Beidou navigation positioning optimization method and system

Abstract

The invention relates to the technical field of path navigation and positioning, in particular to a Beidou navigation and positioning optimization method and system, and the method comprises the steps: collecting a positioning point of a vehicle on a planimetric map at each moment and vehicle driving data; acquiring a surrounding path of the vehicle according to the positioning point of the vehicle; calculating a positioning point error distance according to the vehicle driving data of the vehicle; according to the distance between the surrounding paths of the vehicle and the distance between the positioning point of the vehicle and the surrounding paths, obtaining a same-direction attribution discrimination index of the vehicle to the surrounding paths; calculating the positioning data difference of the vehicle at each moment according to the vehicle driving data and the positioning points of the vehicle at the adjacent moments; obtaining the navigation track matching degree of the vehicle and the surrounding path according to the same-direction attribution discrimination index and the positioning data difference; and obtaining a navigation positioning path of the vehicle at each moment according to the navigation track matching degree, and completing map-assisted positioning of the vehicle. Therefore, optimization of the Beidou navigation positioning method is realized.

Description

Technical Field

[0001] The present invention relates to the field of path navigation and positioning technology, and in particular to a Beidou navigation and positioning optimization method and system. Background Art

[0002] With the improvement of social living standards, urban transportation roads are gradually increasing, and the complexity of roads has brought great challenges to vehicle driving. At present, most vehicles are equipped with satellite navigation and positioning systems, which can provide drivers with road selection and assist driving. The commonly used satellite navigation positioning method is the BD / DR combined positioning method based on satellite navigation and inertial navigation. This method uses the position information provided by the BD satellite navigation system and the motion information provided by the inertial sensor, and uses the Kalman filter algorithm to achieve a fusion estimation of position and velocity, combining the advantages of satellite navigation and inertial navigation, thereby achieving higher positioning accuracy and stability.

[0003] When using the BD / DR combined positioning method for electronic map-assisted positioning, the direct projection algorithm is often used as a map-assisted positioning algorithm to locate the vehicle's position on the map. However, when the vehicle drives to a complex intersection, due to the complex road conditions, it is easy to cause the error of Beidou satellite positioning to be greater than the distance between roads. At this time, the accuracy of using the direct projection algorithm to locate the vehicle is poor. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a Beidou navigation positioning optimization method and system, and the technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present invention provides a Beidou navigation positioning optimization method, the method comprising the following steps:

[0006] Collect the vehicle's location point on the plane map and vehicle driving data at each moment. The vehicle driving data includes: vehicle speed, vehicle acceleration and direction;

[0007] The surrounding path of the vehicle is obtained according to the positioning point of the vehicle at each moment; the positioning point error distance is calculated according to the vehicle driving data of the vehicle at each moment; the central starting point of the surrounding path is obtained according to the endpoint of the surrounding path of the vehicle; the direct projection accuracy of the vehicle at each moment is obtained according to the distance between the central starting points of each surrounding path and the distance between the positioning point of the vehicle and the central starting point of each surrounding path; the same-direction belonging discrimination index of the vehicle to the surrounding path is obtained according to the direction of the vehicle, the surrounding path, the central starting point of the surrounding path and the direct projection accuracy;

[0008] The difference in the positioning data of the vehicle at each moment is calculated based on the vehicle speed and positioning point at adjacent moments; the degree of matching of the navigation trajectory of the vehicle with the surrounding paths at each moment is obtained based on the same-direction belonging discrimination index of the vehicle to the surrounding paths at each moment and the difference in positioning data; the navigation positioning path of the vehicle at each moment is obtained based on the matching degree of the navigation trajectory.

[0009] Further, the obtaining of the surrounding path of the vehicle according to the positioning point of the vehicle at each moment includes:

[0010] The vehicle's positioning point at each moment is taken as the center and the preset length is used as the radius to construct the vehicle's surrounding area; the roads contained in the vehicle's surrounding area are taken as the vehicle's surrounding path at each moment.

[0011] Further, the calculation of the positioning point error distance according to the vehicle driving data of the vehicle at each moment includes:

[0012] For the t-th moment, the square of the preset time interval is calculated to obtain the product of the vehicle acceleration at the t-1th moment and the square, which is recorded as the first product; the product of the vehicle speed at the t-1th moment and the preset time interval is calculated, which is recorded as the second product;

[0013] Calculate the sum of the vehicle speed at the t-1th moment and the vehicle speed at the tth moment, and record it as a first sum; obtain the ratio of the first sum to 2, and record the product of the ratio and the preset time interval as a third product;

[0014] The sum of the first product and the second product is calculated and recorded as the second sum, and the absolute value of the difference between the second sum and the third product is used as the positioning point error distance of the vehicle at the tth moment.

[0015] Further, obtaining the central starting point of the surrounding path according to the endpoints of the surrounding path of the vehicle includes:

[0016] The line connecting the two end points of each surrounding path is recorded as the path starting line of each surrounding path, the path midline of each surrounding path is obtained, and the intersection point of the path starting line and the path midline is taken as the central starting point of each surrounding path.

[0017] Further, obtaining the direct projection accuracy of the vehicle at each moment according to the distances between the central starting points of the surrounding paths and the distances between the positioning point of the vehicle and the central starting points of the surrounding paths includes:

[0018] For the t-th moment, a preset number of moments before and including the t-th moment is taken as an observation window, and the mean of the positioning point error distances of all moments in the observation window is calculated and recorded as the first mean;

[0019] Calculating the Euclidean distances between the center starting points of adjacent surrounding paths, and obtaining the minimum value of the Euclidean distances of all adjacent surrounding paths;

[0020] Calculate the ratio of the minimum value to the first mean; record the Euclidean distance between the vehicle's positioning point and the central starting point of each surrounding path as the plane distance between the vehicle and each surrounding path; obtain the mean of the plane distances between the vehicle's positioning point and all surrounding paths, recorded as the second mean; and use the product of the ratio and the second mean as the direct projection accuracy of the vehicle at the tth moment.

[0021] Further, the obtaining of the same-direction belonging discrimination index of the vehicle to the surrounding path according to the direction of the vehicle, the surrounding path, the central starting point of the surrounding path and the direct projection accuracy includes:

[0022] At the t-th moment, the tangent line of the path midline of each surrounding path at the central starting point is used as the path projection line of the surrounding path; the vertical distance between the vehicle's positioning point and the path projection line of the surrounding path is obtained, which is recorded as the direct projection distance;

[0023] The acute angle between the direction of the vehicle and the path projection line of the surrounding path is recorded as the direction angle between the vehicle and the surrounding path; the product of the arc value of the direction angle and the error distance of the positioning point of the vehicle at the tth moment is calculated, and recorded as the first product;

[0024] Calculate the difference between 1 and the direct projection accuracy at the t-th moment, obtain the maximum value between the difference and 0, and record the product of the maximum value and the first product as the second product;

[0025] Calculate the product of the direct projection distance and the direct projection accuracy at the t-th moment, recorded as the third product; obtain the sum of the second product and the third product;

[0026] Calculate the product of the vehicle speed at the tth moment and the preset time interval, which is recorded as the fourth product; obtain the ratio of the sum and the fourth product; calculate the opposite of the ratio, and use the calculation result of the exponential function with a natural constant as the base and the opposite as the exponent as the vehicle's same-direction belonging discrimination index for the surrounding paths.

[0027] Further, the calculation of the positioning data difference of the vehicle at each moment according to the vehicle speed and positioning point at adjacent moments includes:

[0028] For the tth moment, calculate the product of the vehicle speed at the t-1th moment and the preset time interval; obtain the Euclidean distance between the positioning point of the vehicle at the t-1th moment and the positioning point of the vehicle at the tth moment; and record the absolute value of the difference between the product and the Euclidean distance as the positioning data difference of the vehicle at the tth moment.

[0029] Further, the obtaining of the degree of matching of the navigation track of the vehicle with the surrounding paths at each moment according to the same-direction belonging discrimination index of the vehicle to the surrounding paths at each moment and the positioning data difference includes:

[0030] For the t-th moment, a preset number of moments before and including the t-th moment is used as a projection adjustment window at the t-th moment; obtaining the maximum value of the positioning data differences of all moments in the projection adjustment window, and calculating the ratio of the positioning data difference at the t-th moment to the maximum value;

[0031] The product of the vehicle's same-direction belonging discrimination index for the surrounding paths at the t-th moment and the ratio is calculated; and the sum of the products at all moments in the projection adjustment window is used as the degree of matching of the vehicle's navigation trajectory with the surrounding paths at the t-th moment.

[0032] Further, obtaining the navigation positioning path of the vehicle at each moment according to the navigation trajectory matching degree includes:

[0033] The maximum value of the matching degree of the navigation track of the vehicle and all surrounding paths at each moment is obtained, and the surrounding path corresponding to the maximum value is used as the navigation positioning path of the vehicle at each moment.

[0034] In a second aspect, an embodiment of the present invention further provides a Beidou navigation positioning optimization system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of any one of the above-mentioned methods when executing the computer program.

[0035] The present invention has at least the following beneficial effects:

[0036] The present invention proposes a Beidou navigation positioning optimization method and system. The method analyzes the direct projection distance from the positioning point as a vehicle belonging path judgment index through the traditional direct projection algorithm, that is, the road with the shortest direct projection distance is used as the navigation positioning road of the vehicle, and the influence of the angle data of the vehicle sensor and the error data of the positioning point on the calculation accuracy of the direct projection distance is not fully considered; since the vehicle positioning point in the traditional direct projection algorithm is calculated by combining the speed and acceleration of the vehicle at the previous moment, the error distance of the positioning point is calculated by the difference between the speed and acceleration of the vehicle at the previous moment and the vehicle speed at this moment, and the quantification of the positioning error is realized; by analyzing the influence of the path complexity in the surrounding area of ​​the vehicle on the effectiveness of the direct projection algorithm, the direct projection accuracy is calculated in combination with the positional relationship between the vehicle positioning point and the surrounding path and the positioning error, reflecting the use of the direct projection algorithm at each moment. The positioning effectiveness is improved; in order to improve the traditional direct projection algorithm and make the calculation of the direct projection distance more accurate, the projection error distance of the direct projection distance is calculated according to the error distance of the positioning point and the vehicle direction, which is used as the vehicle belonging path judgment index of the improved algorithm, avoiding the influence of the positioning point error on the direct projection algorithm and improving the navigation positioning accuracy of the vehicle when it travels to a complex intersection; according to the direct projection accuracy, the weights of the traditional and improved vehicle belonging path judgment indicators are set respectively, avoiding the problem that the angle data difference between the vehicle direction and the surrounding path direction at non-complex intersections is small, resulting in poor positioning effect of the improved algorithm; finally, in order to avoid the problem of positioning error caused by large single data error, the vehicle positioning data at multiple times are calculated together to obtain the navigation trajectory matching degree, and the vehicle's navigation positioning path is obtained according to the navigation trajectory matching degree, thereby improving the accuracy of navigation and positioning of the vehicle during driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0038] Figure 1 A flowchart of a Beidou navigation positioning optimization method provided by an embodiment of the present invention;

[0039] Figure 2 A schematic diagram of the surrounding path of the vehicle;

[0040] Figure 3 Schematic diagram of the projection error distance of the vehicle during driving. DETAILED DESCRIPTION

[0041] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the Beidou navigation positioning optimization method and system proposed by the present invention, its specific implementation method, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0042] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0043] The following is a detailed description of a Beidou navigation positioning optimization method and system provided by the present invention in conjunction with the accompanying drawings.

[0044] See also Figure 1 , which shows a flowchart of a Beidou navigation positioning optimization method provided by an embodiment of the present invention, the method comprising the following steps:

[0045] Step S001, obtaining the positioning point of the vehicle on the plane map, and using the vehicle-mounted sensor to obtain the vehicle driving data.

[0046] Get map data, which is a flat map with road areas marked. s, obtain vehicle driving data through on-board sensors, vehicle driving data includes: vehicle speed , vehicle acceleration ,direction The vehicle's positioning point on the plane map is obtained through the BD / DR combined positioning technology.

[0047] During vehicle driving A moment, such as Figure 2 As shown, this embodiment takes the positioning point of the vehicle as the center. The length of is the radius to construct the area around the vehicle; the roads contained in the area around the vehicle are the surrounding paths of the vehicle, and a total of surrounding paths; connecting the endpoints of the surrounding paths to obtain the path starting line; obtaining the path midline of each surrounding path; recording the intersection of the path starting line and the path midline as the central starting point of the surrounding path.

[0048] At this point, the positioning point and vehicle driving data of the vehicle at each moment can be obtained according to the above method of this embodiment.

[0049] Step S002, obtaining the surrounding paths of the vehicle according to the positioning point of the vehicle; calculating the positioning point error distance according to the vehicle driving data; obtaining the same-direction belonging discrimination index of the vehicle to the surrounding paths according to the distance between the surrounding paths of the vehicle and the distance between the positioning point of the vehicle and each surrounding path.

[0050] When using the direct projection algorithm for map-assisted positioning, the distance between the vehicle's positioning point coordinates and the actual vehicle coordinates is greater than the distance between different roads at the intersection, resulting in inaccurate matching of the vehicle's road. Therefore, the direct projection algorithm can be improved by combining the accuracy of satellite positioning and the vehicle's direction data to obtain better map-assisted positioning results. First, the positioning error of the vehicle at each moment is quantified, and the positioning point error distance is calculated based on the vehicle driving data. The calculation formula is:

[0051]

[0052] In the formula, for The positioning point error distance at the moment; yes Acceleration data at the moment; , They are Moment and Vehicle speed data at the moment; is the time interval.

[0053] When the BD / DR combined positioning method is used for positioning, the position to be moved to at the next moment will be predicted based on the motion state at the previous moment and combined with Newton's laws of motion, and then the position of the positioning point will be corrected. However, in the actual vehicle operation process, the driver may brake or accelerate, causing the acceleration of the vehicle to change, resulting in errors between the positioning point coordinates and the actual vehicle coordinates. In the formula, the movement of the vehicle in a short period of time is regarded as uniformly accelerated linear motion, and Calculated from the motion data at all times The vehicle speed data at the moment is then calculated Time has come Predicted displacement between moments , according to the calculation The vehicle speed data at the moment is different from the actual Calculation of vehicle speed data at the moment Time has come The actual displacement between the two moments; the difference between the two is taken as Error distance of the moment positioning point The larger the value, the greater the error distance of the positioning point.

[0054] Furthermore, the complexity of the path in the area around the vehicle is determined based on the relationship between the vehicle positioning point and the surrounding path, and the effectiveness of the direct projection algorithm is determined based on the positioning error. First, the effectiveness of the direct projection algorithm is calculated based on the reasons for the inaccurate road matching of the vehicle analyzed above. At this moment, the path where the vehicle is located is taken as the starting path, and the remaining surrounding paths are sorted in a clockwise direction. The sequence number of each surrounding path is obtained to construct the direct projection accuracy:

[0055]

[0056] In the formula, yes Direct projection accuracy of the moment; yes The number of paths around the vehicle at the moment; yes Time has come The error distance of the positioning point at all times within the time period of time The mean of The experience value of is 10; yes The vehicle's The surrounding paths and The Euclidean distance between the center starting points of the surrounding paths; The vehicle positioning point and The Euclidean distance between the center starting points of the surrounding paths; is the minimum value function.

[0057] The above formula will Time has come The time period is The observation window of the moment, the positioning point error distance at each moment in the observation window The mean of is used as the predicted positioning point error distance at the next moment; the Euclidean distance between the center starting points of the surrounding paths is further compared with the positioning point error distance at the next moment. When the ratio is less than or equal to 1, it means that the positioning point error distance at this time is large. When it is greater than or equal to the spacing of the surrounding paths, the effect of using the direct projection algorithm for map-assisted positioning is poor, and the direct projection accuracy at this time is low; at this time, the greater the Euclidean distance between the vehicle positioning point and the center starting points of each surrounding path, the farther the vehicle is from the intersection, and the higher the effectiveness of the direct projection algorithm. Finally, the greater the value of the effectiveness of the direct projection algorithm, the better the effect of using the direct projection algorithm at this time, and when the value is greater than or equal to 1, the direct projection algorithm is fully capable of map-assisted positioning.

[0058] The first The tangent line of the path midline of the surrounding paths at the central starting point is used as the path projection line. The vertical distance between the vehicle's positioning point and the path projection line of the surrounding paths is obtained and recorded as the direct projection distance ; Change the direction of the vehicle to The acute angle between the path projection lines of the surrounding paths is recorded as the vehicle The direction angle between the moment and the surrounding path .

[0059] Calculate the vehicle's same-direction identification index for surrounding paths:

[0060]

[0061] In the formula, for Time vehicle pair The same-direction belonging discrimination index of surrounding paths; Time vehicle and The direct projection distance between the surrounding paths; The positioning point error distance at the moment; For vehicles in Moment and The direction angle between the surrounding paths; Direct projection accuracy of the moment; is the maximum value function; For vehicles in The vehicle speed at the time; is the time interval; is an exponential function with a natural constant as its base.

[0062] like Figure 3 As shown in the figure, the point with the vehicle's positioning point as the starting point and the moving length along the vehicle's driving direction equal to the positioning point error distance is taken as the actual vehicle position; at this time, the vector with the vehicle's positioning point as the starting point and the actual vehicle position as the end point and the path direction form a sector, the radius is the positioning point error distance, the vehicle direction and the path direction are respectively the directions of the two sides of the sector, and the projection error distance of the direct projection distance is approximately the arc length of the sector; when the arc length of the sector is smaller and closer to 0, it means that the influence of the positioning point error on the direct projection distance is smaller and the vehicle's driving direction is more consistent with the direction of the path, then the larger the same-direction belonging discrimination index is, the more likely the vehicle belongs to the path. This is the improved vehicle path determination index. It is the vehicle path determination index of the traditional direct projection algorithm. and It is the weight assigned to the two according to the accuracy of direct projection. When the effectiveness of the direct projection algorithm is high, that is, the effectiveness of the direct projection algorithm is greater than 1, only the traditional direct projection algorithm is used to judge the vehicle's path; when the effectiveness of the direct projection algorithm is low, the improved algorithm will occupy a larger weight to judge the vehicle's path. The reason is that the improved algorithm combines the direction data of the road, and when the vehicle is at a non-complex intersection, the direction difference between roads is small, and the improved algorithm is difficult to calculate the difference between paths, and its positioning effect is poor. Therefore, the effectiveness of the direct projection algorithm is used as the weight to switch between the traditional direct projection algorithm and the improved direct projection algorithm, avoiding the problem that the improved algorithm has a poor positioning effect when the vehicle drives to a non-complex intersection. It is the driving distance of the vehicle between two sampling moments. The larger the distance, the greater the tolerance of the calculation result of the same-direction belonging discrimination index to the error of the direct projection distance. At this time, the larger the same-direction belonging discrimination index, the more likely the vehicle belongs to this path.

[0063] Step S003, calculating the positioning data difference of the vehicle at each moment; obtaining the navigation trajectory matching degree between the vehicle and the surrounding path according to the same-direction belonging discrimination index and the positioning data difference; obtaining the navigation positioning path of the vehicle at each moment according to the navigation trajectory matching degree.

[0064] Although the error distance of the positioning point can be calculated, it is easy to cause vehicle positioning errors if only the vehicle positioning data at a certain moment is used. Therefore, the vehicle positioning data at multiple moments should be calculated together to complete map-assisted positioning. Calculate the matching degree of the navigation track:

[0065]

[0066]

[0067] In the formula, yes The difference in positioning data at the moment, yes Time vehicle and The matching degree of navigation trajectory of surrounding paths; For vehicles in The vehicle speed at the time; is the time interval; The vehicle is The anchor point of time and The anchor point of time The Euclidean distance between Is the projection adjustment window size, experience value ; for Time vehicle pair The same-direction belonging discrimination index of surrounding paths; is the maximum value function.

[0068] By vehicle The distance traveled at the time minus Moment and The Euclidean distance between the positioning points at the moment indicates the difference between the positioning point and the vehicle-mounted sensor data. The larger the positioning data difference, the less credible the same-direction belonging discrimination index calculated based on the positioning data at this moment. In the projection adjustment window of the data at this moment, the normalized value of the positioning data difference is used as the weight, and the same-direction belonging discrimination index is weightedly added to obtain the navigation trajectory matching degree. The larger the value, the more likely the vehicle belongs to the first path.

[0069] exist The matching degree between the vehicle and the navigation trajectory of all surrounding paths is calculated at all times, and the surrounding path corresponding to the maximum matching degree of the navigation trajectory is selected as the vehicle's The navigation positioning path at the moment, that is, the driving road.

[0070] At this point, the map-assisted positioning of the vehicle is completed, and the Beidou navigation positioning method is optimized.

[0071] Based on the same inventive concept as the above method, an embodiment of the present invention also provides a Beidou navigation positioning optimization system, including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of any one of the above-mentioned Beidou navigation positioning optimization methods are implemented.

[0072] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The above is a description of a specific embodiment of this specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0073] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0074] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A Beidou navigation positioning optimization method, characterized in that: The method comprises the following steps: Collect the vehicle's location point on the plane map and vehicle driving data at each moment. The vehicle driving data includes: vehicle speed, vehicle acceleration and direction; The surrounding path of the vehicle is obtained according to the positioning point of the vehicle at each moment; the positioning point error distance is calculated according to the vehicle driving data of the vehicle at each moment; the central starting point of the surrounding path is obtained according to the endpoint of the surrounding path of the vehicle; the direct projection accuracy of the vehicle at each moment is obtained according to the distance between the central starting points of each surrounding path and the distance between the positioning point of the vehicle and the central starting point of each surrounding path; the same-direction belonging discrimination index of the vehicle to the surrounding path is obtained according to the direction of the vehicle, the surrounding path, the central starting point of the surrounding path and the direct projection accuracy; The difference in the positioning data of the vehicle at each moment is calculated based on the vehicle speed and positioning point at adjacent moments; the degree of matching of the navigation trajectory of the vehicle with the surrounding paths at each moment is obtained based on the same-direction belonging discrimination index of the vehicle to the surrounding paths at each moment and the difference in positioning data; the navigation positioning path of the vehicle at each moment is obtained based on the matching degree of the navigation trajectory.

2. A Beidou navigation positioning optimization method as claimed in claim 1, characterized in that: The method of obtaining the surrounding path of the vehicle according to the positioning point of the vehicle at each moment includes: The vehicle's positioning point at each moment is taken as the center and the preset length is used as the radius to construct the vehicle's surrounding area; the roads contained in the vehicle's surrounding area are taken as the vehicle's surrounding path at each moment.

3. A Beidou navigation positioning optimization method as claimed in claim 1, characterized in that: The calculating of the positioning point error distance according to the vehicle driving data of the vehicle at each moment includes: For the t-th moment, the square of the preset time interval is calculated to obtain the product of the vehicle acceleration at the t-1th moment and the square, which is recorded as the first product; the product of the vehicle speed at the t-1th moment and the preset time interval is calculated, which is recorded as the second product; Calculate the sum of the vehicle speed at the t-1th moment and the vehicle speed at the tth moment, and record it as a first sum; obtain the ratio of the first sum to 2, and record the product of the ratio and the preset time interval as a third product; The sum of the first product and the second product is calculated and recorded as the second sum, and the absolute value of the difference between the second sum and the third product is used as the positioning point error distance of the vehicle at the tth moment.

4. A Beidou navigation positioning optimization method as claimed in claim 1, characterized in that: The step of obtaining the central starting point of the surrounding path according to the endpoints of the surrounding path of the vehicle comprises: The line connecting the two end points of each surrounding path is recorded as the path starting line of each surrounding path, the path midline of each surrounding path is obtained, and the intersection point of the path starting line and the path midline is taken as the central starting point of each surrounding path.

5. A Beidou navigation positioning optimization method as claimed in claim 1, characterized in that: The obtaining of the direct projection accuracy of the vehicle at each moment according to the distances between the central starting points of the surrounding paths and the distances between the positioning point of the vehicle and the central starting points of the surrounding paths comprises: For the t-th moment, a preset number of moments before and including the t-th moment is taken as an observation window, and the mean of the positioning point error distances of all moments in the observation window is calculated and recorded as the first mean; Calculating the Euclidean distances between the center starting points of adjacent surrounding paths, and obtaining the minimum value of the Euclidean distances of all adjacent surrounding paths; Calculate the ratio of the minimum value to the first mean; record the Euclidean distance between the vehicle's positioning point and the central starting point of each surrounding path as the plane distance between the vehicle and each surrounding path; obtain the mean of the plane distances between the vehicle's positioning point and all surrounding paths, recorded as the second mean; and use the product of the ratio and the second mean as the direct projection accuracy of the vehicle at the tth moment.

6. A Beidou navigation positioning optimization method as claimed in claim 1, characterized in that: The method of obtaining a same-direction belonging discrimination index of the vehicle to the surrounding paths according to the direction of the vehicle, the surrounding paths, the central starting point of the surrounding paths, and the direct projection accuracy includes: At the t-th moment, the tangent line of the path midline of each surrounding path at the central starting point is used as the path projection line of the surrounding path; the vertical distance between the vehicle's positioning point and the path projection line of the surrounding path is obtained, which is recorded as the direct projection distance; The acute angle between the direction of the vehicle and the path projection line of the surrounding path is recorded as the direction angle between the vehicle and the surrounding path; the product of the arc value of the direction angle and the error distance of the positioning point of the vehicle at the tth moment is calculated, and recorded as the first product; Calculate the difference between 1 and the direct projection accuracy at the t-th moment, obtain the maximum value between the difference and 0, and record the product of the maximum value and the first product as the second product; Calculate the product of the direct projection distance and the direct projection accuracy at the t-th moment, recorded as the third product; obtain the sum of the second product and the third product; Calculate the product of the vehicle speed at the tth moment and the preset time interval, which is recorded as the fourth product; obtain the ratio of the sum and the fourth product; calculate the opposite of the ratio, and use the calculation result of the exponential function with a natural constant as the base and the opposite as the exponent as the vehicle's same-direction belonging discrimination index for the surrounding paths.

7. A Beidou navigation positioning optimization method as claimed in claim 1, characterized in that: The calculating of the positioning data difference of the vehicle at each moment according to the vehicle speed and positioning point at adjacent moments includes: For the tth moment, calculate the product of the vehicle speed at the t-1th moment and the preset time interval; obtain the Euclidean distance between the positioning point of the vehicle at the t-1th moment and the positioning point of the vehicle at the tth moment; and record the absolute value of the difference between the product and the Euclidean distance as the positioning data difference of the vehicle at the tth moment.

8. A Beidou navigation positioning optimization method as claimed in claim 1, characterized in that: The method of obtaining the matching degree of the navigation track of the vehicle with the surrounding paths at each moment according to the same-direction belonging discrimination index of the vehicle to the surrounding paths at each moment and the positioning data difference includes: For the t-th moment, a preset number of moments before and including the t-th moment is used as a projection adjustment window at the t-th moment; obtaining the maximum value of the positioning data differences of all moments in the projection adjustment window, and calculating the ratio of the positioning data difference at the t-th moment to the maximum value; The product of the vehicle's same-direction belonging discrimination index for the surrounding paths at the t-th moment and the ratio is calculated; and the sum of the products at all moments in the projection adjustment window is used as the degree of matching of the vehicle's navigation trajectory with the surrounding paths at the t-th moment.

9. A Beidou navigation positioning optimization method as claimed in claim 1, characterized in that: The obtaining of the navigation positioning path of the vehicle at each time according to the matching degree of the navigation track includes: The maximum value of the matching degree of the navigation track of the vehicle and all surrounding paths at each moment is obtained, and the surrounding path corresponding to the maximum value is used as the navigation positioning path of the vehicle at each moment.

10. A Beidou navigation positioning optimization system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 9 are implemented.

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