Calibration method and system for automobile test in indoor complex scene

Abstract

The invention relates to the technical field of automobile testing, and discloses a calibration method and system for automobile testing in an indoor complex scene, and the method comprises the steps: setting a motion capture system in an indoor positioning region, and building an indoor local space rectangular coordinate system; correspondingly selecting a plurality of calibration points and a calculation strategy according to the overlapping condition of the indoor positioning area and the outdoor positioning area, acquiring coordinates of the plurality of calibration points in an indoor local space rectangular coordinate system and latitude and longitude information in an outdoor latitude and longitude coordinate system, and aggregating to form coordinate conversion input point information; obtaining a conversion relation between an indoor local space rectangular coordinate system and an outdoor longitude and latitude coordinate system according to the coordinate conversion input point information; and determining a plurality of test points representing the calibration points on the test vehicle and the target object, and obtaining indoor positioning data of the plurality of test points in the indoor positioning area based on motion capture system capture and conversion relation coordinate conversion. According to the method, the motion capture technology and the indoor positioning application scene are combined, and the indoor positioning precision and efficiency during ADAS testing are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile testing, and in particular to a calibration method and system for automobile testing in complex indoor scenarios. Background Art

[0002] Advanced Driver Assistance System (ADAS) testing is a critical step in ensuring functional reliability and safety, both on open roads and in closed-course testing. It's well known that among various testing scenarios, environments like tunnels and underground garages present unique challenges for ADAS testing due to their unique geographical characteristics and lighting conditions. Positioning is particularly prominent. Limited GPS signals in tunnels and underground garages can render GPS-based positioning systems ineffective. ADAS testing, however, requires extremely high positioning accuracy, making it difficult to maintain high-precision positioning during these testing scenarios. Summary of the Invention

[0003] The present invention aims to provide a calibration method and system for automobile testing in complex indoor scenarios, which realizes multi-target indoor positioning based on motion capture technology. It is particularly suitable for obtaining high-precision indoor positioning data when conducting ADAS testing experiments in tunnels and underground garages.

[0004] The basic solution provided by the present invention is: a calibration method for indoor complex scene vehicle testing, the method comprising:

[0005] S100, setting up a motion capture system in the indoor positioning area and establishing an indoor local space rectangular coordinate system;

[0006] S200, selecting a number of calibration points and calculation strategies based on the overlap between the indoor positioning area and the outdoor positioning area, and simultaneously obtaining the coordinates of the calibration points in the indoor local space rectangular coordinate system and the latitude and longitude information in the outdoor latitude and longitude coordinate system, and aggregating them to form coordinate conversion input point information;

[0007] S300, obtaining a conversion relationship between an indoor local space rectangular coordinate system and an outdoor latitude and longitude coordinate system based on coordinate conversion input point information;

[0008] S400, determining a plurality of test points representing calibration points on the test vehicle and the target object, and obtaining indoor positioning data corresponding to the plurality of test points based on the capture and conversion relationship of the motion capture system within the indoor positioning area.

[0009] The present invention is based on a calibration method for indoor complex scene automobile testing, and also provides a calibration system for indoor complex scene automobile testing, the system comprising:

[0010] A motion capture system module is configured to establish an indoor local space rectangular coordinate system within the indoor positioning area to obtain the coordinates of the calibration point or the test point in the indoor local space rectangular coordinate system, including but not limited to obtaining the velocity and posture information of the test point in the indoor local space rectangular coordinate system;

[0011] The coordinate conversion input point information acquisition module is used to select a number of calibration points and calculation strategies according to the overlap between the indoor positioning area and the outdoor positioning area, and simultaneously obtain the coordinates of the calibration points in the indoor local space rectangular coordinate system and the longitude and latitude information in the outdoor longitude and latitude coordinate system, and aggregate them to form the coordinate conversion input point information;

[0012] A coordinate conversion module is used to obtain the conversion relationship between the indoor local space rectangular coordinate system and the outdoor latitude and longitude coordinate system according to the coordinate conversion input point information;

[0013] The test module is used to determine multiple test points representing calibration points on the test vehicle and the target object, perform coordinate conversion based on the motion capture system capture and conversion relationship within the indoor positioning area, and obtain indoor positioning data corresponding to the multiple test points.

[0014] The working principle and advantages of the present invention are as follows: when conducting ADAS testing, test points are selected on the test vehicle and the target object, and positioning devices (usually reflective balls or LEDs) are installed on the test points for marking; a high-precision positioning inertial navigation and an antenna are installed on the vehicle; the vehicle is driven according to the ADAS test requirements: when outdoors, the inertial navigation is used to obtain outdoor positioning data; when driving in the indoor positioning area, the motion capture system is used to capture the position data (coordinates), speed and posture information of the indoor local space rectangular coordinate system, and then the indoor positioning data is obtained through the conversion relationship (based on the rotation and translation matrix to the geodetic coordinate system, and then based on the relationship between the geodetic coordinate system and the outdoor longitude and latitude).

[0015] Compared with existing technologies, the advantages of this solution are: it solves the problem in existing ADAS tests that vehicles cannot be accurately positioned in areas with weak GNSS signals such as tunnels and garages, resulting in the inability to conduct effective ADAS tests; this solution can achieve centimeter-level high-precision positioning even when GNSS signals are limited, accurately measure and capture the object's position, speed, heading and other motion information, and obtain high-precision indoor positioning data. Indoor positioning data can be used instead of outdoor positioning data to conduct ADAS testing in the above-mentioned areas, which is suitable for parking and driving performance testing of intelligent connected vehicles in complex environments such as tunnels, indoor test sites, rain and fog.

[0016] 1) The present invention realizes multi-target indoor positioning based on the motion capture system, and is particularly suitable for ADAS testing in scenarios such as tunnels and underground garages where indoor positioning signals are weak. The indoor positioning system based on motion capture uses motion capture technology to achieve real-time, high-precision positioning of objects (usually people or equipment) in indoor environments, meeting the needs of applications that require real-time tracking. Compared with other indoor positioning technologies (such as WiFi, Bluetooth, etc.), motion capture indoor positioning can achieve higher positioning accuracy, usually in the millimeter to centimeter level; and in addition to position information, it can also provide object posture information, such as rotation angle, etc., and the positioning data is rich. Motion capture positioning is usually not affected by complex indoor environments (such as walls, obstacles), and is not limited by the number of markers. As long as the marker is within the field of view of the camera, positioning can be performed to achieve simultaneous multi-target indoor positioning. This method combines the high precision of motion capture technology with the requirements of positioning technology, and has broad application prospects in many fields.

[0017] 2) Distinguishing between indoor and outdoor areas allows for flexible switching between indoor and outdoor positioning data during ADAS testing. When the vehicle enters the indoor area from the outdoor area, if the outdoor positioning data detects that the positioning status does not meet the test requirements, the ADAS test is immediately switched to the indoor positioning data. Similarly, when the vehicle enters the outdoor area from the indoor area, if the outdoor positioning data recovers, the ADAS test is immediately switched to the outdoor positioning data. Of course, during this switching process, the indoor and outdoor positioning data may not be completely consistent. To avoid step-like data after the switch, filtering and smoothing are performed within a short period of time (2 seconds) after the switch to ensure a smooth transition and switch of the positioning data. Because the intersection of indoor and outdoor areas in actual test sites is often obscured during ADAS testing, and considering that outdoor positioning data takes time to recover, the determined indoor positioning area generally extends outward by a certain distance, overlapping with the outdoor positioning area. The choice of two different calculation strategies for different overlapping area arrangements is primarily based on geographical location and budget considerations. When the geographical location is relatively complex and the area is severely obstructed, GNSS satellite signals cannot be effectively received, or when high-speed ADAS testing is being performed, it is necessary to arrange the overlap between the indoor positioning area and the outdoor area to be larger so that the positioning status of the outdoor positioning system can meet the test needs before the vehicle leaves the indoor positioning area. For relatively open terrain or low-speed ADAS testing, it is not necessary to arrange an excessively long indoor positioning area to avoid excessive overlap with the outdoor positioning area. Therefore, a total station can be used to complete the calibration work, thereby reducing the number of high-speed infrared cameras and saving costs. Different overlap situations are consistent with the coordinate conversion because the input is the same. Only different overlap methods need to be selected according to the test site and working conditions. This does not affect the accuracy of the coordinate conversion, is highly versatile, and can adapt to a variety of test scenarios.

[0018] This solution is suitable for parking and driving performance testing of intelligent connected vehicles in complex environments such as tunnels, indoor test sites, rain and fog, and provides reliable support for the verification and optimization of intelligent driving functions. It can realize real-time calculation of the relative position relationship between vehicles, lane lines, and parking lines, obtain vehicle posture information, adapt to applications in complex environments such as rain, fog, and light, support automatic switching between indoor and outdoor environments, and support combined use with OxTS inertial navigation and target drive tablets. Through actual use tests, in terms of position accuracy, the static positioning accuracy error is less than 0.1mm, the dynamic positioning accuracy error is less than 1.5cm, and the positioning accuracy error in rain and fog environments is less than 2mm. In terms of speed accuracy, the error is less than 0.3km. In terms of heading accuracy, the error is less than 0.1°. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A schematic flow chart of a calibration method for indoor complex scene vehicle testing provided by an embodiment of the present invention;

[0020] Figure 2 A schematic diagram of the layout of the infrared camera provided by an embodiment of the present invention installed in an indoor positioning area;

[0021] Figure 3 A schematic diagram of the viewing angle coverage area of an infrared camera provided in an embodiment of the present invention;

[0022] Figure 4 A schematic diagram of selecting a marker that satisfies the overlapping area requirement provided by an embodiment of the present invention;

[0023] Figure 5 A schematic diagram of marker selection for a situation where there is no or does not meet the required overlapping area provided by an embodiment of the present invention;

[0024] Figure 6 A schematic diagram of a process for obtaining coordinate conversion mark input point information provided by an embodiment of the present invention;

[0025] Figure 7 This is a schematic diagram of a process for obtaining the conversion relationship between the indoor local space rectangular coordinate system and the outdoor latitude and longitude coordinate system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The following is a further detailed description through specific implementation methods:

[0027] The embodiment is basically as shown in the attached Figure 1 A calibration method for indoor complex scene vehicle testing is shown, the method comprising:

[0028] S100: Setting up a motion capture system in an indoor positioning area to establish an indoor local space rectangular coordinate system.

[0029] Specifically, the motion capture system includes a high-speed infrared camera group, calibration tools, markers, computing platform servers, switches, and motion capture software. The high-speed infrared camera captures special markers fixed to the vehicle target at a frame rate of 210 frames per second. The calibration tool is used to calibrate the camera. The markers are installed on the vehicle and target, and the high-speed infrared camera is used to capture the movement trajectory of the vehicle and target. The switch is used to connect all cameras to the switch via wired means to build an efficient and stable local area network. The computing service platform is used to accurately construct the three-dimensional spatial position information of the target object in real time using the data from the high-speed infrared camera group, and to achieve real-time tracking and positioning of the vehicle's motion trajectory. The motion capture software is used to set up and calibrate the infrared camera.

[0030] A high-speed infrared camera group is set up in the indoor positioning area. The infrared camera model LUSTER Swift 30 can be used. The infrared cameras need to be evenly distributed and each infrared camera needs to be accurately calibrated. The viewing angles of at least two adjacent infrared cameras must overlap. That is, the viewing angles of two or more adjacent cameras must overlap.

[0031] The length of the infrared camera layout is closely related to the indoor positioning area. It is necessary to cover the entire area required for ADAS testing. For ADAS testing, rectangular areas are usually more common, and cameras are placed on both sides of the area. The distance between cameras is usually within 6 meters. The following is an example of a coverage plan: Figure 2 As shown, for example, the test site has a 10*7m parking area that needs to be deployed with an indoor positioning system. The largest gray area is the indoor positioning area, and the small gray area represents the infrared camera. The infrared camera group is placed on the boundary of the indoor positioning area, horizontally ( Figure 2 (10m direction shown) The camera spacing is 1.6-1.7m, 6 on one side; longitudinal ( Figure 2 (7m direction as shown) The cameras are spaced 1.75m apart, with four on each side; Figure 3 The figure shows the coverage area of the infrared camera group's field of view. The colors are red, green, and yellow from dark to light. Green (corresponding to the position of the horizontal camera) indicates the overlapping area of at least four cameras, yellow (corresponding to the position of the vertical camera) indicates the overlapping area of at least four cameras, and red (the middle area between the horizontal and vertical directions) indicates the overlapping area of at least five cameras. This ensures that all areas are covered by at least two cameras.

[0032] Using the motion capture system, a coordinate point is selected as the origin in the indoor positioning area, and a suitable heading is selected to establish the indoor local space rectangular coordinate system, which is the indoor positioning system space rectangular coordinate system.

[0033] S200, according to the overlap between the indoor positioning area and the outdoor positioning area, select several calibration points and calculation strategies accordingly, and simultaneously obtain the coordinates of several calibration points in the indoor local space rectangular coordinate system and the latitude and longitude information in the outdoor longitude and latitude coordinate system (outdoor GNSS), and aggregate them to form coordinate conversion input point information, such as Figure 4 、 Figure 5 and Figure 6 shown.

[0034] Specifically, the determination of the indoor positioning area and the outdoor positioning area has been explained above and will not be repeated here. They can be reasonably determined based on the geographical conditions of the actual test site and test requirements.

[0035] like Figure 4 and Figure 6As shown, the indoor positioning area and the outdoor positioning area (outdoor GNSS area) have an overlap area that meets the requirements, that is, a large overlap area with a length of more than 10 meters. In this case, stable, high-precision positioning information can be obtained from both the indoor and outdoor positioning systems. Several calibration points are selected in the overlapping area, which can be 3 to 4. The calibration points need to be as far apart as possible and distributed symmetrically. For example, 4 calibration points are selected to form a symmetrical quadrilateral, and 3 calibration points are selected to form an equilateral triangle. The interval between the points should be within the range of 5-10 meters. This will result in higher measurement accuracy. Reflective balls are placed at these calibration points, and the coordinates of these calibration points in the indoor local space rectangular coordinate system are directly obtained using the motion capture system. The latitude and longitude of these calibration points in an outdoor latitude and longitude coordinate system are then acquired through high-precision positioning inertial navigation. OxTS inertial navigation systems can be used for high-precision positioning inertial navigation. During the calibration process, the vehicle is typically mounted on a stationary vehicle. The antenna, which will be installed on the roof during testing, is placed directly at the calibration location in the field as the calibration point. The inertial navigation system captures the antenna's position data. After calibration, the antenna is then installed on the front and rear of the vehicle for ADAS testing. This allows the motion capture system to simultaneously acquire the coordinates of these calibration points in the indoor local rectangular coordinate system, while the inertial navigation system acquires the latitude and longitude information in the outdoor latitude and longitude coordinate system, combining these information to form the input point information for coordinate conversion.

[0036] like Figure 5 and Figure 6As shown, the indoor positioning area and the outdoor positioning area have no or insufficient overlap, that is, no overlap or a relatively small overlap. The overlap is relatively small, that is, the length of the overlap is less than 10 meters. In this case, it is not possible to select points from the overlap area to participate in the coordinate conversion. A total station is required to achieve this: First, the total station is set up at the intersection of the indoor positioning area and the outdoor positioning area, and it is ensured that there is no obstruction to the indoor positioning area and the outdoor positioning area. In the indoor positioning area, several calibration points are selected, such as 4 calibration points, distributed in a symmetrical quadrilateral with an interval of 5-10 meters. The coordinate values of these calibration points can be obtained by the motion capture system (the process of obtaining the coordinate values is the same as described above). These calibration points are called known points. The total station uses back intersection to establish a station. The coordinate values of all known points are input into the total station. The total station calculates, which is equivalent to establishing a total station spatial rectangular coordinate system on the total station that is consistent with the indoor local spatial rectangular coordinate system. Then, select several calibration points in the outdoor positioning area. The number and layout of the calibration points are not necessarily the same as those selected for the indoor calibration points, and there is no direct correlation in the actual calculation. You can choose four calibration points with a symmetrical distribution of 5-10 points in a quadrilateral. Use a total station to measure and obtain the coordinates of these calibration points in the outdoor positioning area, which are their coordinates in the indoor local space rectangular coordinate system. Then, use high-precision positioning inertial navigation to obtain the latitude and longitude information of these calibration points in the outdoor latitude and longitude coordinate system (outdoor GNSS positioning). This also allows you to simultaneously obtain the coordinates of these calibration points in the indoor local space rectangular coordinate system and the latitude and longitude information in the outdoor latitude and longitude coordinate system, aggregating them to form the coordinate conversion input point information. The total station can be the CTS-632R10 model.

[0037] S300: According to the coordinate conversion input point information, the conversion relationship between the indoor local space rectangular coordinate system and the outdoor latitude and longitude coordinate system is obtained, such as Figure 5 shown.

[0038] Specifically, the main function of the coordinate conversion tool is to input the local coordinate values and longitude and latitude data of multiple sets of calibration points recorded by the two methods mentioned above, calculate the longitude and latitude of the coordinate origin of the indoor local space rectangular coordinate system and the heading angle of the coordinate axis deflection, and then use the longitude and latitude of the coordinate origin and the heading angle of the coordinate axis deflection to obtain the conversion relationship between the indoor local space rectangular coordinate system and the outdoor longitude and latitude coordinate system. In this way, the coordinate conversion tool can be used to calculate the longitude and latitude information of any point in the indoor positioning area by converting the indoor local space rectangular coordinate system to the outdoor longitude and latitude coordinate system, thus achieving indoor positioning.

[0039] The purpose of the coordinate conversion tool is to solve the transformation matrix of two spatial rectangular coordinate systems. Among the corresponding calibration points selected in S200 (i.e., the calibration points of the indoor local spatial rectangular coordinate system obtained by the motion capture system), Figure 7 As shown, first select one of the calibration points as the reference point, establish a geodetic coordinate system with the reference point as the origin and a heading angle of 0 (the latitude, longitude and elevation data of the point are used according to the eccentricity and the axial radius of the earth to obtain the proportional coefficients latRad and lonRad for establishing a coordinate system at this longitude and latitude to calculate the longitude and latitude and the easting and northing coordinate values). According to the longitude and latitude of other calibration points, calculate the coordinates of other calibration points in this geodetic coordinate system (according to the coefficients latRad and lonRad obtained before, the calculation formula is: (lat1-lat0)*latRad=north; (lon1-lon0)*lonRad=east; where: lat1 and lon1 represent the latitude and longitude of the point to be converted, lat0 and lon0 represent the latitude and longitude corresponding to the origin of the geodetic coordinate system; east: represents the easting coordinate, north: represents the northing coordinate). In this way, two sets of coordinate values of other calibration points in the indoor local space rectangular coordinate system and the geodetic coordinate system are obtained. Moreover, these two coordinate systems are spatial rectangular coordinate systems, and can be transformed from one coordinate system to another coordinate system through rotation and translation, that is, PB=T*PA+t, where PB represents the data of point P in the geodetic coordinate system, PA represents the data of point P in the indoor local coordinate system, T represents the rotation matrix, and t represents the translation matrix. With the help of mathematical formulas (using the singular value decomposition (SVD) algorithm for mathematical solution, [U,S,V]=SVD(H); T=VUT; t=-T*centroA+centroB; where U represents the left orthogonal matrix, S represents the diagonal matrix, V represents the right orthogonal matrix, H represents the matrix composed of 3 sets of calibration point data, centroA and centroB represent the average center of the A and B coordinate systems) and the Eigen library, the equations are solved, and the flip and translation matrix can be calculated by programming. The Eigen library is a high-level C++ template library mainly used for linear algebra operations. It provides support for vectors, matrices, and higher-dimensional data structures, and includes a wide range of mathematical operations, such as matrix multiplication, decomposition, eigenvalue problems, etc. Eigen is designed to achieve high performance, ease of use, and flexibility. Based on the rotation and translation matrix, the coordinates of the origin of the indoor local space rectangular coordinate system in the geodetic coordinates (obtained directly from the translation matrix) and the heading angle of the coordinate system deflection (using the rotation matrix to convert the quaternion to the Euler angle to obtain the heading angle information). The longitude and latitude of the coordinate origin are then converted according to the geodetic coordinate system (in the geodetic coordinate system, the coordinate values are converted into longitude and latitude data with the help of the conversion coefficients obtained previously, and the calculation formula is: lat = north / latRad + lat0; lon = east / lonRad + lon0).

[0040] According to the above process, the conversion relationship between the indoor local space rectangular coordinate system and the outdoor latitude and longitude coordinate system can be obtained.

[0041] In order to make the calculated data more accurate, multiple groups of data can be selected for calculation and then the average value can be obtained.

[0042] S400, determining multiple test points representing calibration points on the test vehicle and the target object, performing coordinate conversion within the indoor positioning area based on the capture and conversion relationship of the motion capture system, and obtaining indoor positioning data corresponding to the multiple test points.

[0043] Specifically, according to the requirements of ADAS testing, straight road, curve, following, emergency braking, overtaking, parking, specified speed driving, rain and fog working condition tests are carried out. First, multiple test points are determined on the test vehicle and the target object, and reflective balls are attached to the test points. When driving to the indoor positioning area, the motion capture system is used to capture the motion form of the balls to obtain the vehicle's position data (coordinate points), speed and attitude information (attitude angle) in the indoor local space rectangular coordinate system; the indoor positioning data obtained based on the conversion relationship of coordinate transformation includes but is not limited to longitude and latitude, velocity component of northeast ground, heading angle and timestamp, among which the timestamp is directly obtained through the motion capture system, and the longitude and latitude, velocity component of northeast ground and heading angle are obtained through coordinate transformation. The specific conversion process is as follows:

[0044] According to the rotation and translation relationship between the indoor local space rectangular coordinate system and the geodetic coordinate system obtained in S300, the coordinate point of the indoor local space rectangular coordinate system of the test point output by the motion capture system can be converted to the geodetic coordinate system; then the longitude and latitude are converted to the geodetic coordinate system.

[0045] The calculation of the northeast ground velocity component is based on the indoor local rectangular coordinate velocity data Vx, Vy, and Vz of the test point output by the motion capture system;

[0046] Ve=-1*Vx*cos(-1*refernceHeadig*Π / 180)-Vz*sin(-1*refernceHeadig*Π / 180);

[0047] Vn=-1*Vx*sin(-1*refernceHeadig*Π / 180)+Vz*cos(-1*refernceHeadig*Π / 180);

[0048] Vd=-1*Vy;

[0049] Among them, Vx, Vy, and Vz represent the velocities in the three coordinate axis directions output by the motion capture system; Ve, Vn, and Vd represent the northeast ground velocity respectively; refernceHeadig represents the reference heading angle of the indoor local rectangular coordinate system, that is, the deflection angle between the indoor local space rectangular coordinate system and the geodetic coordinate system (the heading angle of the coordinate system deflection obtained above).

[0050] Heading angle = reference heading angle of the indoor local rectangular coordinate system - Euler angle in the Y-axis direction.

[0051] S500: Forward multiple indoor positioning data in a preset manner.

[0052] Specifically, the obtained indoor positioning data needs to be forwarded through different preset methods and frequencies according to different needs.

[0053] The default method includes encapsulating the data in accordance with the inertial indoor positioning data encapsulation format (GAD data format defined by OxTS inertial navigation) through the Generic Aiding Data Software Development Kit (GAD SDK), and then sending it to the inertial indoor positioning system (the integrated indoor positioning system of the OxTS inertial navigation system specially installed on the vehicle) for indoor positioning.

[0054] The preset method also includes sending the data to a device (such as an inertial navigation system) that needs indoor positioning data through the User Datagram Protocol (UDP) at a set frequency in accordance with a custom data protocol.

[0055] The preset method also includes combining the data into GPS data formats such as GPGGA and GPRMC and forwarding them to different receiving devices according to the set sending frequency through the User Datagram Protocol.

[0056] The preset methods are not limited to the above three, and the transmission method and path can be designed according to actual needs.

[0057] Based on the above calibration method for indoor complex scene automobile testing, a calibration system for indoor complex scene automobile testing is also provided, the system comprising:

[0058] A motion capture system module is configured to establish an indoor local space rectangular coordinate system within the indoor positioning area to obtain the coordinates of the calibration point or the test point in the indoor local space rectangular coordinate system, including but not limited to obtaining the velocity and posture information of the test point in the indoor local space rectangular coordinate system;

[0059] The coordinate conversion input point information acquisition module is used to select a number of calibration points and calculation strategies according to the overlap between the indoor positioning area and the outdoor positioning area, and simultaneously obtain the coordinates of the calibration points in the indoor local space rectangular coordinate system and the longitude and latitude information in the outdoor longitude and latitude coordinate system, and aggregate them to form the coordinate conversion input point information;

[0060] A coordinate conversion module is used to obtain the conversion relationship between the indoor local space rectangular coordinate system and the outdoor latitude and longitude coordinate system according to the coordinate conversion input point information;

[0061] The test module is used to determine multiple test points representing calibration points on the test vehicle and the target object, perform coordinate conversion based on the motion capture system capture and conversion relationship within the indoor positioning area, and obtain indoor positioning data corresponding to the multiple test points.

[0062] It can be understood that this system can fully execute the above-mentioned calibration method for indoor complex scene automobile testing and can achieve the same effect. The specific process will not be repeated here.

[0063] This embodiment provides a calibration method and system for automobile testing in complex indoor scenarios, which solves the problem in existing ADAS testing that vehicles cannot be accurately positioned in areas with weak GNSS signals such as tunnels and garages, resulting in the inability to conduct effective ADAS testing. This solution can achieve centimeter-level high-precision positioning even when GNSS signals are limited, accurately measure and capture the position, speed, heading and other motion information of the object, and obtain high-precision indoor positioning data through coordinate conversion. In the above-mentioned areas, indoor positioning data can be used instead of outdoor positioning data to conduct ADAS testing. This solution is suitable for parking and driving performance testing of intelligent connected vehicles in complex environments such as tunnels, indoor test sites, rain and fog.

[0064] The above is only an embodiment of the present invention. Common knowledge such as the specific structure and characteristics of the scheme is not described in detail here. Ordinary technicians in the relevant field are aware of all common technical knowledge in the technical field of the invention before the application date or priority date, can obtain all existing technologies in the field, and have the ability to apply conventional experimental means before that date. Ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the guidance of this application. Some typical well-known structures or well-known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several variations and improvements can be made, which should also be regarded as the scope of protection of the present invention. These will not affect the effect of the implementation of the present invention and the practicality of the patent.

Claims

1. A calibration method for indoor complex scene automobile testing, characterized in that: The method comprises: S100, setting up a motion capture system in the indoor positioning area and establishing an indoor local space rectangular coordinate system; S200, selecting a number of calibration points and calculation strategies based on the overlap between the indoor positioning area and the outdoor positioning area, and simultaneously obtaining the coordinates of the calibration points in the indoor local space rectangular coordinate system and the latitude and longitude information in the outdoor latitude and longitude coordinate system, and aggregating them to form coordinate conversion input point information; S300, obtaining a conversion relationship between an indoor local space rectangular coordinate system and an outdoor latitude and longitude coordinate system based on coordinate conversion input point information; S400, determining a plurality of test points representing calibration points on the test vehicle and the target object, and obtaining indoor positioning data corresponding to the plurality of test points based on the capture and conversion relationship of the motion capture system within the indoor positioning area.

2. The calibration method for indoor complex scene vehicle testing according to claim 1, characterized in that: In S100, the motion capture system includes a high-speed infrared camera group, which is set in an indoor positioning area, and the viewing angles of at least two adjacent infrared cameras have overlapping parts.

3. The calibration method for indoor complex scene vehicle testing according to claim 1, characterized in that: In S200, the indoor positioning area and the outdoor positioning area have an overlapping area that meets the requirements: The coordinates of several calibration points in the overlapping area in the indoor local space rectangular coordinate system are obtained through the motion capture system; at the same time, the longitude and latitude information of these calibration points in the outdoor longitude and latitude coordinate system are obtained through high-precision positioning inertial navigation.

4. The calibration method for indoor complex scene vehicle testing according to claim 1, characterized in that: In S200, the indoor positioning area and the outdoor positioning area have no overlapping area or have an overlapping area that does not meet the requirements: Set up a total station at the intersection of the indoor positioning area and the outdoor positioning area; The coordinates of several calibration points in the indoor local space rectangular coordinate system are obtained through the motion capture system; According to the coordinates of the plurality of calibration points, a coordinate system corresponding to the indoor local space rectangular coordinate system is established on the total station; The coordinates of several calibration points in the outdoor positioning area are obtained by total station measurement; at the same time, the longitude and latitude information of these calibration points in the outdoor longitude and latitude coordinate system are obtained by high-precision positioning inertial navigation.

5. The calibration method for indoor complex scene automobile testing according to claim 1, characterized in that: In S300, the coordinates of the plurality of calibration points are converted into input point information to calculate the latitude and longitude of the origin of the indoor local space rectangular coordinate system and the heading angle of the coordinate axis deflection, thereby obtaining the conversion relationship between the indoor local space rectangular coordinate system and the outdoor latitude and longitude coordinate system.

6. The calibration method for indoor complex scene vehicle testing according to claim 5, characterized in that: Select one of the calibration points as the reference point, establish a geodetic coordinate system with the reference point as the origin and a heading angle of 0; calculate the coordinates of the other calibration points in the geodetic coordinate system based on the latitude and longitude of the other calibration points; Based on the two sets of coordinate values of other calibration points in the indoor local space rectangular coordinate system and the geodetic coordinate system, the rotation and translation matrices of the two coordinate systems are calculated; Based on the rotation and translation matrix, the coordinates of the origin of the indoor local space rectangular coordinate system in the geodetic coordinate system and the heading angle of the coordinate system deflection are obtained; then the longitude and latitude of the coordinate origin are obtained according to the geodetic coordinate system conversion.

7. The calibration method for indoor complex scene vehicle testing according to claim 1, characterized in that: Indoor positioning data includes but is not limited to latitude and longitude, velocity component of northeast, heading angle, and timestamp.

8. The calibration method for indoor complex scene vehicle testing according to claim 1, characterized in that: It also includes S500, which forwards all indoor positioning data in a preset manner.

9. The calibration method for indoor complex scene automobile testing according to claim 1, characterized in that: The preset method includes but is not limited to: using a general auxiliary data software development kit to encapsulate the data in accordance with the inertial navigation indoor positioning data encapsulation format, and then sending it to the inertial navigation indoor positioning system for indoor positioning; using a custom data protocol, sending it to a device that requires indoor positioning data at a preset frequency through a user datagram protocol; combining the data into a GPS data format through a user datagram protocol at a preset sending frequency and forwarding it to at least one of different receiving devices.

10. A calibration system for indoor complex scene automobile testing, characterized by: The system comprises: A motion capture system module is configured to establish an indoor local space rectangular coordinate system within the indoor positioning area to obtain the coordinates of the calibration point or the test point in the indoor local space rectangular coordinate system, including but not limited to obtaining the velocity and posture information of the test point in the indoor local space rectangular coordinate system; The coordinate conversion input point information acquisition module is used to select a number of calibration points and calculation strategies according to the overlap between the indoor positioning area and the outdoor positioning area, and simultaneously obtain the coordinates of the calibration points in the indoor local space rectangular coordinate system and the longitude and latitude information in the outdoor longitude and latitude coordinate system, and aggregate them to form the coordinate conversion input point information; A coordinate conversion module is used to obtain the conversion relationship between the indoor local space rectangular coordinate system and the outdoor latitude and longitude coordinate system according to the coordinate conversion input point information; The test module is used to determine multiple test points representing calibration points on the test vehicle and the target object, perform coordinate conversion based on the motion capture system capture and conversion relationship within the indoor positioning area, and obtain indoor positioning data corresponding to the multiple test points.

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