阅读说明：本技术 一种全球导航卫星数据校准方法、装置、终端及存储介质 (Global navigation satellite data calibration method, device, terminal and storage medium ) 是由 史文中 包胜 于 2021-08-06 设计创作，主要内容包括：本发明公开了一种全球导航卫星数据校准方法、装置、终端及存储介质,所述方法包括：获取第一全球导航卫星数据和雷达数据,根据所述第一全球导航卫星数据生成第一轨迹数据,根据所述雷达数据生成第二轨迹数据和点云地图；根据所述点云地图确定偏移数据,所述偏移数据用于反映所述第一轨迹数据和所述第二轨迹数据之间的偏差；获取第二全球导航卫星数据,根据所述偏移数据对所述第二全球导航卫星数据进行校准,其中,所述第一全球导航卫星数据的获取时间早于所述第二全球导航卫星数据的获取时间。本发明无需采用惯性传感器,因此可以有效地解决现有技术中在没有惯性传感器的情况下,无法通过LiDAR对GNSS进行校准的问题。(The invention discloses a global navigation satellite data calibration method, a device, a terminal and a storage medium, wherein the method comprises the following steps: acquiring first global navigation satellite data and radar data, generating first track data according to the first global navigation satellite data, and generating second track data and a point cloud map according to the radar data; determining offset data from the point cloud map, the offset data reflecting a deviation between the first trajectory data and the second trajectory data; acquiring second global navigation satellite data, and calibrating the second global navigation satellite data according to the offset data, wherein the acquisition time of the first global navigation satellite data is earlier than the acquisition time of the second global navigation satellite data. The invention does not need to adopt an inertial sensor, thereby effectively solving the problem that the GNSS cannot be calibrated by LiDAR under the condition of no inertial sensor in the prior art.)

1. A global navigation satellite data calibration method, the method comprising:

acquiring first global navigation satellite data and radar data, generating first track data according to the first global navigation satellite data, and generating second track data and a point cloud map according to the radar data;

determining offset data from the point cloud map, the offset data reflecting a deviation between the first trajectory data and the second trajectory data;

acquiring second global navigation satellite data, and calibrating the second global navigation satellite data according to the offset data, wherein the acquisition time of the first global navigation satellite data is earlier than the acquisition time of the second global navigation satellite data.

2. The global navigation satellite data calibration method of claim 1, wherein said generating second trajectory data and a point cloud map from said radar data comprises:

inputting the radar data into a SLAM algorithm;

and acquiring the second track data and the point cloud map which are output by the SLAM algorithm based on the radar data.

3. The global navigation satellite data calibration method of claim 1, wherein said determining offset data from said point cloud map comprises:

judging whether an auxiliary positioning mark exists in the point cloud map;

when the auxiliary positioning mark exists in the point cloud map, acquiring first coordinate information of the auxiliary positioning mark in a world coordinate system and second coordinate information of the auxiliary positioning mark in an SLAM coordinate system, wherein the SLAM coordinate system is a coordinate system corresponding to the point cloud map;

and determining the offset data according to the first coordinate information and the second coordinate information.

4. The global navigation satellite data calibration method of claim 3, wherein said determining said offset data from said first coordinate information and said second coordinate information comprises:

determining a conversion matrix according to the first coordinate information and the second coordinate information;

converting the first track data into the SLAM coordinate system according to the conversion matrix to obtain conversion track data;

and determining the deviation between the converted track data and the second track data to obtain the offset data.

5. The global navigation satellite data calibration method of claim 1, wherein said determining offset data from said point cloud map comprises:

judging whether an auxiliary positioning mark exists in the point cloud map;

when the auxiliary positioning mark does not exist in the point cloud map, acquiring preset initial offset data;

and performing parameter optimization on the initial offset data to obtain the offset data.

6. The gnss data calibration method of claim 5, wherein said performing parameter optimization on said initial offset data to obtain said offset data comprises:

determining standard trajectory data according to the initial offset data, wherein the standard trajectory data is used for reflecting a corresponding standard trajectory of the first trajectory data in a world coordinate system;

and acquiring a deviation value of the first track data and the standard track data, and adjusting the initial offset data according to the deviation value to obtain the offset data.

7. The global navigation satellite data calibration method of claim 6, wherein said adjusting said initial offset data according to said offset value to obtain said offset data comprises:

performing Gauss-Newton iteration operation according to the deviation value, and adjusting the initial deviation data through the Gauss-Newton iteration operation;

and obtaining the offset data when the deviation value reaches a minimum value based on the Gaussian-Newton iteration operation.

8. A global navigation satellite data calibration apparatus, comprising:

the data acquisition module is used for acquiring first global navigation satellite data and radar data, generating first track data according to the first global navigation satellite data, and generating second track data and a point cloud map according to the radar data;

an offset determination module for determining offset data from the point cloud map, the offset data reflecting a deviation between the first trajectory data and the second trajectory data;

and the data calibration module is used for acquiring second global navigation satellite data and calibrating the second global navigation satellite data according to the offset data, wherein the acquisition time of the first global navigation satellite data is earlier than that of the second global navigation satellite data.

9. A terminal, comprising a memory and one or more processors; the memory stores one or more programs; the program comprising instructions for performing a global navigation satellite data calibration method as claimed in any one of claims 1-7; the processor is configured to execute the program.

10. A computer readable storage medium having stored thereon a plurality of instructions adapted to be loaded and executed by a processor to perform the steps of the gnss data calibration method according to any of the preceding claims 1 to 7.

Technical Field

The invention relates to the field of mobile measurement, in particular to a global navigation satellite data calibration method, a global navigation satellite data calibration device, a global navigation satellite data calibration terminal and a storage medium.

Background

With the development of technologies such as smart cities and automatic driving, the mobile measurement system gradually replaces the traditional fixed-point measurement method with the characteristics of convenience and high efficiency. In order to obtain different information, mobile measurement systems are often equipped with various sensors. Besides the accuracy of the sensors, calibrating the sensors is also an important means for improving the quality and accuracy of data, and is an important direction for research of mobile measurement systems.

GNSS and LiDAR, common sensors for mobile measurement systems, have significant calibration between them to improve the accuracy of mobile measurement systems. The current research mainly focuses on calibration of a GNSS/IMU (Inertial Measurement Units) system and LiDAR, that is, existing calibration methods of GNSS require LiDAR and Inertial sensors, and in the absence of Inertial sensors, calibration of GNSS cannot be performed by LiDAR.

Thus, there is still a need for improvement and development of the prior art.

Disclosure of Invention

The present invention is directed to provide a method, an apparatus, a terminal and a storage medium for calibrating GNSS data, which are used to solve the above-mentioned drawbacks of the prior art, and aims to solve the problem that the GNSS cannot be calibrated by LiDAR without an inertial sensor in the prior art.

The technical scheme adopted by the invention for solving the problems is as follows:

in a first aspect, an embodiment of the present invention provides a global navigation satellite data calibration method, where the method includes:

acquiring first global navigation satellite data and radar data, generating first track data according to the first global navigation satellite data, and generating second track data and a point cloud map according to the radar data;

determining offset data from the point cloud map, the offset data reflecting a deviation between the first trajectory data and the second trajectory data;

acquiring second global navigation satellite data, and calibrating the second global navigation satellite data according to the offset data, wherein the acquisition time of the first global navigation satellite data is earlier than the acquisition time of the second global navigation satellite data.

In one embodiment, the generating second trajectory data and a point cloud map from the radar data includes:

inputting the radar data into a SLAM algorithm;

and acquiring the second track data and the point cloud map which are output by the SLAM algorithm based on the radar data.

In one embodiment, the determining offset data from the point cloud map comprises:

judging whether an auxiliary positioning mark exists in the point cloud map;

when the auxiliary positioning mark exists in the point cloud map, acquiring first coordinate information of the auxiliary positioning mark in a world coordinate system and second coordinate information of the auxiliary positioning mark in an SLAM coordinate system, wherein the SLAM coordinate system is a coordinate system corresponding to the point cloud map;

and determining the offset data according to the first coordinate information and the second coordinate information.

In one embodiment, the determining the offset data according to the first coordinate information and the second coordinate information includes:

determining a conversion matrix according to the first coordinate information and the second coordinate information;

converting the first track data into the SLAM coordinate system according to the conversion matrix to obtain conversion track data;

and determining the deviation between the converted track data and the second track data to obtain the offset data.

In one embodiment, the determining offset data from the point cloud map comprises:

judging whether an auxiliary positioning mark exists in the point cloud map;

when the auxiliary positioning mark does not exist in the point cloud map, acquiring preset initial offset data;

and performing parameter optimization on the initial offset data to obtain the offset data.

In an embodiment, the performing parameter optimization on the initial offset data to obtain the offset data includes:

determining standard trajectory data according to the initial offset data, wherein the standard trajectory data is used for reflecting a corresponding standard trajectory of the first trajectory data in a world coordinate system;

and acquiring a deviation value of the first track data and the standard track data, and adjusting the initial offset data according to the deviation value to obtain the offset data.

In an embodiment, the adjusting the initial offset data according to the deviation value to obtain the offset data includes:

performing Gauss-Newton iteration operation according to the deviation value, and adjusting the initial deviation data through the Gauss-Newton iteration operation;

and obtaining the offset data when the deviation value reaches a minimum value based on the Gaussian-Newton iteration operation.

In a second aspect, an embodiment of the present invention further provides a global navigation satellite data calibration apparatus, where the apparatus includes:

the data acquisition module is used for acquiring first global navigation satellite data and radar data, generating first track data according to the first global navigation satellite data, and generating second track data and a point cloud map according to the radar data;

an offset determination module for determining offset data from the point cloud map, the offset data reflecting a deviation between the first trajectory data and the second trajectory data;

and the data calibration module is used for acquiring second global navigation satellite data and calibrating the second global navigation satellite data according to the offset data, wherein the acquisition time of the first global navigation satellite data is earlier than that of the second global navigation satellite data.

In a third aspect, an embodiment of the present invention further provides a terminal, where the terminal includes a memory and one or more processors; the memory stores one or more programs; said program containing instructions for performing a global navigation satellite data calibration method as described in any one of the above; the processor is configured to execute the program.

In a fourth aspect, the present invention further provides a computer-readable storage medium, having a plurality of instructions stored thereon, where the instructions are adapted to be loaded and executed by a processor to implement any of the steps of the gnss data calibration method described above.

The invention has the beneficial effects that: according to the embodiment of the invention, first global navigation satellite data and radar data are obtained, first track data are generated according to the first global navigation satellite data, and second track data and a point cloud map are generated according to the radar data; determining offset data from the point cloud map, the offset data reflecting a deviation between the first trajectory data and the second trajectory data; acquiring second global navigation satellite data, and calibrating the second global navigation satellite data according to the offset data, wherein the acquisition time of the first global navigation satellite data is earlier than the acquisition time of the second global navigation satellite data. The invention does not need to adopt an inertial sensor, thereby effectively solving the problem that the GNSS cannot be calibrated by LiDAR under the condition of no inertial sensor in the prior art.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a schematic flowchart of a global navigation satellite data calibration method according to an embodiment of the present invention.

Fig. 2 is a schematic flowchart of a calibration method with different assisted location markers and different assisted location markers without the assisted location markers according to an embodiment of the present invention.

Fig. 3 is a schematic connection diagram of internal modules of the gnss data calibration apparatus according to the embodiment of the present invention.

Fig. 4 is a schematic block diagram of a terminal according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

It should be noted that, if directional indications (such as up, down, left, right, front, and back … …) are involved in the embodiment of the present invention, the directional indications are only used to explain the relative positional relationship between the components, the movement situation, and the like in a specific posture (as shown in the drawing), and if the specific posture is changed, the directional indications are changed accordingly.

With the development of technologies such as smart cities and automatic driving, the mobile measurement system gradually replaces the traditional fixed-point measurement method with the characteristics of convenience and high efficiency. In order to obtain different information, mobile measurement systems are often equipped with various sensors. Besides the accuracy of the sensors, calibrating the sensors is also an important means for improving the quality and accuracy of data, and is an important direction for research of mobile measurement systems.

GNSS and LiDAR, common sensors for mobile measurement systems, have significant calibration between them to improve the accuracy of mobile measurement systems. The current research mainly focuses on calibration of a GNSS/IMU (Inertial Measurement Units) system and LiDAR, that is, existing calibration methods of GNSS require LiDAR and Inertial sensors, and in the absence of Inertial sensors, calibration of GNSS cannot be performed by LiDAR.

In order to overcome the defects of the prior art, the invention provides a global navigation satellite data calibration method, which comprises the steps of acquiring first global navigation satellite data and radar data, generating first track data according to the first global navigation satellite data, and generating second track data and a point cloud map according to the radar data; determining offset data from the point cloud map, the offset data reflecting a deviation between the first trajectory data and the second trajectory data; acquiring second global navigation satellite data, and calibrating the second global navigation satellite data according to the offset data, wherein the acquisition time of the first global navigation satellite data is earlier than the acquisition time of the second global navigation satellite data. The invention does not need to adopt an inertial sensor, thereby effectively solving the problem that the GNSS cannot be calibrated by LiDAR under the condition of no inertial sensor in the prior art.

As shown in fig. 1, the method comprises the steps of:

step S100, first global navigation satellite data and radar data are obtained, first track data are generated according to the first global navigation satellite data, and second track data and a point cloud map are generated according to the radar data.

Specifically, to enable calibration between GNSS and LiDAR, the present embodiment requires acquisition of first GNSS satellite data by a GNSS sensor and simultaneous acquisition of radar data by a LiDAR sensor. First trajectory data reflecting a trajectory of movement of the user may then be generated based on the first global navigation satellite data. And meanwhile, second track data and a point cloud map for reflecting the moving track of the user are generated based on the radar data, wherein the point cloud map can reflect the environmental information around the moving track of the user. In the absence of errors, the first trajectory data and the second trajectory data should be coincident, but in real life, the first trajectory data and the second trajectory data are deviated from each other, and therefore, the first trajectory data and the second trajectory data need to be calibrated. It should be noted that, in order to ensure that the first trajectory data and the second trajectory data reflect the same movement trajectory of the user, it is necessary to ensure that the timestamp information of the corresponding data points in the first trajectory data and the second trajectory data are the same.

In one implementation, the generating the second trajectory data and the point cloud map according to the radar data specifically includes the following steps:

step S101, inputting the radar data into an SLAM algorithm;

and S102, acquiring the second track data and the point cloud map output by the SLAM algorithm based on the radar data.

Specifically, the radar is the most studied SLAM sensor, and can provide distance information between the robot body and surrounding obstacles, and the moving track of the radar sensor, that is, the second track data, can be calculated by combining radar data acquired by the radar sensor with a SLAM algorithm (that is, a simultaneous localization and mapping algorithm), and a point cloud map for describing the surrounding environment in the moving route of the radar sensor is generated at the same time.

As shown in fig. 1, the method further comprises the steps of:

step S200, determining offset data according to the point cloud map, wherein the offset data is used for reflecting the deviation between the first track data and the second track data.

Specifically, the present embodiment aims to calibrate the GNSS by LiDAR without an inertial sensor, and since the point cloud map can reflect the surrounding environment in the moving route of the radar sensor, the point cloud map can connect information in the real environment with information in the SLAM map, so as to determine the deviation between the first trajectory data and the second trajectory data, and obtain the offset data.

In one implementation, the determining offset data according to the point cloud map specifically includes the following steps:

step S201, judging whether an auxiliary positioning mark exists in the point cloud map;

step S202, when the auxiliary positioning mark exists in the point cloud map, acquiring first coordinate information of the auxiliary positioning mark in a world coordinate system and second coordinate information of the auxiliary positioning mark in an SLAM coordinate system, wherein the SLAM coordinate system is a coordinate system corresponding to the point cloud map;

step S203, determining the offset data according to the first coordinate information and the second coordinate information.

In short, in this embodiment, it is first required to determine whether an auxiliary locating mark, that is, a mark preset in the environment where the radar sensor is located, exists in the point cloud map, and provide a method for determining offset data according to the existence of the auxiliary locating mark and the absence of the auxiliary locating mark (as shown in fig. 2). Specifically, for the case where the auxiliary locating mark exists, it is necessary to determine the coordinate information of the auxiliary locating mark in the world coordinate system and the coordinate information of the auxiliary locating mark in the SLAM coordinate system, that is, the first coordinate information and the second coordinate information are obtained. The first coordinate information and the second coordinate information can reflect position information of the auxiliary positioning mark in different coordinate systems, so that the first track data and the second track data can be converted into the same coordinate system to be compared on the basis of the first coordinate information and the second coordinate information, offset data can be obtained, and deviation between the first track data and the second track data can be reflected through the offset data.

In an implementation manner, the step S203 specifically includes the following steps:

step S2031, determining a conversion matrix according to the first coordinate information and the second coordinate information;

step S2032, converting the first track data into the SLAM coordinate system according to the conversion matrix to obtain conversion track data;

step S2033, determining a deviation between the converted trajectory data and the second trajectory data to obtain the offset data.

In particular, since the first coordinate information and the second coordinate information may reflect position information of the auxiliary locator mark in different coordinate systems, a transformation matrix may be determined based on the first coordinate information and the second coordinate information, and the transformation matrix may reflect a coordinate transformation relationship between the world coordinate system and the SLAM coordinate system. Based on the transformation matrix, all data points in the first trajectory data can thus be transformed into the SLAM coordinate system, resulting in transformed trajectory data. Ideally, when there is no error between the GNSS and the LiDAR, the converted trajectory data and the second trajectory data should be coincident, however, in practical applications, there is more or less a certain deviation between the converted trajectory data and the second trajectory data, and therefore, by comparing the converted trajectory data with the second trajectory data, offset data reflecting the deviation between the converted trajectory data and the second trajectory data can be obtained.

For example, the world coordinate system may be calculated using the ICP algorithmAnd SLAM coordinate systemConversion matrix betweenAnd using a transformation matrixThe first track dataConversion to SLAM coordinate SystemThe following equation (1) shows:

wherein the superscript s is expressed in the SLAM coordinate systemIn the following, the superscript l is expressed in the world coordinate systemIn the following, the first and second parts of the material,is thatThe rotation matrix of (a) is,is thatThe translational component of (a). A difference value between the LiDAR trajectory obtained in the SLAM process is then calculated, thereby calculating a deviation between the first trajectory data and the second trajectory data, resulting in offset data t_laAs shown in the following equation (2):

where i represents the i-th point on a paired LiDAR trace,is a rotation matrix of the point i,is the position of point i, t_la,iIs a corresponding t_la。t_laThe calculation formula (3) is as follows

In one implementation, t is calculated_laIn the process of (3), the abnormal value can be eliminated by using the absolute median difference, as shown in formula (4):

wherein S is_tlaIs all of t_la,iIs a median operation, MAD is S_tlaThe absolute median difference of (2).

In another implementation, the determining offset data according to the point cloud map specifically includes the following steps:

step S204, judging whether an auxiliary positioning mark exists in the point cloud map;

step S205, when the auxiliary positioning mark does not exist in the point cloud map, acquiring preset initial offset data;

and S206, performing parameter optimization on the initial offset data to obtain the offset data.

Specifically, when the point cloud map does not have the auxiliary locating mark, initial offset data stored in advance by the system is obtained, parameter optimization is carried out on the initial offset data, the initial offset data is enabled to be closer to a true value, and the offset data is obtained after the parameter optimization is finished.

In an implementation manner, the step S206 specifically includes the following steps:

step S2061, determining standard trajectory data according to the initial offset data, wherein the standard trajectory data is used for reflecting a standard trajectory corresponding to the first trajectory data in a world coordinate system;

step S2062, obtaining a deviation value of the first track data and the standard track data, and adjusting the initial offset data according to the deviation value to obtain the offset data.

Specifically, since the initial offset data may roughly reflect the deviation of the first trajectory data from the second trajectory data, a standard trajectory corresponding to the first trajectory data in the world coordinate system may be generated based on the initial offset data, resulting in standard trajectory data. Since the standard trajectory data can reflect the correct position of the first trajectory data in the world coordinate system, the initial offset data can be adjusted based on the deviation value between the first trajectory data and the standard trajectory data to obtain the offset data that better meets the true value.

In an implementation manner, the adjusting the initial offset data according to the deviation value to obtain the offset data specifically includes the following steps:

step S20621, executing Gauss-Newton iteration operation according to the deviation value, and adjusting the initial offset data through the Gauss-Newton iteration operation;

step S20622, when the deviation value reaches the minimum value based on the Gaussian-Newton iteration operation, obtaining the deviation data.

Specifically, the parameter optimization for the offset data in the embodiment mainly adopts a gaussian-newton iteration method. The deviation value can reflect the difference between the first track data and the standard track data, so that Gaussian-Newton iteration operation can be performed on the deviation value, the initial offset data is continuously updated in the Gaussian-Newton iteration operation process until the deviation value reaches the minimum value based on the Gaussian-Newton iteration operation, the Gaussian-Newton iteration operation is stopped, and the offset data obtained at the moment is used as final offset data.

In an implementation manner, the euler angles of the preset initial conversion matrix can be simultaneously obtained, the gaussian-newton iteration operation is adopted to simultaneously perform parameter optimization on the initial offset data and the euler angles of the initial conversion matrix, and when the gaussian-newton iteration operation is stopped, the offset data and the euler angles of the conversion matrix after parameter optimization are obtained, wherein the euler angles of the offset data and the conversion matrix are three-dimensional changes.

For example, equation (5) for parameter optimization using the gauss-newton method is as follows:

wherein i represents the ith point on the first trajectory data,is the position of the point i and,is the correct position of the estimated i point. Assume that each data point in the first trajectory data isPose under the estimation of Andthe position component and the rotation matrix, respectively, hold as follows equation (6):

wherein the content of the first and second substances,is the pose of each data point in the matched second trajectory data. Since the world coordinate system uses the pose of the first data point in the first trajectory data as the origin, formula (7) holds:

wherein the content of the first and second substances,is an estimated i-point in the world coordinate systemThe pose below, in conjunction with equations (6) and (7), can be derived from equation (8):

wherein, t_la(byThree-axis parametric composition) and(represented by Euler angles)) Is a six-dimensional parameter estimated using a gauss-newton algorithm.Is the rotation matrix ofComponent of translation thereofCan be calculated by equation (6).

In one implementation, the rotation matrix corresponding to the radar data may be passedAnd GNSS position under FlAccurately estimating the position of the second trajectory data in the SLAM coordinate systemThis value can be used as additional observation and secondary trajectory data derived by SLAM algorithmPerforming data fusion, or evaluating as truthThe calculation formula is as follows (9):

based on the above embodiment, the present invention further provides a global navigation satellite data calibration apparatus, as shown in fig. 3, the apparatus includes:

the data acquisition module 01 is used for acquiring first global navigation satellite data and radar data, generating first track data according to the first global navigation satellite data, and generating second track data and a point cloud map according to the radar data;

an offset determining module 02, configured to determine offset data according to the point cloud map, where the offset data is used to reflect a deviation between the first trajectory data and the second trajectory data;

and a data calibration module 03, configured to acquire second gnss data and calibrate the second gnss data according to the offset data, where an acquisition time of the first gnss data is earlier than an acquisition time of the second gnss data.

Based on the above embodiments, the present invention further provides a terminal, and a schematic block diagram thereof may be as shown in fig. 4. The terminal comprises a processor, a memory, a network interface and a display screen which are connected through a system bus. Wherein the processor of the terminal is configured to provide computing and control capabilities. The memory of the terminal comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the terminal is used for connecting and communicating with an external terminal through a network. The computer program is executed by a processor to implement a global navigation satellite data calibration method. The display screen of the terminal can be a liquid crystal display screen or an electronic ink display screen.

It will be understood by those skilled in the art that the block diagram of fig. 4 is a block diagram of only a portion of the structure associated with the inventive arrangements and is not intended to limit the terminals to which the inventive arrangements may be applied, and that a particular terminal may include more or less components than those shown, or may have some components combined, or may have a different arrangement of components.

In one implementation, one or more programs are stored in a memory of the terminal and configured to be executed by one or more processors, including instructions for performing a global navigation satellite data calibration method.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

In summary, the present invention discloses a method, an apparatus, a terminal and a storage medium for calibrating global navigation satellite data, wherein the method comprises: acquiring first global navigation satellite data and radar data, generating first track data according to the first global navigation satellite data, and generating second track data and a point cloud map according to the radar data; determining offset data from the point cloud map, the offset data reflecting a deviation between the first trajectory data and the second trajectory data; acquiring second global navigation satellite data, and calibrating the second global navigation satellite data according to the offset data, wherein the acquisition time of the first global navigation satellite data is earlier than the acquisition time of the second global navigation satellite data. The invention does not need to adopt an inertial sensor, thereby effectively solving the problem that the GNSS cannot be calibrated by LiDAR under the condition of no inertial sensor in the prior art.

It is to be understood that the invention is not limited to the examples described above, but that modifications and variations may be effected thereto by those of ordinary skill in the art in light of the foregoing description, and that all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.