwares, and feeding the ADC data back to the millimeter-wave radar after each upgrade, and obtaining a plurality of millimeter-wave radar point cloud data groups by feeding back the ADC data through the millimeter-wave radar;

[0078] Step S026, receiving a plurality of millimeter wave radar point cloud data groups sent by the data acquisition device, and performing matching according to the plurality of millimeter wave radar point cloud data groups by using the scene target true value to obtain a plurality of matching results;

[0079] Step S027, evaluating the plurality of matching results to obtain a plurality of evaluation results, and determining a final upgrade firmware based on the plurality of evaluation results.

[0080] In order to obtain more accurate acquisition parameters, this embodiment generates multiple sets of parameter values ​​of parameters to be tuned through an optimization algorithm (the optimization algorithm refers to a genetic algorithm), and then writes each set of parameter values ​​into the configuration file in turn, and compiles the source program to obtain the firmware to be upgraded. The compilation operation, OTA upgrade, and ADC data re-injection on the host computer can all be operated by an automated window control tool written in Python. The OTA upgrade pushes the firmware with new parameters to the millimeter-wave radar device for upgrading. By re-injecting the original ADC data, point cloud-level data under the new parameter combination can be obtained to verify the effect of millimeter-wave radar signal processing under different parameter combinations.

[0081] In order to verify the acquisition effect of the parameters, this embodiment also obtains the true value of the scene target for effect verification. After the upgrade firmware is sent to the millimeter-wave radar and the ADC data is fed back, the millimeter-wave radar in the data acquisition device can be used to process the ADC data through the new parameters to obtain each millimeter-wave radar point cloud data group of the upgraded firmware, and then the obtained millimeter-wave radar point cloud data group is sent to the host computer;

[0082] The host computer performs corresponding matching and evaluation based on the millimeter-wave radar point cloud data group and the scene target true value to obtain the best parameter group, and determines that the upgrade firmware corresponding to the best parameter group is the final upgrade firmware.

[0083] More specifically, the specific steps of extracting frames from the video data to obtain an image set and annotating the image set to obtain the true value of the scene target in the above step S22 include:

[0084] Step S0221, extracting frames from the video data based on a preset frame rate to obtain an image set;

[0085] Step S0222, annotating the image set by using an annotation tool to obtain annotation information, wherein the annotation information includes detection target, object bounding box, object category and spatial position information;

[0086] Step S0223, generating a scene target true value according to the annotation information.

[0087] In the fields of target detection, autonomous driving, computer vision, etc., "ground truth" refers to the real labeled data of the target position, category and related attributes in a specific scene or image. It is usually obtained by manual annotation or other precise measurement methods. It is used as the standard answer for training, verifying and testing machine learning models. Therefore, in order to obtain the ground truth of the scene target for result verification, this embodiment extracts frames from the video data at a fixed frame rate to obtain several representative video frame images, ensuring that the number of frames is dense enough to cover the entire time period of interest. After obtaining the synchronized video frames, such as Figure 2 As shown, professional annotation tools are used to annotate the scene targets in each frame of the image. The annotated targets are the main detection objects of the millimeter-wave radar, which can be vehicles, pedestrians, etc. The true value data of each target should include accurate object bounding boxes, categories, and spatial location information. These annotated images will serve as reference standards for subsequent algorithm optimization.

[0088] Furthermore, in order to obtain the optimal radar parameters, the millimeter wave radar point cloud data group is matched and evaluated in this embodiment, so the above step S026, according to the several millimeter wave radar point cloud data groups, matches the scene target true value, and obtains several matching results, including:

[0089] Step S0261, projecting the scene target true value to the radar coordinate system by changing the coordinate system, and obtaining the position information of the scene target true value in the radar coordinate system;

[0090] Step S0262: Match the plurality of millimeter radar point cloud data groups by maximum weight matching according to the position information, until each group of millimeter radar point cloud data in the plurality of millimeter radar point cloud data groups is matched, thereby obtaining a plurality of matching results.

[0091] The point cloud data is obtained by re-injecting the original ADC data. By comparing the timestamps of the video data and the millimeter-wave radar point cloud data, the millimeter-wave radar point cloud data corresponding to each frame of the video image is accurately indexed. The target true value data in the video image uses the image coordinate system, while the millimeter-wave radar point cloud data is in the radar coordinate system. The bounding box of the target true value in the image coordinate system is projected to the radar coordinate system through the coordinate system transformation. According to the position information of the true value bounding box in the radar coordinate system and the point cloud position information, the maximum weight matching method is used to perform one-to-one matching between the point cloud and the true value to obtain the matching results of each group of millimeter-wave point cloud data.

[0092] The specific matching in this embodiment can be: after calibrating the intrinsic and extrinsic matrix, the projection of the three-dimensional point in the world coordinate system to the image coordinate system is calculated. However, the matrix operation from the image coordinate system to the radar coordinate system is irreversible, so the transmission transformation method is used instead of the inverse operation. First, a frame of example point cloud data is used to calculate the corresponding 2D coordinates in the image coordinate system through the intrinsic and extrinsic parameters to obtain multiple 2D coordinate and radar coordinate matching pairs. Then, the 2D coordinates are used as the source coordinates and the radar coordinates are used as the target coordinates to calculate the transmission transformation matrix H to obtain the coordinate mapping relationship from 2D to radar point cloud. The coordinates of the point cloud in the radar coordinate system are projected onto the 2D image plane as shown in FIG. Figure 3 As shown in Figure 2, the red dots represent the radar point cloud, and the 2D ground truth bounding box is projected into the radar coordinate system as Figure 4 As shown in the figure, the purple polygon represents the true value bounding box, the blue triangle represents the center of the true value box, the red point represents the radar point cloud, and the marked red point represents the radar point cloud that successfully matches the true value bounding box.

[0093] It should be noted that after obtaining the position information of the true value bounding box coordinate transformation, the maximum weight matching method is used to perform one-to-one matching between the point cloud and the true value according to the position information of the true value bounding box in the radar coordinate system and the point cloud position information. The entire matching process can be divided into two maximum weight matchings. The detailed process of the first maximum weight matching is as follows:

[0094] (1) Graph construction: Create an undirected graph to represent the relationship between the ground-truth bounding box and the point cloud. Traverse each ground-truth bounding box and create a node for each bounding box. The node is named gt_x, where x is the index of the ground-truth value.

[0095] (2) Adding edges: Traverse all point clouds, and for each point cloud, check whether it is within a bounding box of a true value. If the point cloud is within the bounding box of the true value, calculate the distance between the point and the center of the bounding box, and calculate a score based on the distance, where:

[0096]

[0097] If the point cloud is not within the bounding box of the true value, score = None. For points whose scores are not None, an edge from the true value node to the point cloud node is added to the graph, and the weight of the edge is the calculated score.

[0098] (3) Maximum weight matching: The maximum weight matching method is used to find the maximum weight match and obtain the point cloud index that matches the true value bounding box. The second maximum weight matching object is the true value bounding box and point cloud that failed to match in the first match. The second match changes the rule of adding edges. Specifically, the length of the preset search radius is determined according to the category of the target true value box. For large targets such as trucks or buses, a larger search radius is set. Then, with the true value box as the center of the circle, for each point cloud that has not been successfully matched, check whether its coordinates are within the circle established by a certain true value bounding box. If the point cloud is within the true value bounding box, calculate the distance between the point and the center of the bounding box, and calculate a score based on the distance, where

[0099]

[0100] If the point cloud is not within the circle established by the true value bounding box, score = None. For points whose scores are not None, an edge from the true value node to the point cloud node is added to the graph, and the weight of the edge is the calculated score.

[0101] The above step S027, evaluating the plurality of matching results to obtain a plurality of evaluation results, and determining the final step of upgrading the firmware based on the plurality of evaluation results, includes:

[0102] Step S0271, calculating the plurality of matching results to obtain a detection rate, a false detection rate and a distance cost of each matching result;

[0103] Step S0272, based on the detection rate, false detection rate and distance cost of the plurality of matching results, the plurality of matching results are evaluated by using preset evaluation weights to obtain a plurality of evaluation results;

[0104] Step S0273: determining a final upgrade firmware among the plurality of upgrade firmwares based on the plurality of evaluation results.

[0105] The evaluation results of the new parameters are calculated based on the matching results of each frame. The evaluation results are mainly divided into three indicators, namely detection rate, false detection rate and distance cost. The detection rate refers to the proportion of the target true value that is successfully matched to the point cloud. This indicator is used to evaluate the effective detection capability of the radar for the target under the current parameter setting. The higher the value, the more accurately the radar can detect the target. The false detection rate refers to the proportion of the point cloud that is not successfully matched to the true value target. This indicator reflects the false detection in the radar signal processing, that is, whether the radar detects the wrong point cloud or noise. The lower the false detection rate, the cleaner and more accurate the radar data under the parameter setting. The distance cost is the sum of the distances from the point cloud to the center of the true value frame in each set of matching pairs. The smaller the distance cost, the more accurately the point cloud data reflects the position of the target true value.

[0106] The distance cost calculation formula is as follows:

[0107]

[0108] Among them, dist(P i ,G i ) represents the point cloud point P in the i-th matching pair i and the target truth value G i The smaller the distance cost, the more accurately the point cloud data reflects the position of the target truth.

[0109] In this embodiment, the evaluation weights are also explained, that is, according to different usage requirements, corresponding weights can be set for the detection rate, false detection rate and distance cost to obtain radar detection parameters that better meet user needs. In addition, this embodiment can also use judgment rules. The optimal judgment rule is to give priority to the parameter with the highest detection rate. If the detection rates are the same, then select the parameter with the lowest false detection rate. If the false detection rates are also the same, then select the parameter with the lowest distance cost.

[0110] This embodiment adopts the above scheme, specifically by receiving radar acquisition parameters, video data and mode conversion ADC data sent by the data acquisition device; generating the final upgrade firmware according to the radar acquisition parameters, video data and ADC data; sending the final upgrade firmware to the data acquisition device, and the data acquisition device performs parameter upgrade on the millimeter-wave radar of the data acquisition device according to the final upgrade firmware to achieve tuning and obtain the tuning result. Thus, the host computer uses the radar acquisition parameters, video data and ADC data sent by the data acquisition device to analyze and verify, obtains the final upgrade firmware with the best effect, and then sends the final upgrade firmware to the data acquisition device, and performs parameter upgrade on the millimeter-wave radar through the data acquisition device to achieve tuning and obtain the tuning result, which solves the problem of accuracy and low efficiency of manual debugging in the existing millimeter-wave radar signal processing parameter tuning process and improves the efficiency of parameter tuning.

[0111] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 5 The parameter tuning method is also applied to a data acquisition device, which includes a millimeter wave radar and a camera device. The method includes steps S04 to S06:

[0112] Step S04, based on the radar acquisition parameters of the millimeter wave radar, converting the ADC data through the millimeter wave radar acquisition mode, and acquiring video data through the camera device;

[0113] Step S05, sending the radar acquisition parameters, video data and ADC data to a host computer, the host computer generates a final upgrade firmware according to the radar acquisition parameters, video data and ADC data, and sends the final upgrade firmware to the data acquisition device;

[0114] Step S06: According to the final upgraded firmware, the parameters of the millimeter wave radar are upgraded to achieve tuning and obtain a tuning result.

[0115] It should be clear that the data acquisition device in this embodiment and the host computer together form a general control system, and the two assist each other. The data acquisition device in this embodiment includes a millimeter wave radar, a data acquisition board, and a camera device.

[0116] In this embodiment, the control software of the host computer configures the radar acquisition parameters to ensure that the millimeter-wave radar can correctly output the original ADC data. At the same time, the video data is captured in real time. The host computer receives the original ADC data of the millimeter-wave radar and the video data of the camera in real time, and stores the data in the local file system for subsequent processing. ADC (Analog-to-Digital Converter) is an electronic device that converts continuous analog signals into discrete digital signals. In electronic systems, ADC is a key component that converts analog signals (such as temperature, voltage, sound, etc.) into digital formats that can be processed by digital processors (such as microcontrollers, computers, etc.);

[0117] The basic principle of ADC is:

[0118] ① Input signal: usually an analog signal, such as voltage;

[0119] ② Sampling: ADC samples the analog signal at fixed time intervals;

[0120] ③Quantization: After sampling, the amplitude of the analog signal is divided into several discrete values, and the accuracy of quantization is determined by the resolution of the ADC;

[0121] ④Encoding: Convert the quantized signal into a digital signal in binary format.

[0122] The video data and ADC data are then sent to the host computer, which iteratively optimizes the radar acquisition parameters, video data, ADC and millimeter-wave radar, and determines that the upgrade firmware corresponding to the acquisition parameters with the best effect is the final upgrade firmware;

[0123] Finally, the data acquisition device adjusts the acquisition parameters of the millimeter-wave radar by finally upgrading the firmware to obtain the tuning results.

[0124] To help understand the implementation process of the parameter tuning method obtained by combining this embodiment with the above-mentioned embodiment 1, please refer to Figure 6 , Figure 6 A brief flow chart of a parameter tuning method is provided, specifically:

[0125] Step 1: Make the host computer communicate with the millimeter-wave radar and camera normally, and use the millimeter-wave radar and camera to collect the millimeter-wave radar original ADC data and video data;

[0126] Step 2: Extract multiple frames of video and index the millimeter-wave radar ADC data at the corresponding time according to the timestamp, and mark the scene target true value on the extracted frame images;

[0127] Step 3: Generate the parameter values ​​of the parameters to be tuned through the optimization algorithm and write them into the configuration file. Use the automation tool to implement compilation, OTA upgrade, and ADC data re-injection;

[0128] Step 4: Match the point cloud data obtained by data re-injection with the target true value through the maximum weight matching method;

[0129] Step 5: Evaluate the matching results and give the evaluation results of the group of parameter values;

[0130] Step 6: Jump to step 3 and iterate again until the termination condition is met, save the parameter value of the optimal evaluation result, and output it as the final upgrade firmware.

[0131] This embodiment adopts the above scheme, specifically based on the radar acquisition parameters of the millimeter-wave radar, converts ADC data through the millimeter-wave radar acquisition mode, and collects video data through the camera device; sends the radar acquisition parameters, video data and ADC data to the host computer, and the host computer generates the final upgrade firmware according to the radar acquisition parameters, video data and ADC data, and sends the final upgrade firmware to the data acquisition device; according to the final upgrade firmware, the millimeter-wave radar is parameter upgraded to achieve tuning and obtain the tuning result. Thus, the host computer uses the radar acquisition parameters, video data and ADC data sent by the data acquisition device to analyze and verify, obtain the final upgrade firmware with the best effect, and then sends the final upgrade firmware to the data acquisition device, and the millimeter-wave radar is parameter upgraded through the data acquisition device to achieve tuning and obtain the tuning result, which solves the problem of accuracy and efficiency of manual debugging in the existing millimeter-wave radar signal processing parameter tuning process, and improves the efficiency of parameter tuning.

[0132] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the parameter tuning method of the present application. More simple transformations based on this technical concept are all within the protection scope of the present application.

[0133] This application also provides a parameter tuning device, please refer to Figure 7 The parameter tuning device is applied to a host computer, and the device comprises:

[0134] A receiving module, used for receiving radar acquisition parameters, video data and ADC data sent by the data acquisition device;

[0135] A generation module, used to generate final upgrade firmware according to the radar acquisition parameters, video data and ADC data;

[0136] The tuning module is used to send the final upgraded firmware to the data acquisition device, and the data acquisition device upgrades the parameters of the millimeter-wave radar of the data acquisition device according to the upgraded firmware to achieve tuning and obtain a tuning result.

[0137] The parameter tuning device provided by the present application adopts the parameter tuning method in the above embodiment, which can solve the technical problems of low accuracy and efficiency of manual debugging in the existing millimeter-wave radar signal processing parameter tuning process. Compared with the prior art, the beneficial effects of the parameter tuning device provided by the present application are the same as those of the parameter tuning method provided by the above embodiment, and the other technical features in the parameter tuning device are the same as those disclosed in the above embodiment method, which will not be repeated here.

[0138] The present application provides a parameter tuning device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the parameter tuning method in the above-mentioned embodiment 1.

[0139] Reference below Figure 8 , which shows a schematic diagram of the structure of a parameter tuning device suitable for implementing the embodiment of the present application. The parameter tuning device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 8The parameter tuning device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0140] like Figure 8 As shown, the parameter tuning device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the parameter tuning device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the parameter tuning device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a parameter tuning device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0141] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0142] The parameter tuning device provided by the present application adopts the parameter tuning method in the above embodiment, which can solve the technical problems of low accuracy and efficiency of manual debugging in the existing millimeter-wave radar signal processing parameter tuning process. Compared with the prior art, the beneficial effects of the parameter tuning device provided by the present application are the same as the beneficial effects of the parameter tuning method provided by the above embodiment, and the other technical features in the parameter tuning device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0143] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0144] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0145] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the parameter tuning method in the above-mentioned embodiment.

[0146] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0147] The computer-readable storage medium may be included in the parameter tuning device; or may exist independently without being assembled into the parameter tuning device.

[0148] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the parameter tuning device, the parameter tuning device: receives the radar acquisition parameters, video data and mode conversion ADC data sent by the data acquisition device; generates the final upgrade firmware according to the radar acquisition parameters, video data and ADC data; sends the final upgrade firmware to the data acquisition device, and the data acquisition device performs parameter upgrade on the millimeter-wave radar of the data acquisition device according to the final upgrade firmware to achieve tuning and obtain the tuning result.

[0149] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0150] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0151] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0152] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned parameter tuning method, and can solve the technical problems of low accuracy and efficiency of manual debugging in the existing millimeter-wave radar signal processing parameter tuning process. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the parameter tuning method provided in the above-mentioned embodiment, and will not be elaborated here.

[0153] The present application also provides a computer program product, including a computer program, which implements the steps of the parameter tuning method as described above when the computer program is executed by a processor.

[0154] The computer program product provided by the present application can solve the technical problems of low accuracy and efficiency of manual debugging in the existing millimeter wave radar signal processing parameter tuning process. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as those of the parameter tuning method provided by the above embodiment, and will not be elaborated here.

[0155] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A parameter tuning method, characterized in that: The method is applied to a host computer, and the method comprises: Receive radar acquisition parameters, video data and mode conversion ADC data sent by the data acquisition device; Generate final upgrade firmware according to the radar acquisition parameters, video data and ADC data; The final upgraded firmware is sent to the data acquisition device, and the data acquisition device upgrades the millimeter-wave radar of the data acquisition device according to the final upgraded firmware to achieve parameter tuning and obtain a tuning result.

2. The method according to claim 1, characterized in that The step of generating the final upgrade firmware according to the radar acquisition parameters, video data and ADC data comprises: According to the radar acquisition parameters, generating a plurality of tuning parameter value groups by optimizing the parameters; Extracting frames from the video data to obtain an image set, and annotating the image set to obtain a true value of a scene target; Writing the plurality of tuning parameter value groups into a configuration file, and compiling based on the configuration file to obtain a plurality of upgrade firmwares; Sending the several upgraded firmwares to the data acquisition device; The millimeter-wave radar is upgraded according to the several upgraded firmwares, and the ADC data is fed back to the millimeter-wave radar after each upgrade, and the millimeter-wave radar is used to feed back the ADC data to obtain several millimeter-wave radar point cloud data groups; Receiving a plurality of millimeter-wave radar point cloud data groups sent by the data acquisition device, and performing matching according to the plurality of millimeter-wave radar point cloud data groups by using the scene target true value to obtain a plurality of matching results; The plurality of matching results are evaluated to obtain a plurality of evaluation results, and a final upgrade firmware is determined based on the plurality of evaluation results.

3. The method according to claim 2, characterized in that The step of extracting frames from the video data to obtain an image set, and annotating the image set to obtain a true value of a scene target comprises: Extracting frames from the video data based on a preset frame rate to obtain an image set; Annotating the image set by using an annotation tool to obtain annotation information, wherein the annotation information includes detection target, object bounding box, object category and spatial position information; A scene target true value is generated according to the annotation information.

4. The method according to claim 2, characterized in that The step of performing matching according to the plurality of millimeter wave radar point cloud data groups through the scene target true value to obtain a plurality of matching results comprises: Projecting the scene target true value to the radar coordinate system through coordinate system change to obtain position information of the scene target true value in the radar coordinate system; According to the position information, the plurality of millimeter radar point cloud data groups are matched by maximum weight matching until each group of millimeter radar point cloud data in the plurality of millimeter radar point cloud data groups is matched, thereby obtaining a plurality of matching results.

5. The method according to claim 2, characterized in that The step of evaluating the plurality of matching results to obtain a plurality of evaluation results, and determining the final upgrade firmware based on the plurality of evaluation results comprises: Calculating the plurality of matching results to obtain a detection rate, a false detection rate, and a distance cost of each matching result; Based on the detection rate, false detection rate and distance cost of the plurality of matching results, the plurality of matching results are evaluated by using preset evaluation weights to obtain a plurality of evaluation results; A final upgrade firmware among the plurality of upgrade firmwares is determined based on the plurality of evaluation results.

6. A parameter tuning method, characterized in that: The method is applied to a data acquisition device, the data acquisition device includes a millimeter wave radar and a camera device, and the method includes: Based on the radar acquisition parameters of the millimeter wave radar, converting ADC data through the millimeter wave radar acquisition mode, and acquiring video data through the camera device; Sending the radar acquisition parameters, video data and ADC data to a host computer, which generates a final upgrade firmware according to the radar acquisition parameters, video data and ADC data, and sends the final upgrade firmware to the data acquisition device; According to the final upgraded firmware, the parameters of the millimeter wave radar are upgraded to achieve tuning and obtain a tuning result.

7. A parameter tuning device, characterized in that: The device is applied to a host computer, and the device comprises: A receiving module, used for receiving radar acquisition parameters, video data and ADC data sent by the data acquisition device; A generation module, used to generate final upgrade firmware according to the radar acquisition parameters, video data and ADC data; The tuning module is used to send the final upgraded firmware to the data acquisition device, and the data acquisition device upgrades the parameters of the millimeter-wave radar of the data acquisition device according to the upgraded firmware to achieve tuning and obtain a tuning result.

8. A parameter tuning device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the parameter tuning method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the parameter tuning method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the parameter tuning method according to any one of claims 1 to 6 are implemented.

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