Multi-dimensional signal processing method of smart city big data positioning system

Abstract

The invention discloses a multi-dimensional signal processing method of a smart city big data positioning system. The method comprises the following steps: constructing a virtual positioning three-dimensional model; constructing a positioning three-dimensional coordinate axis; establishing a position correction base station, and obtaining a spherical domain by taking the position correction base station as a circle center and the target distance as a radius; obtaining interference intersection points of the spherical domain and the solid model, carrying out stress analysis on each interference intersection point, and calculating the support state of the interference intersection points to screen out interference intersection points without support; and calculating dimension coordinate values of the to-be-measured target points one by one, and gradually screening out interference intersection points of which the dimension coordinate values are not consistent until the last interference intersection point is screened out. According to the method, the multi-dimensional virtual positioning three-dimensional model is constructed, the interference intersection point of the spherical surface domain and the entity model is obtained, the final dimension coordinate value of the target point to be detected is obtained through a series of analysis and screening of the interference intersection point, the target point to be detected is screened and determined from the multi-dimensional surface, and the accuracy of the target dimension in the spatial dimension is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of urban big data positioning signal analysis and processing, and in particular to a multi-dimensional signal processing method for a smart city big data positioning system. Background Art

[0002] Smart cities use various information technologies or innovative concepts to connect and integrate urban systems and services to improve the efficiency of resource utilization, optimize urban management and services, and improve the quality of life of citizens. In the construction of smart cities, precise positioning of targets can effectively control vehicle traffic and the flow of people in public places. For example, accurate positioning of elevated vehicles can effectively determine the approximate number of elevated vehicles and the degree of congestion, so as to set certain control gates at the elevated entrances to prevent vehicle congestion and blockage.

[0003] Taking public transportation places as an example, since some public transportation places have different elevation dimensions, such as multi-storey parking lots in shopping malls and multi-storey viaducts, target vehicles at the same horizontal position are not necessarily at the same height dimension. It is impossible to determine the exact position of the target vehicle by relying solely on the positioning signal of a single dimension.

[0004] Urban public transportation environments, shopping malls and other public activity venues are mostly multi-dimensional three-dimensional spaces and are relatively complex. Existing positioning technologies rely solely on the positioning signal coordinates of a single dimension and cannot accurately determine the precise position of the target on the height dimension, so the positioning accuracy on the height dimension is low. Summary of the invention

[0005] To this end, the present invention provides a multi-dimensional signal processing method for a smart city big data positioning system, which effectively solves the problem that the positioning technology in the prior art only relies on the positioning signal coordinates of a single dimension and cannot accurately determine the precise position of the target on the height dimension, and the positioning accuracy on the height dimension is low.

[0006] In order to solve the above technical problems, the present invention specifically provides the following technical solutions: a multi-dimensional signal processing method for a smart city big data positioning system, comprising:

[0007] Construct an arc domain with reference to the surface of the area to be positioned, and construct a vertical domain vertically upward along the surface, and construct a solid model on the arc domain and the vertical domain in combination with the physical parameters of the area to be positioned to obtain a virtual positioning three-dimensional model;

[0008] A point is randomly selected from the inner side of the surface of the virtual positioning three-dimensional model as a positioning base point, and a positioning three-dimensional coordinate axis is constructed on the virtual positioning three-dimensional model with the positioning base point as the zero point;

[0009] Establish at least one calibration base station between the area to be positioned and the positioning base point, obtain the target distance between the calibration base station and the target point to be measured at the calibration base station, and obtain a spherical domain with the calibration base station as the center and the target distance as the radius;

[0010] Obtain the interference intersection points on the spherical domain that intersect with the solid model, perform force analysis on each interference intersection point, calculate the support state of the interference intersection point, and screen out the interference intersection points without support;

[0011] The positioning system is used to measure the azimuth and pitch of the target point to be measured, and the measured data is substituted into the dimensional coordinate calculation formula to calculate the x, y, and z dimensional coordinate values ​​of the target point to be measured in the three-dimensional positioning coordinate axis one by one, and the interference intersection points with inconsistent dimensional coordinate values ​​are gradually screened out until the last interference intersection point remains and is output as the target point to be measured.

[0012] Further,

[0013] The calibration distance between the calibration base station and the zero point is smaller than the distance between the entity model corresponding to all height planes in the area to be positioned and the zero point;

[0014] The calibration base station is established between the arc surface area and the positioning base point, and is located on the z-axis of the positioning three-dimensional coordinate axis;

[0015] The distances from the positioning base point to each position on the arc surface are equal.

[0016] Further,

[0017] Creating a set of entity points in the three-dimensional positioning coordinate axis according to entity parameters of the area to be positioned, wherein the entity model is formed by combining the set of entity points;

[0018] The solid model takes the arc surface domain as a base surface and extends along the vertical domain direction.

[0019] Further,

[0020] The interference intersection point between the spherical domain and the solid model is the point where the spherical surface formed by the spherical domain intersects with the domain surface of the solid model;

[0021] Wherein, the interference intersection points are all located outside the arc surface area and on a side away from the positioning base point.

[0022] Further,

[0023] The specific steps of performing force analysis on the interference intersection point include:

[0024] Taking the interference intersection as the starting point, a power lead is drawn along the direction of the connecting line between the interference intersection and the positioning base point;

[0025] Taking the interference intersection as a starting point, drawing a support line in a direction away from and perpendicular to the domain surface of the solid model corresponding to the interference intersection;

[0026] Drawing branch leads for the support leads along the straight line direction corresponding to the power leads;

[0027] Analyze and determine the directions of the branch leads and the power leads.

[0028] Further,

[0029] In the case where the branch lead and the power lead are in the same direction, it is determined that the interference intersection point has no support;

[0030] In the case where the branch lead and the power lead are in opposite directions, it is determined that the interference intersection point has support;

[0031] The target point to be measured can move on the solid model domain surface corresponding to the interference intersection point where support exists.

[0032] Further,

[0033] Using a positioning system to measure the azimuth and elevation of the target point to be measured at the calibration base station;

[0034] The specific steps of measuring the azimuth and elevation of the target point to be measured include:

[0035] Establishing a direction-finding three-dimensional coordinate axis at the calibration base station;

[0036] Calculate the angle between the mapping line of the connection line between the calibration base station and the target point to be measured along the (x1, y1) plane and the y1 axis as the azimuth;

[0037] The angle between the connection line between the calibration base station and the target point to be measured and the mapping line is calculated as the pitch angle.

[0038] Further,

[0039] After filtering out the interference intersection points without support, coordinate comparisons are performed between the remaining interference intersection points in the x, y, and z axes, and the coincidence rates of the coordinate values ​​in the x, y, and z axes are calculated;

[0040] According to the values ​​of the coincidence rates of the coordinate values ​​in the x, y, and z axes, the calculation programs of the dimensional coordinate values ​​in the x, y, and z axes are prioritized;

[0041] The dimensional coordinate calculation formula used in the calculation program for the dimensional coordinate values ​​of the x, y, and z axes is:

[0042]

[0043] Among them, x is the x-axis dimension coordinate value of the target point to be measured, y is the y-axis dimension coordinate value of the target point to be measured, z is the z-axis dimension coordinate value of the target point to be measured, r is the calibration distance between the calibration base station and the zero point, s is the minimum distance from the target point to be measured to the spherical surface where the calibration base station is located, ∠A is the pitch angle, and ∠B is the azimuth angle.

[0044] Further,

[0045] The priority of the calculation programs corresponding to the dimensional coordinate values ​​of the x, y, and z axes are arranged from high to low according to the coincidence rate values ​​of the coordinate values ​​in the x, y, and z axes.

[0046] Further,

[0047] In the process of comparing the calculation result of the dimensional coordinate calculation formula with the dimensional coordinate value of the interference intersection, the data correlation between the calculation result and the dimensional coordinate value of the interference intersection is calculated, and the interference intersections with data correlation lower than the correlation threshold are marked as interference intersections with inconsistent dimensional coordinate values ​​and screened out.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] In the present invention, an arc domain is constructed along the surface of the area to be positioned, a vertical domain is constructed vertically upward along the arc domain, and a multi-dimensional virtual positioning three-dimensional model is constructed from the plane dimension and the vertical dimension upward from the plane. In addition, a spherical domain is constructed to obtain the interference intersection points of the spherical domain and the solid model. The interference intersection points may be the target points to be measured. After a series of analyses and screening of the interference intersection points, the final dimensional coordinate values ​​of the target points to be measured are obtained. Based on the target distance, the target points to be measured are screened and determined from multiple dimensions. By increasing the screening work along the vertical dimension of the plane, the accuracy of the target dimension in the spatial dimension is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0051] Figure 1 A flowchart of a multi-dimensional signal processing method for a smart city big data positioning system provided by an embodiment of the present invention;

[0052] Figure 2 is a schematic diagram of a virtual positioning three-dimensional model in an embodiment of the present invention;

[0053] Figure 3is a schematic diagram of a lateral three-dimensional coordinate axis in an embodiment of the present invention;

[0054] Figure 4 is a schematic diagram of a bottom azimuth angle and a bottom pitch angle in an embodiment of the present invention;

[0055] Figure 5 is a schematic diagram of a physical model in an embodiment of the present invention;

[0056] Figure 6 Schematic diagram of force analysis for interference intersection;

[0057] Figure 7 for Figure 6 A is an enlarged schematic diagram.

[0058] The numbers in the figure represent the following:

[0059] 1-calibration base station; 2-positioning base point; 3-arc domain; 4-vertical domain; 5-spherical surface where the calibration base station is located; 6-target point to be measured; 7-spherical domain; 8-first power lead; 9-first support lead; 10-first branch lead; 11-second power lead; 12-second support lead; 13-second branch lead; 14-azimuth; 15-pitch angle; 16-physical model; 17-bottom azimuth; 18-bottom pitch angle; DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] like Figure 1 and Figure 2 As shown, the present invention provides a multi-dimensional signal processing method for a smart city big data positioning system, comprising:

[0062] Construct an arc domain with reference to the surface of the area to be positioned, and construct a vertical domain vertically upward along the surface, and construct a solid model on the arc domain and the vertical domain in combination with the physical parameters of the area to be positioned to obtain a virtual positioning three-dimensional model;

[0063] A point is randomly selected from the inner side of the surface of the virtual positioning three-dimensional model as a positioning base point, and a positioning three-dimensional coordinate axis is constructed on the virtual positioning three-dimensional model with the positioning base point as the zero point;

[0064] Establish at least one calibration base station between the area to be positioned and the positioning base point, obtain the target distance between the calibration base station and the target point to be measured at the calibration base station, and obtain a spherical domain with the calibration base station as the center and the target distance as the radius;

[0065] Obtain the interference intersection points on the spherical domain that intersect with the solid model, perform force analysis on each interference intersection point, calculate the support state of the interference intersection point, and screen out the interference intersection points without support;

[0066] The positioning system is used to measure the azimuth and pitch of the target point to be measured, and the measured data is substituted into the dimensional coordinate calculation formula to calculate the x, y, and z dimensional coordinate values ​​of the target point to be measured in the three-dimensional positioning coordinate axis one by one, and the interference intersection points with inconsistent dimensional coordinate values ​​are gradually screened out until the last interference intersection point remains and is output as the target point to be measured.

[0067] In the present invention, the target distance is used as a reference for the gradual screening and determination of the target point to be measured. Therefore, the target distance requires a certain degree of accuracy. The target distance refers to the distance between the calibration base station and the target point to be measured. In the actual measurement process, the positioning pulse signal is usually obtained through the positioning system, and the target distance is obtained by processing the positioning pulse signal. In order to improve the accuracy of the overall final positioning information, at least two calibration base stations can be established between the area to be positioned and the positioning base point. The distances between the two calibration base stations and the positioning base point are consistent. The signal recognition method provided by the present invention is performed once for the target distance corresponding to each calibration base station. That is to say, two signal recognition processing processes are performed to obtain two target points to be measured. By comparing the overlap of the two target points to be measured, the final target point to be measured can be determined and calculated.

[0068] In the present invention, an arc domain is constructed along the surface of the area to be positioned, and a vertical domain is constructed vertically upward with the arc domain as the base surface, and a multi-dimensional virtual positioning three-dimensional model is constructed from the plane dimension and the vertical dimension upward from the plane. In addition, a spherical domain is constructed to obtain the interference intersection points of the spherical domain and the solid model. The interference intersection points may be the target points to be measured. After a series of analyses and screening of the interference intersection points, the final dimensional coordinate values ​​of the target points to be measured are obtained. Based on the target distance, the target points to be measured are screened and determined from multiple dimensions. By increasing the screening work along the vertical dimension of the plane, the accuracy of the target dimension in the spatial dimension is improved.

[0069] A city is taken as the area to be positioned. Since the surface of the earth can be regarded as an arc surface, the surface of the city can also be regarded as an arc surface. The surface of the city is approximately analogized to an arc surface domain. The arc surface domain is a vertical domain extending vertically upward from the base surface, in order to provide a three-dimensional space for the virtual positioning three-dimensional model.

[0070] Among them, the distance from the positioning base point to each position of the arc surface is equal. In actual application, as an embodiment of the present invention, the center of mass of the earth is used as the position of the positioning base point. This design is also for the subsequent force analysis process to use the gravity generated as the "power" corresponding to the interference intersection.

[0071] Therefore, the calibration base station can also be regarded as being on a sphere, the center position of which corresponds to the center of mass of the earth. If there are two calibration base stations, both of them are set on the sphere, and the calibration distance between the calibration base station and the zero point is less than the distance between the physical model corresponding to all height planes in the area to be positioned and the zero point. That is to say, the calibration base station is closer to the zero point (center of mass of the earth) than the physical model corresponding to all height planes in the area to be positioned. The calibration base station is established between the arc domain and the positioning base point. In addition, in each multi-dimensional signal processing process, no matter where the calibration base station is actually located, the virtual positioning three-dimensional model is rotated around the positioning base point, and the calibration base station is adjusted to the z-axis of the positioning three-dimensional coordinate axis, and then subsequent signal processing is performed. This step is for the convenience of analysis. The angle information between the calibration base station and the target point to be measured can directly obtain the relationship between the corresponding target point to be measured and the positioning three-dimensional coordinate axis, thereby deriving the corresponding dimensional coordinate calculation formula:

[0072]

[0073] Among them, x is the x-axis dimension coordinate value of the target point to be measured, y is the y-axis dimension coordinate value of the target point to be measured, z is the z-axis dimension coordinate value of the target point to be measured, r is the calibration distance between the calibration base station and the zero point, s is the minimum distance from the target point to be measured to the spherical surface where the calibration base station is located (the sphere corresponding to the spherical surface where the calibration base station is located coincides with the positioning base point), ∠A is the pitch angle, and ∠B is the azimuth angle.

[0074] In the present invention, a physical point set is created in the positioning three-dimensional coordinate axis according to the physical parameters of the area to be positioned, and the physical model is formed by combining the physical point set, wherein the physical model takes the arc domain as the base surface and extends along the vertical domain direction. The arc domain and the vertical domain are equivalent to forming a virtual three-dimensional space. The physical model constructs a virtual positioning three-dimensional model in the three-dimensional space. The physical model can be a proportional model of a public transportation space, such as a spiral viaduct, such as Figure 5 As shown in the figure, the simplified solid model of the spiral viaduct intersects with the spherical domain. This situation belongs to the case where the spiral viaduct is just near the calibration base station. Figure 5 This is an example diagram to facilitate the explanation of the force analysis process.

[0075] In the area to be positioned, a corresponding virtual positioning three-dimensional model is composed of multiple solid models, wherein the interference intersection between the spherical domain and the solid model is the point where the spherical surface formed by the spherical domain intersects with the solid model domain surface. Since the interference intersection is used to screen and determine the target point to be measured, the target point to be measured moves in the area to be positioned and cannot be on the side of the arc domain close to the positioning base point. Therefore, the interference intersection is located outside the arc domain on the side away from the positioning base point.

[0076] like Figure 5 As shown in the figure, after determining the interference intersection point between the spherical domain and the solid model, it is necessary to perform force analysis on the interference intersection point.

[0077] The specific steps for force analysis of interference intersections include:

[0078] Take the interference intersection as the starting point and draw the power lead line along the direction of the connecting line between the interference intersection and the positioning base point;

[0079] Taking the interference intersection as the starting point, draw a support line in a direction away from and perpendicular to the domain surface of the solid model corresponding to the interference intersection;

[0080] Draw branch leads for the support leads along the corresponding straight line direction of the power leads;

[0081] Analyze and determine the direction of branch leads and power leads.

[0082] When the directions of the branch lead and the power lead are consistent, it is determined that the interference intersection point has no support;

[0083] When the branch lead and the power lead are in opposite directions, it is determined that the interference intersection point has support;

[0084] The target point to be measured can move on the solid model domain surface corresponding to the interference intersection point with support.

[0085] In the above embodiment, the process of force analysis is to screen out the interference intersections without support, that is, to screen out the interference intersections that do not conform to the laws of nature and cannot become the target points to be measured.

[0086] As Figure 5 Take it as an example, the force analysis diagram is as follows Figure 6 and Figure 7 As shown, the force analysis process of the interference intersection point a and the interference intersection point c is described below:

[0087] Taking the interference intersection a as the starting point, draw the first power lead 8 along the direction of the connecting line between the interference intersection a and the positioning base point; taking the interference intersection a as the starting point, draw the first support lead 9 in the direction away from and perpendicular to the domain surface of the solid model corresponding to the interference intersection a; draw the first branch lead 10 for the first support lead 9 along the direction of the straight line corresponding to the first power lead 8; wherein, the direction of the first branch lead 10 is opposite to that of the first power lead 8, and it is determined that the interference intersection a has support;

[0088] Taking the interference intersection c as the starting point, draw the second power lead 11 along the direction of the connecting line between the interference intersection c and the positioning base point; taking the interference intersection c as the starting point, draw the second support lead 12 along the direction away from and perpendicular to the domain surface of the solid model corresponding to the interference intersection; draw the second branch lead 13 for the second support lead 12 along the direction of the straight line corresponding to the second power lead 11; wherein, the direction of the second branch lead 13 is consistent with that of the second power lead 11, and it is judged that the interference intersection c has no support (indicating that the target point to be measured cannot move at the interference intersection c, and the interference intersection c cannot be the target point to be measured), and the interference intersection c needs to be screened out.

[0089] In the present invention, the positioning system is used to measure the azimuth and elevation of the target point to be measured at the calibration base station;

[0090] Among them, Figure 3 As shown in FIG. 1 , the specific steps of measuring the azimuth and elevation of the target point to be measured include:

[0091] Establish a three-dimensional coordinate axis for direction finding at the calibration base station;

[0092] Calculate the angle between the mapping line of the connection line between the calibration base station and the target point to be measured along the (x1, y1) plane and the y1 axis as the azimuth angle 14;

[0093] Calculate the angle between the connection line between the calibration base station and the target point to be measured and the mapping line as the pitch angle 15.

[0094] like Figure 4 As shown, there are corresponding bottom azimuth angle 17 and bottom pitch angle 18 in the positioning three-dimensional coordinate axis, wherein the bottom azimuth angle is the angle between the mapping line of the positioning base point and the target point to be measured along the (x, y) plane and the y-axis, and the bottom pitch angle is the angle between the mapping line of the positioning base point and the target point to be measured.

[0095] Among them, the bottom azimuth angle and the azimuth angle have the same value, and there is a certain quantitative relationship between the bottom pitch angle and the pitch angle. According to the quantitative relationship and the triangle and side length relationship corresponding to the spatial triangle formed in the positioning three-dimensional coordinate axis, the dimensional coordinate calculation formula is derived. Among them, the dimensional coordinate calculation formula used in the calculation program of the dimensional coordinate values ​​of the x, y, and z axes is:

[0096]

[0097] Wherein, x is the x-axis coordinate value of the target point to be measured, y is the y-axis coordinate value of the target point to be measured, z is the z-axis coordinate value of the target point to be measured, r is the calibration distance between the calibration base station and the zero point, s is the minimum distance from the target point to be measured to the spherical surface where the calibration base station is located, ∠A is the pitch angle, and ∠B is the azimuth angle.

[0098] In the present invention, after the azimuth angle and the pitch angle are measured, the dimensional coordinate values ​​of the target points to be measured can be calculated one by one.

[0099] Before calculating the dimensional coordinate values ​​of the target point to be measured, the coordinates of the remaining interference intersections after filtering out the unsupported interference intersections are compared in pairs in the x, y, and z axes, and the coincidence rate of the coordinate values ​​in the x, y, and z axes is calculated;

[0100] The calculation procedures for the dimensional coordinate values ​​of the x, y, and z axes are prioritized according to the values ​​of the coincidence rates of the coordinate values ​​of the x, y, and z axes.

[0101] The priority of the calculation programs corresponding to the dimensional coordinate values ​​of the x, y, and z axes are arranged from high to low according to the coincidence rate values ​​of the coordinate values ​​in the x, y, and z axes.

[0102] The specific implementation process of the above embodiment is as follows: assuming that after filtering out the interference intersections without support, the remaining interference intersections are a, b, d, and e, and the coordinates of the interference intersections a, b, d, and e are compared in the x, y, and z directions, and the x, y, and z coordinate values ​​of the interference intersections a, b, d, and e are checked to see whether there is overlap, and the coordinate value overlap rate in the x, y, and z directions is calculated, where the coordinate value overlap rate is the ratio of the number of overlaps to the total number of comparisons, assuming that there are 2 overlapped coordinate values ​​in the x dimension, and the corresponding coordinate value overlap rate in the x dimension is 2 / 6=1 / 3;

[0103] According to the numerical values ​​of the coordinate value overlap rates of the x, y, and z axes, the calculation programs of the dimensional coordinate values ​​of the x, y, and z axes are prioritized in order. The numerical values ​​of the coordinate value overlap rates of the x, y, and z axes correspond to the priority of the calculation programs of the dimensional coordinate values ​​of the x, y, and z axes from high to low. Assuming that the coordinate value overlap rates of the x and y dimensions are both 1 / 3, and the coordinate value overlap rate of the z dimension is 0, then the calculation program of the dimensional coordinate value of the z axis has the highest priority, that is, the dimensional coordinate value of the z dimension of the target point to be measured is calculated first. Since the dimensional coordinate values ​​of the z dimension of the interference intersection are not repeated, the calculated value will only correspond to one of the interference intersections. The interference intersections whose dimensional coordinate values ​​of other z dimensions do not match can be screened out through a calculation program of the dimensional coordinate value of the z axis, and there is no need to calculate the dimensional coordinate values ​​of the x and y dimensions. This design can not only determine the dimensional coordinate value of the target point to be measured from the three-dimensional space, but also greatly speed up the determination speed (calculation speed) of the target point to be measured.

[0104] In the above embodiment, the x-, y-, and z-axis coordinate comparison between the interference intersection points a, b, d, and e does not require that the values ​​between the two interference intersection points are completely consistent in order to determine that there are duplications in the corresponding axial coordinate values ​​between the interference intersection points. It can also be determined that there are duplications between the two interference intersection points when there is a certain degree of similarity between the values, so as to avoid errors in the actual calculation process that lead to inaccurate coordinates of the corresponding interference intersection points.

[0105] In the present invention, in the process of comparing the calculation result of the dimensional coordinate calculation formula with the dimensional coordinate value of the interference intersection, the data correlation between the calculation result and the dimensional coordinate value of the interference intersection is calculated, and the interference intersections with data correlation lower than the correlation threshold are marked as interference intersections with inconsistent dimensional coordinate values ​​and screened out.

[0106] Assuming that the correlation threshold is 0.950, taking the calculation result of the dimensional coordinate value of the z dimension as an example, assuming that its calculation result is different from the dimensional coordinate value of the z-axis direction of a certain interference intersection, but the data correlation between its final calculation result and the dimensional coordinate value of the z-axis direction of the interference intersection is 0.987, then the interference intersection is determined to be the final target point to be measured, and the final coordinates of the target point to be measured are calculated.

[0107] The above embodiments are only exemplary embodiments of the present application and are not intended to limit the present application. The protection scope of the present application is defined by the claims. Those skilled in the art may make various modifications or equivalent substitutions to the present application within the essence and protection scope of the present application, and such modifications or equivalent substitutions shall also be deemed to fall within the protection scope of the present application.

Claims

1. A multi-dimensional signal processing method for a smart city big data positioning system, characterized in that: include: Construct an arc domain with reference to the surface of the area to be positioned, and construct a vertical domain vertically upward along the surface, and construct a solid model on the arc domain and the vertical domain in combination with the physical parameters of the area to be positioned to obtain a virtual positioning three-dimensional model; A point is randomly selected from the inner side of the surface of the virtual positioning three-dimensional model as a positioning base point, and a positioning three-dimensional coordinate axis is constructed on the virtual positioning three-dimensional model with the positioning base point as the zero point; Establish at least one calibration base station between the area to be positioned and the positioning base point, obtain the target distance between the calibration base station and the target point to be measured at the calibration base station, and obtain a spherical domain with the calibration base station as the center and the target distance as the radius; Obtain the interference intersection points on the spherical domain that intersect with the solid model, perform force analysis on each interference intersection point, calculate the support state of the interference intersection point, and screen out the interference intersection points without support; The positioning system is used to measure the azimuth and pitch of the target point to be measured, and the measured data is substituted into the dimensional coordinate calculation formula to calculate the x, y, and z dimensional coordinate values ​​of the target point to be measured in the three-dimensional positioning coordinate axis one by one, and the interference intersection points with inconsistent dimensional coordinate values ​​are gradually screened out until the last interference intersection point remains and is output as the target point to be measured.

2. The multi-dimensional signal processing method of the smart city big data positioning system according to claim 1 is characterized in that: The calibration distance between the calibration base station and the zero point is smaller than the distance between the entity model corresponding to all height planes in the area to be positioned and the zero point; The calibration base station is established between the arc surface area and the positioning base point, and is located on the z-axis of the positioning three-dimensional coordinate axis; The distances from the positioning base point to each position on the arc surface are equal.

3. The multi-dimensional signal processing method of the smart city big data positioning system according to claim 1 is characterized in that: Creating a set of entity points in the three-dimensional positioning coordinate axis according to entity parameters of the area to be positioned, wherein the entity model is formed by combining the set of entity points; The solid model takes the arc surface domain as a base surface and extends along the vertical domain direction.

4. The multi-dimensional signal processing method of the smart city big data positioning system according to claim 2 is characterized in that: The interference intersection point between the spherical domain and the solid model is the point where the spherical surface formed by the spherical domain intersects with the domain surface of the solid model; Wherein, the interference intersection points are all located outside the arc surface area and on a side away from the positioning base point.

5. The multi-dimensional signal processing method of the smart city big data positioning system according to claim 4 is characterized in that: The specific steps of performing force analysis on the interference intersection point include: Taking the interference intersection as the starting point, a power lead is drawn along the direction of the connecting line between the interference intersection and the positioning base point; Taking the interference intersection as a starting point, drawing a support line in a direction away from and perpendicular to the domain surface of the solid model corresponding to the interference intersection; Drawing branch leads for the support leads along the straight line direction corresponding to the power leads; Analyze and determine the directions of the branch leads and the power leads.

6. The multi-dimensional signal processing method of the smart city big data positioning system according to claim 5 is characterized in that: In the case where the branch lead and the power lead are in the same direction, it is determined that the interference intersection point has no support; In the case where the branch lead and the power lead are in opposite directions, it is determined that the interference intersection point has support; The target point to be measured can move on the solid model domain surface corresponding to the interference intersection point where support exists.

7. The multi-dimensional signal processing method of the smart city big data positioning system according to claim 5 is characterized in that: Using a positioning system to measure the azimuth and elevation of the target point to be measured at the calibration base station; The specific steps of measuring the azimuth and elevation of the target point to be measured include: Establishing a direction-finding three-dimensional coordinate axis at the calibration base station; Calculate the angle between the mapping line of the connection line between the calibration base station and the target point to be measured along the (x1, y1) plane and the y1 axis as the azimuth; The angle between the connection line between the calibration base station and the target point to be measured and the mapping line is calculated as the pitch angle.

8. The multi-dimensional signal processing method of the smart city big data positioning system according to claim 1 is characterized in that: After filtering out the interference intersection points without support, coordinate comparisons are performed between the remaining interference intersection points in the x, y, and z axes, and the coincidence rates of the coordinate values ​​in the x, y, and z axes are calculated; According to the values ​​of the coincidence rates of the coordinate values ​​in the x, y, and z axes, the calculation programs of the dimensional coordinate values ​​in the x, y, and z axes are prioritized; The dimensional coordinate calculation formula used in the calculation program for the dimensional coordinate values ​​of the x, y, and z axes is: Among them, x is the x-axis dimension coordinate value of the target point to be measured, y is the y-axis dimension coordinate value of the target point to be measured, z is the z-axis dimension coordinate value of the target point to be measured, r is the calibration distance between the calibration base station and the zero point, s is the minimum distance from the target point to be measured to the spherical surface where the calibration base station is located, ∠A is the pitch angle, and ∠B is the azimuth angle.

9. The multi-dimensional signal processing method of the smart city big data positioning system according to claim 8 is characterized in that: The priority of the calculation programs corresponding to the dimensional coordinate values ​​of the x, y, and z axes are arranged from high to low with the values ​​of the coincidence rates of the coordinate values ​​in the x, y, and z axes corresponding to the dimensional coordinate values ​​of the x, y, and z axes.

10. The multi-dimensional signal processing method of the smart city big data positioning system according to claim 9, characterized in that: In the process of comparing the calculation result of the dimensional coordinate calculation formula with the dimensional coordinate value of the interference intersection, the data correlation between the calculation result and the dimensional coordinate value of the interference intersection is calculated, and the interference intersections with data correlation lower than the correlation threshold are marked as interference intersections with inconsistent dimensional coordinate values ​​and screened out.

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