Visibility probability determination method and apparatus, computer device, and storage medium

Abstract

A visibility probability determination method executed by a computer device. The method comprises: determining an obstruction of an object to be positioned, and on the basis of a space occupation parameter of the obstruction, respectively performing inward contraction and outward expansion on the external contour of the obstruction represented by the space occupation parameter to obtain error modeling data (202); on the basis of the error modeling data, determining an inward contraction boundary determined by means of inward contraction and an outward expansion boundary determined by means of outward expansion, and using the inward contraction boundary and the outward expansion boundary to construct an error space range of the obstruction (204); acquiring a candidate location of said object, and on the basis of a linear signal propagation path between a satellite location of a satellite and the candidate location, determining a spatial location relationship between the linear signal propagation path and the error space range (206); and determining a visibility probability value of the satellite for the candidate location on the basis of the spatial location relationship, the visibility probability value being used for determining a satellite-based positioning location of said object in combination with the candidate location (208).

Description

Method, device, computer equipment and storage medium for determining visual probability

[0001] Related applications

[0002] This application claims priority to Chinese patent application number 2024101738030, filed on February 6, 2024, entitled “Method, device, computer device and storage medium for determining visual probability”, the entire text of which is hereby incorporated by reference. Technical Field

[0003] The present application relates to the field of satellite positioning, and in particular to a method, apparatus, computer equipment and storage medium for determining visibility probability. Background Art

[0004] The Global Navigation Satellite System (GNSS), also known as the Global Navigation Satellite System, is an airborne radio navigation and positioning system that can provide users with all-weather three-dimensional coordinates, velocity, and time information at any location on the Earth's surface or in near-Earth space.

[0005] At present, the satellite visibility obtained based on the signal-to-noise ratio judgment standard can be used as a reference benchmark. The satellite spatial visibility obtained based on the existing 3D building model and satellite azimuth, elevation and other information can be scored for the possible position of the object to be located in the map. The positioning position of the object to be located is then determined by the visibility score.

[0006] However, in actual positioning, the influence of terrain often leads to a reduction in the number of visible satellites. In other words, when obstacles block the view of the satellites, there will be a large error in the accuracy of satellite visibility, thus reducing the accuracy of satellite-based object positioning. Summary of the Invention

[0007] The present application provides a method, apparatus, computer device, and storage medium for determining visual probability.

[0008] In a first aspect, the present application provides a method for determining visual probability, performed by a computer device, the method comprising:

[0009] Determine an obstruction of the object to be located, and based on a space occupancy parameter of the obstruction, shrink and expand an outer contour of the obstruction represented by the space occupancy parameter to obtain error modeling data;

[0010] Determining, based on the error modeling data, a shrinking boundary determined by the shrinking and an expanding boundary determined by the expanding, and constructing an error space range of the obstruction using the shrinking boundary and the expanding boundary;

[0011] Obtaining a candidate position of the object to be positioned, and determining a spatial positional relationship between the straight-line signal propagation path and the error space range based on a straight-line signal propagation path between the satellite position of the satellite and the candidate position;

[0012] According to the spatial position relationship, a visibility probability value of the satellite for the candidate position is determined, and the visibility probability value is used to determine the satellite positioning position of the object to be positioned in combination with the candidate position.

[0013] In a second aspect, the present application further provides a device for determining visual probability, the device comprising:

[0014] a modeling module for determining an obstruction of the object to be located, and based on a space occupancy parameter of the obstruction, shrinking and expanding an outer contour of the obstruction represented by the space occupancy parameter to obtain error modeling data;

[0015] an error space range construction module, configured to determine, based on the error modeling data, an inward contraction boundary determined by the inward contraction and an outward expansion boundary determined by the outward expansion, and construct the error space range of the obstruction using the inward contraction boundary and the outward expansion boundary;

[0016] a spatial position relationship determination module, configured to obtain a candidate position of the object to be positioned, and determine a spatial position relationship between the straight-line signal propagation path and the error space range based on a straight-line signal propagation path between the satellite position of the satellite and the candidate position;

[0017] The visibility probability value determination module is used to determine the visibility probability value of the satellite for the candidate position according to the spatial position relationship, and the visibility probability value is used to determine the satellite positioning position of the object to be positioned in combination with the candidate position.

[0018] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the above-mentioned method for determining visual probability when executing the computer program.

[0019] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which implements the above-mentioned method for determining the visibility probability when executed by a processor.

[0020] In a fifth aspect, the present application further provides a computer program product, which includes a computer program that implements the above-mentioned method for determining visual probability when executed by a processor.

[0021] The details of one or more embodiments of the present application are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the present application will become apparent from the description, drawings, and claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the conventional technology, the following briefly introduces the drawings required for use in the embodiments or the conventional technology descriptions. Obviously, the drawings described below are merely embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the disclosed drawings without any creative work.

[0023] FIG1 is a diagram illustrating an application environment of a method for determining visibility probability according to an embodiment;

[0024] FIG2 is a schematic flow chart of a method for determining visibility probability according to one embodiment;

[0025] FIG3 is a schematic diagram of splitting multiple obstructions of different heights in one embodiment;

[0026] FIG4 is a schematic diagram of the error space range in one embodiment;

[0027] FIG5 is a schematic diagram of a straight-line signal propagation path in one embodiment;

[0028] FIG6 is a schematic diagram of a process for determining a spatial position relationship in one embodiment;

[0029] FIG7 is a schematic diagram of a top view of a spatial position relationship in one embodiment;

[0030] FIG8 is a schematic diagram of a side view of a spatial position relationship in one embodiment;

[0031] FIG9 is a schematic diagram of a process for determining a satellite visibility probability value for a candidate location in one embodiment;

[0032] FIG10 is a schematic diagram of a top view of the error space range in one embodiment;

[0033] FIG11 is a schematic diagram of a top-down vertical distance and a top-down vertex distance in one embodiment;

[0034] FIG12 is a schematic diagram of a side view error spatial range in one embodiment;

[0035] FIG13 is a schematic diagram of a side-view vertical distance and a side-view vertex distance in one embodiment;

[0036] FIG14 is a schematic diagram of a process for determining a satellite visibility probability value for a candidate location according to another embodiment;

[0037] FIG15 is a schematic diagram showing that a top-view projection and a top-view outward expansion boundary do not intersect in one embodiment;

[0038] FIG16 is a schematic diagram illustrating the intersection of a top-view projection and a top-view indented boundary in one embodiment;

[0039] FIG17 is a schematic diagram of a process for determining a satellite visibility probability value for a candidate location according to another embodiment;

[0040] FIG18 is a schematic diagram of a complete flow chart of a method for determining visibility probability according to one embodiment;

[0041] FIG19 is a block diagram of a device for determining a visibility probability according to an embodiment;

[0042] FIG20 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0044] The Global Navigation Satellite System (GNSS), also known as the Global Navigation Satellite System (GNSS), is a space-based radio navigation and positioning system that provides users with all-weather three-dimensional coordinates, velocity, and time information anywhere on the Earth's surface or in near-Earth space. Currently, satellite visibility, determined by signal-to-noise ratio (SNR) criteria, is used as a reference. Satellite spatial visibility is scored based on existing 3D building models and information such as satellite azimuth and elevation angles at the possible locations of the object to be located on the map. The visibility score then determines the location of the object to be located. Based on this, the satellite's altitude and azimuth can be calculated from the observation point location and satellite position. If the altitude is below ground level, the object is considered invisible. Other methods consider obstructions along the signal propagation path and calculate the altitude of obstructions in the satellite's direction. The satellite's altitude must be greater than the altitude of the obstruction to be considered visible. However, while these methods consider the impact of obstructions, their modeling of obstructions is relatively simple and does not account for errors in the obstruction data. Furthermore, the output visibility result is a binary value: visible or invisible. However, in actual positioning, the influence of terrain often reduces the number of visible satellites. In other words, when obstacles block the view, there will be a large error in the accuracy of satellite visibility. Therefore, positioning based on inaccurate visibility results will reduce the accuracy of satellite-based object positioning.

[0045] To solve the above problems, the present invention provides a method for determining visual probability that can improve the efficiency of visual probability value determination. Before providing a detailed description, some terms involved in the present invention are first explained.

[0046] The Global Navigation Satellite System (GNSS), also known as the Global Navigation Satellite System (GLONASS), is a space-based radio navigation and positioning system that provides users with all-weather 3D coordinates, velocity, and time information anywhere on the Earth's surface or in near-Earth space. Satellite navigation systems are widely used in navigation, communications, consumer entertainment, mapping, timing, vehicle monitoring and management, and automotive navigation and information services. The overall development trend is to provide high-precision services for real-time applications.

[0047] 2. A mobile terminal or mobile communication terminal refers to a computer device that can be used on the move. Mobile terminals are usually integrated with a global satellite navigation system positioning chip for processing satellite signals and accurately positioning users. They are currently widely used in location services. Based on this, the mobile terminal includes a satellite positioning device and the mobile terminal can obtain satellite observation values. The satellite observation values ​​output by the mobile terminal include pseudorange, pseudorange rate, and accumulated delta range (ADR). Among them, the pseudorange measures the geometric distance from the satellite to the positioning device, the pseudorange rate observation measures the Doppler effect caused by the relative motion of the positioning device and the satellite, and the ADR measures the change in the geometric distance from the satellite to the positioning device.

[0048] 3. Shadow matching positioning: The principle of the shadow matching algorithm is to use the satellite visibility obtained according to the signal-to-noise ratio judgment standard as a reference benchmark. The satellite spatial visibility obtained at the possible positions (search range) of the receiver in the urban canyon is scored based on the existing three-dimensional (3D) building model and satellite azimuth, elevation and other information. The position with the highest score (visibility match) among all possible positions is used as the receiver positioning position.

[0049] The method for determining visibility probability provided in the embodiments of the present application can be applied in the application environment shown in FIG1 . In this embodiment, terminal 102 communicates with server 104 via a network. A data storage system can store data that server 104 needs to process. The data storage system can be integrated with server 104 or placed in the cloud or on another server.

[0050] Specifically, taking the application to server 104 as an example, in the presence of an obstruction that affects the satellite's positioning of the object to be positioned, the server 104 shrinks and expands the obstruction based on the spatial occupancy parameters of the obstruction to obtain error modeling data. Based on this, the server 104 determines the shrinkage boundary determined by shrinkage and the expansion boundary determined by expansion based on the error modeling data, and uses the shrinkage boundary and the expansion boundary to construct the error space range of the obstruction, and obtains the candidate position of the object to be positioned. Based on the straight line signal propagation path between the satellite position and the candidate position, the spatial position relationship between the straight line signal propagation path and the error space range is determined. Thus, the server 104 determines the satellite's visibility probability value for the candidate position based on the spatial position relationship, and the visibility probability value is used to determine the satellite positioning position of the object to be positioned in combination with the candidate position. Since the visible probability value does not directly describe whether the candidate position is visible or invisible in a traditional binary way, but allows for data errors of occluders in a percentage probability way, the visible probability value can more flexibly and accurately describe the occlusion relationship of the occluder to the candidate position. Therefore, on the basis of improving the accuracy of the visible probability value, positioning the object to be positioned based on the aforementioned visible probability value can improve the object positioning accuracy.

[0051] Terminal 102 may be, but is not limited to, various desktop computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices may include smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, and the like. Portable wearable devices may include smart watches, smart bracelets, head-mounted devices, and the like. Server 104 may be implemented as a standalone server or a server cluster consisting of multiple servers. The method for determining visual probability provided in the embodiments of the application can be applied to various scenarios, including but not limited to cloud technology, artificial intelligence, smart transportation, assisted driving, and the like.

[0052] The following embodiment is used for specific explanation: In one embodiment, as shown in FIG2 , a method for determining a visibility probability is provided. This method is described by taking the server 104 in FIG1 as an example. It is understood that the method can also be applied to a system including a terminal 102 and a server 104 and implemented through interaction between the terminal 102 and the server 104. In this embodiment, the method includes the following steps:

[0053] Step 202 : Determine the obstruction of the object to be located, and based on the space occupancy parameters of the obstruction, shrink and expand the outer contour of the obstruction represented by the space occupancy parameters to obtain error modeling data.

[0054] Among them, the space occupancy parameter of the obstruction is in the form of a straight polyhedron, and the space occupancy parameter includes height and vertex coordinates. The height is the height of the obstruction, and the vertex coordinates are specifically the coordinates of the bottom vertices of each bottom surface of the obstruction. The vertex coordinates can be directly longitude and latitude coordinates. Due to actual application requirements, the vertex coordinates can also be plane coordinates converted from longitude and latitude coordinates, which are not specifically limited here. Based on this, the data format of the space occupancy parameter is specifically {P i ,H}, where P i represents the vertex coordinates, H represents the height. The error modeling data is the data obtained after shrinking and expanding based on the space occupation parameters of the occluder, that is, the error modeling data includes the height after shrinking and expanding, and the vertex coordinates after shrinking and expanding.

[0055] Secondly, an obstruction is an object that affects the satellite's positioning of the object to be positioned. Therefore, for the object to be positioned, the obstruction can be single or multiple. If there are multiple obstructions, and the heights of the multiple obstructions are different, that is, in actual applications, there may be situations where obstructions belong to the same obstructing building but have different heights. At this time, the heights of the multiple obstructions that make up the obstructing building can be split to obtain multiple obstructions. For ease of understanding, as shown in Figure 3, Figure 3 (A) shows an obstructing building including obstructions of different heights, and specifically includes obstruction 302 and obstruction 304. Based on the heights of the different obstructions, the obstructing building shown in Figure 3 (A) can be split to obtain obstruction 302 shown in Figure 3 (B) and obstruction 304 shown in Figure 3 (C). As can be seen in Figure 3(B), the spatial occupancy parameters of occluder 302 include the bottom vertex coordinates of multiple bottom vertices. These multiple bottom vertices are the gray bottom vertices in Figure 3(B) that constitute the bottom surface of occluder 302. Similarly, as can be seen in Figure 3(C), the spatial occupancy parameters of occluder 304 include the bottom vertex coordinates of multiple bottom vertices. These multiple bottom vertices are the gray bottom vertices in Figure 3(C) that constitute the bottom surface of occluder 304.

[0056] Specifically, the server first determines whether there is an obstruction that affects the satellite's positioning of the object to be located. The method for determining the obstruction that affects the satellite's positioning of the object to be located can be: the object to be located determines whether there is an obstruction through the quality and / or power of one or more signals between the object to be located and the satellite. Specifically, the presence of an obstruction is determined when the signal between the object to be located and the satellite is attenuated or the signal quality deteriorates. Alternatively, the object to be located can directly capture an image of the obstruction nearby through an image acquisition device to determine the presence of the obstruction. Therefore, the method for determining the obstruction is not specifically limited in this embodiment.

[0057] The server then determines the spatial occupancy parameters of the obstruction. Specifically, it first determines whether the obstruction is single or multiple. If the obstruction is single, the server directly obtains the obstruction's height and the bottom vertex coordinates of each bottom vertex that constitutes the obstruction's bottom surface to obtain the spatial occupancy parameters of the obstruction. If the obstruction is multiple, the server separates the multiple obstructions by height to obtain multiple independent obstructions. The server then obtains the obstruction's height and the bottom vertex coordinates of each bottom vertex that constitutes the obstruction's bottom surface to obtain the spatial occupancy parameters of each obstruction.

[0058] Based on this, the server shrinks and expands the obstruction based on the spatial occupancy parameters of the obstruction, and obtains the data obtained after shrinking and expanding, that is, the error modeling data. From the above introduction, it can be seen that the spatial occupancy parameters include height and vertex coordinates. Then in actual applications, the server can use the contour shrinking and expanding algorithm (Cavalier Contours) of non-self-intersecting polygons to shrink and expand according to the spatial occupancy parameters to obtain error modeling data. Therefore, the error modeling data includes the height after shrinking and expanding, and the vertex coordinates after shrinking and expanding. The Cavalier Contours algorithm performs better in numerical stability, handling overlapping line segments, folded arcs and other problems. It can flexibly deal with various complex situations such as curves, non-convex polygons, self-intersections, etc. in actual applications to ensure the reliability of error modeling data.

[0059] Step 204 : Based on the error modeling data, determine the shrinking boundary determined by shrinking and the expanding boundary determined by expanding, and construct the error space range of the occluder using the shrinking boundary and the expanding boundary.

[0060] The error space includes the outer contour of the occluder. Since an occluder has a front view, a top view, and a side view, its outer contour essentially includes the front view, the top view, and the side view. The front view and the side view are interchangeable; that is, the original front view can be used as the side view, and the original front view contour as the side view contour; or the original side view can be used as the front view, and the original side view contour as the front view contour.

[0061] In an optional embodiment, the error space range includes at least a top-view error space range and a side-view error space range. The top-view error space range is the space range after the top view is expanded and contracted. Since the outer contour of the obstruction exists as a top-view outer contour based on the top view, the top-view expansion boundary and the top-view contraction boundary corresponding to the top-view outer contour can be obtained after expanding and contracting the top view. Then the top-view error space range is composed of the space range between the top-view expansion boundary and the top-view contraction boundary.

[0062] Similarly, it can be known that the side view error space range is the space range after the side view is expanded and contracted. Since the outer contour of the occluder exists as the side view outer contour based on the side view, the side view expansion boundary and the side view contraction boundary corresponding to the side view outer contour can be obtained after the side view is expanded and contracted. Then the side view error space range is composed of the space range between the side view expansion boundary and the side view contraction boundary. And in actual applications, the error space range can also include the front view error space range. Similar to the above, the front view error space range is the space range after the front view is expanded and contracted. Since the outer contour of the occluder exists as the front view outer contour based on the front view, the front view expansion boundary and the front view contraction boundary corresponding to the front view outer contour can be obtained after the front view is expanded and contracted. Then the front view error space range is composed of the space range between the front view expansion boundary and the front view contraction boundary.

[0063] Specifically, based on the error modeling data, the server determines the inner shrinkage boundary determined by shrinkage and the outer expansion boundary determined by outer expansion, and uses the inner shrinkage boundary and the outer expansion boundary to construct the error space range of the obstruction. It can be seen from the above embodiment that the space occupancy parameters include height and vertex coordinates; the error modeling data includes the height after shrinkage and outer expansion, and the vertex coordinates after shrinkage and outer expansion. Therefore, according to the height in the space occupancy parameters and the height after shrinkage and outer expansion in the error modeling data, as well as the vertex coordinates in the space occupancy parameters and the vertex coordinates after shrinkage and outer expansion in the error modeling data, the outer expansion boundary after outer expansion and the inner shrinkage boundary after shrinkage can be obtained, thereby constructing the spatial range between the outer expansion boundary and the inner shrinkage boundary, which is the error space range of the outer contour.

[0064] In a specific embodiment, based on error modeling data, a shrinking boundary determined by shrinking and an expanding boundary determined by expanding are determined, and the shrinking boundary and the expanding boundary are used to construct the error space range of the occupant, including: constructing the expanding boundary of the occupant according to the space occupancy parameters and the height after expansion and the vertex coordinates after expansion in the error modeling data; constructing the shrinking boundary of the occupant according to the space occupancy parameters and the height after shrinking and the vertex coordinates after shrinking in the error modeling data; and determining the space range between the expanding boundary and the shrinking boundary as the error space range including the outer contour of the occupant.

[0065] For ease of understanding, as shown in Figure 4, Figure 4 (A) shows the occluder before it is retracted and expanded. At this time, the occluder parameters include height and vertex coordinates, and the black boundary in Figure 4 (A) is the outer contour of the occluder. By expanding the occluder shown in Figure 4 (A), the height and vertex coordinates after expansion can be obtained. At this time, the expanded occluder as shown in Figure 4 (B) can be constructed. At this time, the black boundary in Figure 4 (B) is the expanded boundary of the occluder. Similarly, by retracting the occluder shown in Figure 4 (A), the height and vertex coordinates after retraction can be obtained. At this time, the retracted occluder as shown in Figure 4 (C) can be constructed. At this time, the black boundary in Figure 4 (C) is the retracted boundary of the occluder.

[0066] Based on this, the obstruction shown in Figure 4 (A), the expanded obstruction shown in Figure 4 (B), and the retracted obstruction shown in Figure 4 (C) are placed in the same position relationship for comparison, and the error space range shown in Figure 4 (D) is obtained. As can be seen from Figure 4 (D), the error space range is the space range between the expanded boundary shown in Figure 4 (B) and the retracted boundary shown in Figure 4 (C), and the error space range includes the outer contour shown in Figure 4 (A).

[0067] Step 206 , obtaining a candidate position of the object to be positioned, and determining a spatial position relationship between the straight-line signal propagation path and the error space range based on a straight-line signal propagation path between the satellite position and the candidate position.

[0068] Candidate locations can be predicted using the historical satellite positioning of the object to be located. Specifically, the historical satellite positioning positions of the object to be located within a preset period of time can be used to form a trajectory of the object to be located. The trajectory trend and positioning time are then used to predict at least one candidate location. Candidate locations can be discrete locations within the predicted area determined according to a preset strategy.

[0069] Among them, the straight-line signal propagation path is specifically the signal propagation path between the satellite position and the candidate position, and the signal propagation path is a straight line. For ease of understanding, as shown in Figure 5, the straight-line signal line 506 between the satellite position 502 of the satellite and the candidate position 504 of the object to be located is the straight-line signal propagation path between the satellite position 502 and the candidate position 504. As can be seen from Figure 5, the satellite signal may be blocked by high-rise buildings. If the candidate position 504 of the object to be located is in the visible area, the satellite is a line-of-sight (LOS) satellite. Conversely, if the candidate position 504 of the object to be located is in the shadowed area, the satellite is a non-line-of-sight (NLOS) satellite.

[0070] It can be seen from this that the spatial position relationship can at least describe: whether the straight signal propagation path intersects or does not intersect with the error space range. In an optional embodiment, it can be seen from the above introduction that the error space range at least includes a top-view error space range and a side-view error space range. The top-view error space range is composed of the space range between the top-view outward expansion boundary and the top-view inward contraction boundary; the side-view error space range is composed of the space range between the side-view outward expansion boundary and the side-view inward contraction boundary. Then the spatial position relationship can consider the spatial position relationship between the top-view projection of the straight signal propagation path on the top-view error space range and the top-view error space range, and consider the spatial position relationship between the side-view projection of the straight signal propagation path on the side-view error space range and the side-view error space range. Therefore, the spatial position relationship includes a top-view spatial position relationship and a side-view spatial position relationship.

[0071] It can be seen from this that the overhead spatial position relationship includes at least: the spatial position relationship between the overhead projection of the straight line signal propagation path on the overhead error space range and the overhead outer expansion boundary, as well as the spatial position relationship between the overhead projection and the overhead inner contraction boundary; the side view spatial position relationship includes at least: the spatial position relationship between the side view projection of the straight line signal propagation path on the side view error space range and the side view outer expansion boundary, as well as the spatial position relationship between the side view projection and the side view inner contraction boundary.

[0072] It is understandable that, since the error space range may also include the orthographic error space range, the spatial position relationship may further consider the spatial position relationship between the orthographic projection of the straight-line signal propagation path on the orthographic error space range and the orthographic error space range, that is, the spatial position relationship may also include the orthographic spatial position relationship. The orthographic spatial position relationship may at least include: the spatial position relationship between the orthographic projection of the straight-line signal propagation path on the orthographic error space range and the orthographic outward expansion boundary, and the spatial position relationship between the orthographic projection and the orthographic inward contraction boundary.

[0073] Specifically, the server first determines the satellite positions and candidate positions of the object to be positioned. The satellite positions are determined using satellite ephemeris. Satellite ephemeris is a dataset of predicted satellite states broadcast periodically to the ground by satellites. Therefore, the satellite positioning augmentation service provider receives satellites within the observable range in real time using a large number of highly sensitive, fixed satellite receiving base stations. After analysis, processing, and encoding by its internal high-precision positioning service processing platform, the server then issues various correction parameters based on the satellites' designated ephemeris codes, various observation parameters, representation parameters, atmospheric corrections, and other factors. The satellite positioning augmentation service provider then obtains corresponding satellite ephemeris data based on the satellite ephemeris codes. The satellite position can then be calculated based on the ephemeris data and various error correction parameters provided by the satellite augmentation provider. Secondly, the candidate positions of the object to be positioned are predetermined using a shadow matching algorithm. In practical applications, other algorithms can also be used to determine the candidate positions of the object to be positioned, but these are not limited here. Furthermore, the server determines the straight-line signal propagation path between the satellite position and the candidate position, and further determines the spatial relationship between the straight-line signal propagation path and the error space range.

[0074] Step 208: Determine the satellite's visibility probability value for the candidate position based on the spatial position relationship. The visibility probability value is used to determine the satellite positioning position of the object to be positioned in combination with the candidate position.

[0075] The visibility probability value represents the probability that the candidate location is visible to the satellite in the presence of an obstruction that affects the satellite's ability to locate the object to be located, and the visibility probability value is used to locate the object to be located. The visibility probability value can be used as a score in the visibility score. In some embodiments, the visibility probability value can be used using the same methods as conventional visibility score scores.

[0076] Specifically, the server determines the probability that the candidate position is visible under the satellite, taking into account the spatial position relationship, that is, obtaining the visible probability value of the candidate position, and thus the server locates the object to be located through the visible probability value. In this embodiment, the process of locating the object to be located by the visible probability value is implemented according to the shadow matching positioning algorithm, that is, the server calculates the distance between the object to be located and the satellite based on the received satellite observation data, and then combines the signal-to-noise ratio and the visible probability value obtained in this application to perform the optimal estimation to obtain the satellite positioning position. A detailed introduction is not given here.

[0077] In one embodiment, it can be determined whether the visibility probability value is greater than or equal to a preset threshold. If so, the candidate location is determined as the satellite positioning location of the object to be located. Furthermore, if not, the candidate location is not determined as the satellite positioning location of the object to be located. The preset threshold can be manually set according to actual needs or determined based on actual testing conditions.

[0078] In one embodiment, for multiple candidate positions, the candidate position with the largest visibility probability value may be determined as the satellite positioning position of the object to be positioned.

[0079] In one embodiment, for multiple candidate locations, the candidate location with the largest visibility probability value, where the visibility probability value is greater than or equal to a preset threshold, may be determined as the satellite positioning location of the object to be located. The preset threshold may be manually set based on actual needs or determined based on actual testing conditions.

[0080] In one embodiment, for multiple candidate locations, the visibility probability value corresponding to each candidate location can be determined as the weight of the candidate location, thereby weighting and summing the multiple candidate locations according to their respective weights to obtain the satellite positioning location of the object to be located. In other embodiments, only the candidate locations whose corresponding visibility probability values ​​exceed a preset threshold can be weighted and summed. The preset threshold can be manually set according to actual needs or determined based on actual testing conditions. The above-mentioned preset thresholds can be the same or different.

[0081] It should be understood that all examples in this embodiment are only used to understand this solution, and the specific settings need to be flexibly determined based on actual conditions.

[0082] In the above-mentioned method for determining the visibility probability, in the presence of an obstruction that affects the satellite's positioning of the object to be positioned, error modeling data is obtained by shrinking and expanding, and based on the error modeling data, the shrinkage boundary determined by shrinking and the expansion boundary determined by expanding are determined, and the shrinkage boundary and the expansion boundary are used to construct the error space range of the obstruction, so that the error space range can more completely and precisely describe the actual obstruction area of ​​the obstruction, thereby determining the spatial position relationship between the straight-line signal propagation path and the error space range, and considering different spatial position relationships to determine the satellite's visibility probability value for the candidate position. Since the visibility probability value is not a traditional binary method that directly describes whether the candidate position is visible or invisible, but allows for obstruction data errors in a percentage probability method, the visibility probability value can more flexibly and accurately describe the obstruction relationship of the obstruction to the candidate position. Therefore, on the basis of improving the accuracy of the visibility probability value, positioning the object to be positioned based on the aforementioned visibility probability value can improve the object positioning accuracy.

[0083] The following describes in detail how to determine the spatial position relationship when the error space range includes the top-view error space range and the side-view error space range. In one embodiment, as shown in FIG6 , the error space range includes the top-view error space range and the side-view error space range. Based on this, a candidate position of the object to be located is obtained, and based on the straight-line signal propagation path between the satellite position and the candidate position, the spatial position relationship between the straight-line signal propagation path and the error space range is determined, including:

[0084] Step 602 : determining a top-down spatial position relationship between the straight-line signal propagation path and the top-down error spatial range based on a straight-line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned.

[0085] The "downward-looking spatial position relationship" specifically refers to the spatial position relationship between the downward-looking projection of the straight-line signal propagation path on the downward-looking error space and the downward-looking error space. As previously explained, the downward-looking error space consists of the spatial range between the downward-looking outer boundary and the downward-looking inner boundary. Therefore, the "downward-looking spatial position relationship" specifically includes the spatial position relationship between the downward-looking projection of the straight-line signal propagation path on the downward-looking error space and the downward-looking outer boundary, and the spatial position relationship between the downward-looking projection of the straight-line signal propagation path on the downward-looking error space and the downward-looking inner boundary.

[0086] In a specific embodiment, based on the straight-line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned, the overhead spatial position relationship between the straight-line signal propagation path and the overhead error space range is determined, including: projecting the straight-line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned on the overhead error space range to obtain the overhead projection of the straight-line signal propagation path on the overhead error space range; and determining the overhead spatial position relationship between the overhead projection and the overhead error space range.

[0087] That is, the server first projects the straight signal propagation path between the satellite position of the satellite and the candidate position of the object to be located on the overlooking error space range, that is, the overlooking projection of the straight signal propagation path on the overlooking error space range can be obtained, thereby determining the overlooking spatial position relationship between the overlooking projection and the overlooking error space range. For ease of understanding, as shown in Figure 7, the straight signal propagation path between the satellite position 701 of the satellite and the candidate position 702 of the object to be located is projected on the overlooking error space range to obtain the overlooking projection 703. The overlooking error space range is specifically composed of the spatial range between the overlooking outer expansion boundary 704 and the overlooking inner contraction boundary 705, and the overlooking error space range includes the overlooking outer contour 706. As can be seen from Figure 7, the overhead projection 703 can have a spatial position relationship with the overhead expansion boundary 704 and the overhead retraction boundary 705 in the overhead error space range, that is, the overhead spatial position relationship includes: the spatial position relationship between the overhead projection 703 and the overhead expansion boundary 704, and the spatial position relationship between the overhead projection 703 and the overhead retraction boundary 705.

[0088] Step 604 : determining a side view spatial position relationship between the straight line signal propagation path and the side view error spatial range based on the straight line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned.

[0089] The side view spatial position relationship specifically refers to the spatial position relationship between the side view projection of the straight signal propagation path on the side view error space and the side view error space. As previously explained, the side view error space consists of the spatial range between the side view outer boundary and the side view inner boundary. Therefore, the side view spatial position relationship specifically includes the spatial position relationship between the side view projection of the straight signal propagation path on the side view error space and the side view outer boundary, and the spatial position relationship between the side view projection of the straight signal propagation path on the side view error space and the side view inner boundary.

[0090] In a specific embodiment, based on the straight line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned, the side view spatial position relationship between the straight line signal propagation path and the side view error space range is determined, including: projecting the straight line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned on the side view error space range to obtain the side view projection of the straight line signal propagation path on the side view error space range; and determining the side view spatial position relationship between the side view projection and the side view error space range.

[0091] That is, the server first projects the straight-line signal propagation path between the satellite position of the satellite and the candidate position of the object to be located onto the side view error space range, thereby obtaining the side view projection of the straight-line signal propagation path onto the side view error space range, and then determines the side view spatial position relationship between the side view projection and the side view error space range. For ease of understanding, as shown in Figure 8, the straight-line signal propagation path between the satellite position 801 of the satellite and the candidate position 802 of the object to be located is projected onto the side view error space range to obtain a side view projection 803. The side view error space range is specifically composed of the spatial range between the side view outward expansion boundary 804 and the side view inward contraction boundary 805, and the side view error space range includes a side view outer contour 806. It can be seen from Figure 7 that there can be a spatial position relationship between the side view projection 803 and the side view outward expansion boundary 804 and the side view inward contraction boundary 805 in the side view error space range, that is, the side view spatial position relationship includes: the spatial position relationship between the side view projection 803 and the side view outward expansion boundary 804, and the spatial position relationship between the side view projection 803 and the side view inward contraction boundary 805.

[0092] And, determining a satellite visibility probability value for the candidate location based on the spatial position relationship, including:

[0093] Step 606: Determine the satellite visibility probability value for the candidate position based on the downward-looking spatial position relationship and the side-looking spatial position relationship.

[0094] Specifically, since the spatial position relationship includes the top-view spatial position relationship and the side-view spatial position relationship, the server determines the satellite's visibility probability value for the candidate location based on the top-view spatial position relationship and the side-view spatial position relationship. It should be understood that all examples in this embodiment are only for understanding this solution, and the specific settings need to be flexibly determined based on actual conditions.

[0095] In this embodiment, the situation where the error space range includes the overhead error space range and the side error space range is specifically considered. The overhead projection of the straight line signal propagation path on the overhead error space range and the side projection of the straight line signal propagation path on the side error space range are used to more accurately determine the spatial position relationship between the straight line signal propagation path and the error space range. That is, the visible probability value can be determined from two dimensions of the overhead spatial position relationship and the side spatial position relationship, further improving the accuracy of the determination of the visible probability value, thereby improving the accuracy of object positioning based on the visible probability value.

[0096] As can be seen from the above embodiments, since the spatial position relationship includes the overhead spatial position relationship and the side view spatial position relationship, the following will detail how to determine the satellite visibility probability value for the candidate position based on the overhead spatial position relationship and the side view spatial position relationship in the spatial position relationship:

[0097] In one embodiment, as shown in FIG9 , determining the satellite visibility probability value for the candidate position based on the spatial position relationship includes:

[0098] Step 902: When the top view projection intersects with the top view outer expansion boundary and does not intersect with the top view inner contraction boundary, and the side view projection intersects with the side view outer expansion boundary and does not intersect with the side view inner contraction boundary, obtain the top view visibility probability value through the top view projection and obtain the side view visibility probability value through the side view projection.

[0099] Among them, the overhead visibility probability value represents the probability that the candidate position is visible under the satellite for the overhead error space range. Similarly, the side view visibility probability value represents the probability that the candidate position is visible under the satellite for the side view error space range. Specifically, when the overhead projection intersects with the overhead expansion boundary and does not intersect with the overhead contraction boundary, it means that the overhead projection is specifically within the spatial range between the overhead contraction boundary and the overhead expansion boundary. For ease of understanding, please refer to Figure 7 again. The overhead projection 703 shown in Figure 7 intersects with the overhead expansion boundary 704, and the overhead projection 703 does not intersect with the overhead contraction boundary 705, that is, the overhead projection 703 is within the spatial range between the overhead expansion boundary 704 and the overhead contraction boundary 705. Therefore, the server obtains the overhead visibility probability value through the overhead projection.

[0100] In a specific embodiment, the range of the overlooking error space includes the overlooking outer contour of the occluder. Based on this, the overlooking visibility probability value is obtained through the overlooking projection, including: determining the overlooking vertex closest to the overlooking projection from the overlooking outer contour, and determining the overlooking indentation vertex corresponding to the overlooking vertex and the overlooking outward expansion vertex corresponding to the overlooking vertex from the overlooking indentation boundary; determining the overlooking vertical distance between the overlooking projection and the overlooking indentation vertex, and the overlooking vertex distance between the overlooking indentation vertex and the overlooking outward expansion vertex; the overlooking vertical distance represents the distance that the overlooking projection is blocked in the range of the overlooking error space, and the overlooking vertex distance represents the maximum blocking distance of the overlooking projection in the range of the overlooking error space; the overlooking visibility probability value is obtained by calculating the overlooking vertical distance and the overlooking vertex distance, and the ratio between the overlooking vertical distance and the overlooking vertex distance is negatively correlated with the overlooking visibility probability value.

[0101] Among them, the top-down outer contour is composed of a plurality of top-down outer contour vertices, and the top-down vertex is the top-down outer contour vertex closest to the top projection among the plurality of top-down outer contour vertices. Based on this, since the top-down retraction boundary is constructed according to the space occupancy parameters for the top view, the height after retraction, and the vertex coordinates after retraction, the top-down retraction boundary is composed of a plurality of top-down retraction vertices, and each top-down retraction vertex is obtained based on the top-down outer contour vertex after retraction, that is, each top-down outer contour vertex has a corresponding top-down retraction vertex. Similarly, since the top-down expansion boundary is constructed according to the space occupancy parameters for the top view, the height after expansion, and the vertex coordinates after expansion, the top-down expansion boundary is composed of a plurality of top-down expansion vertices, and each top-down expansion vertex is obtained based on the top-down outer contour vertex after expansion, that is, each top-down outer contour vertex has a corresponding top-down expansion vertex.

[0102] For ease of understanding, as shown in Figure 10, the top-view error space range includes the top-view outer contour 1001 of the obstruction, and the top-view error space range is the spatial range between the top-view indentation boundary 1002 and the top-view outdentation boundary 1003. Based on this, the top-view outer contour 1001 is composed of the top-view outer contour vertex A1, the top-view outer contour vertex B1, the top-view outer contour vertex C1, and the top-view outer contour vertex D1, the top-view indentation boundary 1002 is composed of the top-view indentation vertex A2, the top-view indentation vertex B2, the top-view indentation vertex C2, and the top-view indentation vertex D2, and the top-view outdentation boundary 1002 is composed of the top-view outdentation vertex A3, the top-view outdentation vertex B3, the top-view outdentation vertex C3, and the top-view outdentation vertex D3. It can be seen from Figure 10 that the top view outer contour vertex A1 corresponds to the top view inward-retracting vertex A2 and the top view outward-expanding vertex A3. Similarly, the top view outer contour vertex B1 corresponds to the top view inward-retracting vertex B2 and the top view outward-expanding vertex B3, the top view outer contour vertex C1 corresponds to the top view inward-retracting vertex C2 and the top view outward-expanding vertex C3, and the top view outer contour vertex D1 corresponds to the top view inward-retracting vertex D2 and the top view outward-expanding vertex D3.

[0103] Based on this, the overlooking vertical distance is the vertical distance between the overlooking projection and the overlooking indented vertex, and the overlooking vertex distance is the vertex distance between the overlooking indented vertex and the overlooking outward-expanding vertex. The overlooking vertical distance represents the distance at which the overlooking projection is blocked within the range of the overlooking error space, and the overlooking vertex distance represents the maximum blocking distance of the overlooking projection within the range of the overlooking error space. For ease of understanding, the examples of Figures 7 and 10 are introduced. As shown in Figure 11, the overlooking projection 1101 is closest to the overlooking outer contour vertex A1, so the overlooking outer contour vertex A1 can be determined as the overlooking vertex, and the overlooking vertex (overlooking outer contour vertex A1) corresponds to the overlooking indented vertex A2 and the overlooking outward-expanding vertex A3. At this time, the vertical distance between the overlooking indented vertex A2 and the overlooking projection 1101 is first calculated to obtain the overlooking vertical distance 1102, and then a straight line is drawn between the overlooking indented vertex A2 and the overlooking outward-expanding vertex A3 to obtain the overlooking vertex distance.

[0104] Furthermore, the overlooking visibility probability value is calculated by the overlooking vertical distance and the overlooking vertex distance, and the ratio between the overlooking vertical distance and the overlooking vertex distance is negatively correlated with the overlooking visibility probability value. The specific calculation method is shown in the example of formula (1):

[0105] Among them, P1 is the probability value of overlooking visibility, d1 is the overlooking vertical distance, and m is the overlooking vertex distance.

[0106] Furthermore, when the side view projection intersects the side view outward expansion boundary but does not intersect the side view inward contraction boundary, it indicates that the side view projection is specifically within the spatial range between the side view inward contraction boundary and the side view outward expansion boundary. For ease of understanding, please refer again to Figure 8 . In Figure 8 , side view projection 803 intersects side view outward expansion boundary 804 and does not intersect side view inward contraction boundary 805, meaning that side view projection 803 is within the spatial range between side view outward expansion boundary 804 and side view inward contraction boundary 805. Therefore, the server obtains the side view visibility probability value based on the side view projection.

[0107] In a specific embodiment, the side view error space range includes the side view outer contour of the occluder. Based on this, the side view visibility probability value is obtained through the side view projection, including: determining the side view vertex closest to the side view projection from the side view outer contour, and determining the side view indentation vertex corresponding to the side view vertex and the side view expansion vertex corresponding to the side view vertex from the side view indentation boundary; determining the side view vertical distance between the side view projection and the side view indentation vertex, and the side view vertex distance between the side view indentation vertex and the side view expansion vertex; the side view vertical distance represents the distance that the side view projection is blocked in the side view error space range, and the side view vertex distance represents the maximum blocking distance of the side view projection in the side view error space range; the side view visibility probability value is calculated by the side view vertical distance and the side view vertex distance, and the ratio between the side view vertical distance and the side view vertex distance is negatively correlated with the side view visibility probability value.

[0108] Among them, the side view outer contour is composed of multiple side view outer contour vertices, and the side view vertex is the side view outer contour vertex closest to the side view projection among the multiple side view outer contour vertices. Based on this, since the side view retraction boundary is constructed according to the space occupancy parameters for the side view, the height after retraction, and the vertex coordinates after retraction, the side view retraction boundary is composed of multiple side view retraction vertices, and each side view retraction vertex is obtained based on the side view outer contour vertex after retraction, that is, each side view outer contour vertex has a corresponding side view retraction vertex. Similarly, since the side view expansion boundary is constructed according to the space occupancy parameters for the side view, the height after expansion, and the vertex coordinates after expansion, the side view expansion boundary is composed of multiple side view expansion vertices, and each side view expansion vertex is obtained based on the side view outer contour vertex after expansion, that is, each side view outer contour vertex has a corresponding side view expansion vertex.

[0109] For ease of understanding, as shown in FIG12 , the side view error space range includes the side view outer contour 1201 of the occluder, and the side view error space range is the spatial range between the side view indentation boundary 1202 and the side view outdentation boundary 1203. Based on this, the side view outer contour 1201 is composed of the side view outer contour vertex E1, the side view outer contour vertex F1, the side view outer contour vertex G1, and the side view outer contour vertex H1, the side view indentation boundary 1202 is composed of the side view indentation vertex E2, the side view indentation vertex F2, the side view indentation vertex G2, and the side view indentation vertex H2, and the side view outdentation boundary 1203 is composed of the side view outdentation vertex E3, the side view outdentation vertex F3, the side view outdentation vertex G3, and the side view outdentation vertex H3. It can be seen from Figure 12 that the side view external contour vertex E1 corresponds to the side view inward-retracted vertex E2 and the side view outward-expanding vertex E3. Similarly, it can be seen that the side view external contour vertex F1 corresponds to the side view inward-retracted vertex F2 and the side view outward-expanding vertex F3, the side view external contour vertex G1 corresponds to the side view inward-retracted vertex G2 and the side view outward-expanding vertex G3, and the side view external contour vertex H1 corresponds to the side view inward-retracted vertex H2 and the side view outward-expanding vertex H3.

[0110] Based on this, the side view vertical distance is the vertical distance between the side view projection and the side view indentation vertex, and the side view vertex distance is the vertex distance between the side view indentation vertex and the side view outdentation vertex. The side view vertical distance represents the distance that the side view projection is blocked in the side view error space range, and the side view vertex distance represents the maximum blocking distance of the side view projection in the side view error space range. For ease of understanding, the examples of Figures 8 and 12 are introduced. As shown in Figure 13, the side view projection 1301 is closest to the side view outer contour vertex E1, so the side view outer contour vertex E1 can be determined as the side view vertex, and the side view vertex (side view outer contour vertex E1) corresponds to the side view indentation vertex E2 and the side view outdentation vertex E3. At this time, the vertical distance between the side view indentation vertex E2 and the side view projection 1301 is first calculated to obtain the side view vertical distance 1302, and then a straight line is drawn between the side view indentation vertex E2 and the side view outdentation vertex E3 to obtain the side view vertex distance.

[0111] Furthermore, the side view visibility probability value is calculated by the side view vertical distance and the side view vertex distance, and the ratio between the side view vertical distance and the side view vertex distance is negatively correlated with the side view visibility probability value. The specific calculation method is shown in formula (2):

[0112] Among them, P2 is the side view visibility probability value, d2 is the side view vertical distance, and n is the side view vertex distance.

[0113] Step 904 : Multiply the top-view visibility probability value and the side-view visibility probability value to obtain the satellite visibility probability value for the candidate position.

[0114] Specifically, the server multiplies the top view visibility probability value and the side view visibility probability value to obtain the satellite visibility probability value for the candidate location. That is, the server multiplies the top view visibility probability value and the side view visibility probability value to obtain the satellite visibility probability value for the candidate location. The specific calculation method is as shown in formula (3): p(LOS|BB)=P1·P2;(3)

[0115] Among them, p(LOS|BB) is the visibility probability value, P1 is the visibility probability value of the top view, and P2 is the visibility probability value of the side view.

[0116] It should be understood that all examples in this embodiment are only used to understand this solution, and the specific settings need to be flexibly determined based on actual conditions.

[0117] In this embodiment, the case where the projection of the straight-line signal propagation path intersects with the outward expansion boundary but does not intersect with the inward contraction boundary is considered, indicating that there is indeed an obstruction between the satellite and the object to be positioned that blocks the signal transmission. At this time, the distance at which the projection of the straight-line signal propagation path is blocked in the fuzzy area and the maximum blocking distance of the projection in the overhead error space are considered to obtain the visible proportion of the projection of the straight-line signal propagation path in the fuzzy area. Since the proportion is negatively correlated with the visible probability value, that is, the smaller the distance at which the projection is blocked in the fuzzy area, the more visible areas the projection is in the fuzzy area, the visible probability value of the candidate position is determined by the two-dimensional visible probability value of the overhead visible probability value and the side visible probability value, thereby further improving the accuracy of determining the visible probability value, thereby improving the accuracy of object positioning based on the visible probability value.

[0118] In one embodiment, as shown in FIG14 , determining a satellite visibility probability value for a candidate position based on a spatial position relationship includes:

[0119] Step 1402 : When the top view projection does not intersect with the top view outer boundary, and the side view projection does not intersect with the side view outer boundary, the maximum visibility probability value is determined as the satellite visibility probability value for the candidate position.

[0120] Among them, the maximum visible probability value represents the visible probability value when the obstruction does not block the straight-line signal propagation path, and the maximum visible probability value is a value close to 1. However, considering that there may be other obstructions or positioning influencing factors in actual applications, the maximum visible probability value in this embodiment is 0.9.

[0121] Specifically, when the top-view projection does not intersect the top-view outward boundary, it indicates that the top-view projection of the straight signal propagation path within the top-view error space does not intersect the top-view error space. This indicates that the occluder pair within the top-view error space does not have an obstruction effect on the straight signal propagation path. For ease of understanding, as shown in Figure 15, the top-view projection 1501 of the straight signal propagation path within the top-view error space does not intersect the top-view outward boundary 1502 of the top-view error space. Similarly, when the side-view projection does not intersect the side-view outward boundary, it indicates that the side-view projection of the straight signal propagation path within the side-view error space does not intersect the side-view error space. This indicates that the occluder pair within the side-view error space does not have an obstruction effect on the straight signal propagation path. The specific example is similar to Figure 15 and is not repeated here. Therefore, the server now determines the maximum visibility probability value as the satellite's visibility probability value for the candidate location. If the maximum visibility probability value in this embodiment is 0.9, then the satellite's visibility probability value for the candidate location is 0.9.

[0122] Step 1404 : When the top view projection intersects the top view indentation boundary and the side view projection intersects the side view indentation boundary, the minimum visibility probability value is determined as the satellite visibility probability value for the candidate position.

[0123] Among them, the minimum visible probability value represents the visible probability value when the obstruction blocks the straight signal propagation path and the impact is the greatest, and the minimum visible probability value is a value close to 0. However, considering that there may be other positioning influencing factors in actual applications, the minimum visible probability value in this embodiment is 0.1.

[0124] Specifically, when the top-view projection intersects the top-view indentation boundary, it indicates that the top-view projection of the straight-line signal propagation path on the top-view error space intersects the top-view error space, and the intersection with the top-view indentation boundary indicates that the obstruction caused by the obstruction within the top-view error space is significant. For ease of understanding, as shown in FIG16 , the top-view projection 1601 of the straight-line signal propagation path on the top-view error space intersects the top-view indentation boundary 1602 of the top-view error space. Similarly, when the side-view projection intersects the side-view indentation boundary, it indicates that the side-view projection of the straight-line signal propagation path on the side-view error space intersects the side-view error space, and the intersection with the side-view indentation boundary indicates that the obstruction caused by the obstruction within the side-view error space is significant. The specific example is similar to FIG16 and is not repeated here. Therefore, the server now determines the minimum visibility probability value as the satellite's visibility probability value for the candidate position. For example, in this embodiment, the minimum visibility probability value is 0.1, and the visibility probability value of the satellite for the candidate position is 0.1.

[0125] It should be understood that all examples in this embodiment are only used to understand this solution, and the specific settings need to be flexibly determined based on actual conditions.

[0126] In this embodiment, the case where the projection of the straight signal propagation path does not intersect with the outward expansion boundary is considered, which means that the obstruction does not block the straight signal propagation path, so the maximum visibility probability value is determined as the satellite's visibility probability value for the candidate position. Secondly, considering the case where the projection of the straight signal propagation path intersects with the inward contraction boundary, it means that the obstruction caused by the obstruction in the fuzzy area on the straight signal propagation path has a greater impact, so the minimum visibility probability value is determined as the satellite's visibility probability value for the candidate position. Based on this, the determined visibility probability value takes into account a variety of actual situations, thereby improving the reliability and flexibility of the determined visibility probability value.

[0127] In one embodiment, as shown in FIG17 , when there are multiple obstructions, and the obstructions have different heights, determining the satellite visibility probability value for the candidate location based on the spatial position relationship includes:

[0128] Step 1702 : From the candidate visibility probability values ​​of the plurality of obstructions, the candidate visibility probability value with the smallest value is selected as the visibility probability value of the satellite for the candidate position.

[0129] Specifically, the server determines the top-view spatial position relationship between the linear signal propagation path and the top-view error spatial range of each obstruction, and the side-view spatial position relationship between the linear signal propagation path and the top-view error spatial range of each obstruction, similar to the aforementioned embodiment. Based on this, the server then determines the candidate visibility probability value of the satellite for each candidate position under each obstruction using the top-view spatial position relationship and the side-view spatial position relationship for each obstruction, similar to the aforementioned embodiment.

[0130] For example, there are occluders I1, I2, I3 and I4, so it is necessary to determine the overhead spatial position relationship between the straight-line signal propagation path and the overhead error spatial range of occluders I1, I2, I3 and I4, and to determine the side spatial position relationship between the straight-line signal propagation path and the side error spatial range of occluders I1, I2, I3 and I4, thereby determining the candidate visibility probability value of the satellite for each candidate position under occluders I1, I2, I3 and I4 through the overhead spatial position relationship and side spatial position relationship of occluders I1, I2, I3 and I4. For example, the candidate visibility probability value of each satellite for the candidate position under the occlusion I1 is 0.9, the candidate visibility probability value of each satellite for the candidate position under the occlusion I2 is 0.4, the candidate visibility probability value of each satellite for the candidate position under the occlusion I3 is 0.6, and the candidate visibility probability value of each satellite for the candidate position under the occlusion I4 is 0.1.

[0131] Step 1704 : From the candidate visibility probability values ​​of the plurality of obstructions, the candidate visibility probability value with the smallest value is taken as the visibility probability value of the satellite for the candidate position.

[0132] Specifically, the server selects the smallest candidate visibility probability value from each obstruction's respective candidate visibility probability values ​​and determines it as the satellite's visibility probability value for the candidate location. As previously explained, a larger visibility probability value indicates a smaller impact of the obstruction on positioning. Therefore, to maximize object positioning accuracy, selecting the visibility probability value with the greatest impact allows for the worst-case obstruction scenario. Therefore, the smallest candidate visibility probability value is determined as the satellite's visibility probability value for the candidate location. For ease of understanding, as can be seen from the above example, the candidate visibility probability value of the satellite for the candidate position under the occlusion I1 is 0.9, the candidate visibility probability value of the satellite for the candidate position under the occlusion I2 is 0.4, the candidate visibility probability value of the satellite for the candidate position under the occlusion I3 is 0.6, and the candidate visibility probability value of the satellite for the candidate position under the occlusion I4 is 0.1. The smallest value among the above candidate visibility probability values ​​is 0.1, that is, the candidate visibility probability value of the satellite for the candidate position under the occlusion I4 is the smallest. At this time, the candidate visibility probability value of the satellite for the candidate position under the occlusion I4 is determined as the visibility probability value of the satellite for the candidate position.

[0133] It should be understood that all examples in this embodiment are only used to understand this solution, and the specific settings need to be flexibly determined based on actual conditions.

[0134] In this embodiment, since the larger the visibility probability value, the smaller the impact of the obstruction on positioning, in order to maximize the accuracy of object positioning, selecting the visibility probability value that has the greatest impact on positioning for positioning can take into account the worst obstruction situation. Therefore, the candidate visibility probability value with the smallest value is determined as the satellite's visibility probability value for the candidate position to ensure the reliability of subsequent object positioning.

[0135] Based on the detailed introduction of the aforementioned embodiment, the complete process of the method for determining the visual probability in the embodiment of the present application will be described below. In one embodiment, as shown in FIG18 , a method for determining the visual probability is provided. The method is described by taking the server 104 in FIG1 as an example. It is understandable that the method can also be applied to a system including a terminal 102 and a server 104 and implemented through the interaction between the terminal 102 and the server 104. In this embodiment, the method includes the following steps:

[0136] Step 1801 : Determine the occluder of the object to be located, and based on the space occupancy parameter of the occluder, shrink and expand the outer contour of the occluder represented by the space occupancy parameter to obtain error modeling data.

[0137] Step 1802 : Based on the error modeling data, determine the shrinking boundary determined by shrinking and the expanding boundary determined by expanding, and construct the error space range of the occluder using the shrinking boundary and the expanding boundary.

[0138] Step 1803: Project the straight-line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned on the overlooking error space range to obtain the overlooking projection of the straight-line signal propagation path on the overlooking error space range; and determine the overlooking spatial position relationship between the overlooking projection and the overlooking error space range.

[0139] Step 1804: Project the straight-line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned onto the side-view error space range to obtain a side-view projection of the straight-line signal propagation path onto the side-view error space range; and determine the side-view spatial position relationship between the side-view projection and the side-view error space range.

[0140] Step 1805: When the top view projection intersects with the top view outward expansion boundary and does not intersect with the top view inward contraction boundary, and the side view projection intersects with the side view outward expansion boundary and does not intersect with the side view inward contraction boundary, obtain the top view visibility probability value through the top view projection and obtain the side view visibility probability value through the side view projection.

[0141] Step 1806 , multiplying the top view visibility probability value and the side view visibility probability value to obtain the satellite visibility probability value for the candidate position.

[0142] Step 1807 : When the top view projection does not intersect with the top view outer boundary, and the side view projection does not intersect with the side view outer boundary, the maximum visibility probability value is determined as the satellite visibility probability value for the candidate position.

[0143] Step 1808 : When the top view projection intersects the top view indentation boundary and the side view projection intersects the side view indentation boundary, the minimum visibility probability value is determined as the satellite visibility probability value for the candidate position.

[0144] It should be understood that the specific implementation of steps 1801 to 1818 are similar to those in the aforementioned embodiment and will not be repeated here.

[0145] It should be understood that, although the steps in the flowcharts involved in the above-mentioned embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the above-mentioned embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0146] Based on the same inventive concept, embodiments of the present application also provide a visual probability determination device for implementing the visual probability determination method described above. The implementation solution provided by this device is similar to the implementation solution described in the above method. Therefore, the specific limitations of one or more visual probability determination device embodiments provided below can be found in the limitations of the visual probability determination method described above and will not be repeated here.

[0147] In one embodiment, as shown in FIG19 , a device for determining a visibility probability is provided, comprising: a modeling module 1902 , an error space range building module 1904 , a spatial position relationship determining module 1906 , and a visibility probability value determining module 1908 , wherein:

[0148] Modeling module 1902 is used to determine the occluders of the object to be located, and based on the space occupancy parameters of the occluders, shrink and expand the outer contour of the occluders represented by the space occupancy parameters to obtain error modeling data;

[0149] The error space range construction module 1904 is configured to determine, based on the error modeling data, an inner contraction boundary determined by inner contraction and an outer expansion boundary determined by outer expansion, and construct the error space range of the occluder using the inner contraction boundary and the outer expansion boundary;

[0150] The spatial position relationship determination module 1906 is configured to obtain a candidate position of the object to be located and determine a spatial position relationship between the straight-line signal propagation path and the error space range based on a straight-line signal propagation path between the satellite position and the candidate position.

[0151] The visibility probability value determination module 1908 is used to determine the visibility probability value of the satellite for the candidate position based on the spatial position relationship. The visibility probability value is used to determine the satellite positioning position of the object to be positioned in combination with the candidate position.

[0152] In one embodiment, the error space range includes a top-view error space range and a side-view error space range;

[0153] The spatial position relationship determination module 1906 is specifically configured to determine a downward-looking spatial position relationship between the straight-line signal propagation path and the downward-looking error spatial range based on the straight-line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned; and to determine a side-looking spatial position relationship between the straight-line signal propagation path and the side-looking error spatial range based on the straight-line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned;

[0154] The visibility probability value determination module 1908 is specifically configured to determine the visibility probability value of the satellite for the candidate position according to the downward-looking spatial position relationship and the side-looking spatial position relationship.

[0155] In one embodiment, the spatial position relationship determination module 1906 is specifically used to project the straight-line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned on the overhead error space range to obtain the overhead projection of the straight-line signal propagation path on the overhead error space range; determine the overhead spatial position relationship between the overhead projection and the overhead error space range; project the straight-line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned on the side view error space range to obtain the side view projection of the straight-line signal propagation path on the side view error space range; and determine the side view spatial position relationship between the side view projection and the side view error space range.

[0156] In one embodiment, the error space range includes a top-view error space range and a side-view error space range; the top-view error space range is composed of a space range between a top-view outward expansion boundary and a top-view inward contraction boundary; the side-view error space range is composed of a space range between a side-view outward expansion boundary and a side-view inward contraction boundary;

[0157] The spatial position relationship includes a top-view spatial position relationship and a side-view spatial position relationship; the top-view spatial position relationship includes at least: the spatial position relationship between the top-view projection of the straight line signal propagation path on the top-view error space range and the top-view outer expansion boundary, and the spatial position relationship between the top-view projection and the top-view inner contraction boundary; the side-view spatial position relationship includes at least: the spatial position relationship between the side-view projection of the straight line signal propagation path on the side-view error space range and the side-view outer expansion boundary, and the spatial position relationship between the side-view projection and the side-view inner contraction boundary.

[0158] In one embodiment, the visibility probability value determination module 1908 is specifically configured to obtain a top-view visibility probability value through a top-view projection and a side-view visibility probability value through a side-view projection when the top-view projection intersects with the top-view outward expansion boundary and does not intersect with the top-view inward contraction boundary, and when the side-view projection intersects with the side-view outward expansion boundary and does not intersect with the side-view inward contraction boundary; and to multiply the top-view visibility probability value and the side-view visibility probability value to obtain a satellite visibility probability value for the candidate position.

[0159] In one embodiment, the top-view error space range includes the top-view outer contour of the occluder;

[0160] The visible probability value determination module 1908 is specifically used to determine the overlooking vertex closest to the overlooking projection from the overlooking outer contour, and determine the overlooking indentation vertex corresponding to the overlooking vertex and the overlooking outward expansion vertex corresponding to the overlooking vertex from the overlooking indentation boundary; determine the overlooking vertical distance between the overlooking projection and the overlooking indentation vertex, and the overlooking vertex distance between the overlooking indentation vertex and the overlooking outward expansion vertex; the overlooking vertical distance represents the distance at which the overlooking projection is blocked in the overlooking error space range, and the overlooking vertex distance represents the maximum blocking distance of the overlooking projection in the overlooking error space range; the overlooking visible probability value is obtained by calculating the overlooking vertical distance and the overlooking vertex distance, and the ratio between the overlooking vertical distance and the overlooking vertex distance is negatively correlated with the overlooking visible probability value.

[0161] In one embodiment, the side view error space range includes the side view outer contour of the occluder;

[0162] The visible probability value determination module 1908 is specifically used to determine the side view vertex closest to the side view projection from the side view external contour, and determine the side view indentation vertex corresponding to the side view vertex, and the side view expansion vertex corresponding to the side view vertex from the side view indentation boundary; determine the side view vertical distance between the side view projection and the side view indentation vertex, and the side view vertex distance between the side view indentation vertex and the side view expansion vertex; the side view vertical distance represents the distance at which the side view projection is blocked in the side view error space range, and the side view vertex distance represents the maximum blocking distance of the side view projection in the side view error space range; the side view visible probability value is obtained by calculating the side view vertical distance and the side view vertex distance, and the ratio between the side view vertical distance and the side view vertex distance is negatively correlated with the side view visible probability value.

[0163] In one embodiment, the visibility probability value determination module 1908 is specifically configured to determine the maximum visibility probability value as the satellite visibility probability value for the candidate position when the top view projection does not intersect the top view outward boundary and the side view projection does not intersect the side view outward boundary.

[0164] In one embodiment, the visibility probability value determining module 1908 is specifically configured to determine the minimum visibility probability value as the satellite visibility probability value for the candidate position when the top view projection intersects the top view indentation boundary and the side view projection intersects the side view indentation boundary.

[0165] In one embodiment, the space occupancy parameter includes height and vertex coordinates; the error modeling data includes the height after shrinking and expanding, and the vertex coordinates after shrinking and expanding;

[0166] Modeling module 1902 is specifically used to construct the outward expansion boundary of the occupant according to the space occupancy parameters, the outward expansion height and the outward expansion vertex coordinates in the error modeling data; to construct the inward contraction boundary of the occupant according to the space occupancy parameters, the inward contraction height and the inward contraction vertex coordinates in the error modeling data; and to determine the spatial range between the outward expansion boundary and the inward contraction boundary as the error spatial range including the outer contour of the occupant.

[0167] In one embodiment, there are multiple obstructions;

[0168] The visibility probability value determination module 1908 is specifically used to determine the candidate visibility probability value of the satellite for each candidate position under each obstruction based on the spatial position relationship; from the candidate visibility probability values ​​of each obstruction, the candidate visibility probability value with the smallest value is taken as the visibility probability value of the satellite for the candidate position.

[0169] In one embodiment, a computer device is provided. The computer device can be either a server or a terminal. In this embodiment, a server is used as an example. Its internal structure diagram can be shown in FIG20 . The computer device includes a processor, a memory, an input / output (I / O) interface, and a communication interface. The processor, the memory, and the I / O interface are connected via a system bus, and the communication interface is connected to the system bus via the I / O interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store data related to the embodiments of the present application, such as spatial occupancy parameters of obstructions and error modeling data. The I / O interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via a network connection. When executed by the processor, the computer program implements a method for determining visibility probability.

[0170] Those skilled in the art will understand that the structure shown in Figure 20 is merely a block diagram of a portion of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0171] In one embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0172] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0173] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0174] It should be noted that the object information (including but not limited to object device information, object personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the object or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0175] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0176] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0177] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for determining a visibility probability value for satellite positioning, performed by a computer device, the method comprising: Determine an obstruction of the object to be located, and based on a space occupancy parameter of the obstruction, shrink and expand an outer contour of the obstruction represented by the space occupancy parameter to obtain error modeling data; Determining, based on the error modeling data, a shrinking boundary determined by the shrinking and an expanding boundary determined by the expanding, and constructing an error space range of the obstruction using the shrinking boundary and the expanding boundary; Obtaining a candidate position of the object to be positioned, and determining a spatial positional relationship between the straight-line signal propagation path and the error space range based on a straight-line signal propagation path between the satellite position of the satellite and the candidate position; and According to the spatial position relationship, a visibility probability value of the satellite for the candidate position is determined, and the visibility probability value is used to determine the satellite positioning position of the object to be positioned in combination with the candidate position.

2. The method according to claim 1, wherein the error space range includes a top-view error space range and a side-view error space range; The acquiring of the candidate position of the object to be positioned, and determining, based on a straight-line signal propagation path between the satellite position of the satellite and the candidate position, a spatial position relationship between the straight-line signal propagation path and the error space range, includes: determining, based on a straight-line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned, a look-down spatial position relationship between the straight-line signal propagation path and the look-down error spatial range; determining a side view spatial position relationship between the straight line signal propagation path and the side view error spatial range based on a straight line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned; Determining the visibility probability value of the satellite for the candidate position according to the spatial position relationship includes: A visibility probability value of the satellite for the candidate position is determined according to the downward-looking spatial position relationship and the side-looking spatial position relationship.

3. The method according to claim 2, wherein determining the overlooking spatial position relationship between the straight-line signal propagation path and the overlooking error spatial range based on the straight-line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned comprises: Projecting a straight-line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned on the range of the overlooking error space to obtain a overlooking projection of the straight-line signal propagation path on the range of the overlooking error space; Determining a top-view spatial positional relationship between the top-view projection and the top-view error spatial range; The determining, based on a straight line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned, a side view spatial position relationship between the straight line signal propagation path and the side view error spatial range comprises: Projecting a straight-line signal propagation path between the satellite position of the satellite and the candidate position of the object to be positioned on the side-view error space range to obtain a side-view projection of the straight-line signal propagation path on the side-view error space range; A side view spatial position relationship between the side view projection and the side view error spatial range is determined.

4. The method according to any one of claims 1 to 3, wherein the error space range includes a top-view error space range and a side-view error space range; the top-view error space range is formed by the space range between the top-view outward expansion boundary and the top-view inward contraction boundary; and the side-view error space range is formed by the space range between the side-view outward expansion boundary and the side-view inward contraction boundary; The spatial position relationship includes a top-view spatial position relationship and a side-view spatial position relationship; The top-view spatial position relationship includes at least: a spatial position relationship between a top-view projection of the straight-line signal propagation path on the top-view error spatial range and the top-view outward expansion boundary, and a spatial position relationship between the top-view projection and the top-view inward contraction boundary; The side view spatial position relationship includes at least: the spatial position relationship between the side view projection of the straight signal propagation path on the side view error space range and the side view outward expansion boundary, and the spatial position relationship between the side view projection and the side view inward contraction boundary.

5. The method according to claim 4, wherein determining the visibility probability value of the satellite for the candidate position based on the spatial position relationship comprises: When the top view projection intersects the top view outward expansion boundary and does not intersect the top view inward contraction boundary, and the side view projection intersects the side view outward expansion boundary and does not intersect the side view inward contraction boundary, obtaining a top view visibility probability value through the top view projection and a side view visibility probability value through the side view projection; The product of the overhead visibility probability value and the side visibility probability value is calculated to obtain a visibility probability value of the satellite for the candidate position.

6. The method according to claim 5, wherein the top-view error space range includes the top-view outer contour of the obstruction; The obtaining of the overhead visibility probability value through the overhead projection includes: Determine a top-down vertex closest to the top-down projection from the top-down outer contour, and determine a top-down retracted vertex corresponding to the top-down vertex and a top-down expanded vertex corresponding to the top-down vertex from the top-down retracted boundary; Determine a top-down vertical distance between the top-down projection and the top-down retracted vertex, and a top-down vertex distance between the top-down retracted vertex and the top-down expanded vertex; the top-down vertical distance represents a distance by which the top-down projection is blocked within the top-down error space, and the top-down vertex distance represents a maximum blocking distance of the top-down projection within the top-down error space; The overlooking visibility probability value is calculated by the overlooking vertical distance and the overlooking vertex distance, and the ratio of the overlooking vertical distance to the overlooking vertex distance is negatively correlated with the overlooking visibility probability value.

7. The method according to claim 5, wherein the side view error space range includes the side view outer contour of the occluder; The obtaining of the side view visibility probability value through the side view projection includes: Determine a side view vertex closest to the side view projection from the side view outer contour, and determine a side view indentation vertex corresponding to the side view vertex and a side view expansion vertex corresponding to the side view vertex from the side view indentation boundary; Determine a side view vertical distance between the side view projection and the side view inward-retracted vertex, and a side view vertex distance between the side view inward-retracted vertex and the side view outward-expanded vertex; the side view vertical distance represents a distance that the side view projection is blocked within the side view error space, and the side view vertex distance represents a maximum blocking distance of the side view projection within the side view error space; The side view visibility probability value is calculated by the side view vertical distance and the side view vertex distance, and the ratio between the side view vertical distance and the side view vertex distance is negatively correlated with the side view visibility probability value.

8. The method according to any one of claims 4 to 7, wherein determining the visibility probability value of the satellite for the candidate position based on the spatial position relationship comprises: When the top-view projection does not intersect the top-view outward boundary, and the side-view projection does not intersect the side-view outward boundary, a maximum visibility probability value is determined as the visibility probability value of the satellite for the candidate position.

9. The method according to any one of claims 4 to 7, wherein determining the visibility probability value of the satellite for the candidate position based on the spatial position relationship comprises: When the top-view projection intersects the top-view indentation boundary and the side-view projection intersects the side-view indentation boundary, a minimum visibility probability value is determined as the visibility probability value of the satellite for the candidate position.

10. The method according to any one of claims 1 to 9, wherein the space occupancy parameters include height and vertex coordinates; the error modeling data includes the height after indentation and expansion, and the vertex coordinates after indentation and expansion; The step of determining, based on the error modeling data, a shrinking boundary determined by the shrinking and an expanding boundary determined by the expanding, and constructing an error space range of the obstruction using the shrinking boundary and the expanding boundary includes: Constructing an outward expansion boundary of the occluder according to the space occupancy parameter and the outward expansion height and outward expansion vertex coordinates in the error modeling data; Constructing a retracted boundary of the obstruction according to the space occupancy parameter and the retracted height and the retracted vertex coordinates in the error modeling data; The spatial range between the outward-expanding boundary and the inward-shrinking boundary is determined as the error spatial range including the outer contour of the obstruction.

11. The method according to claim 1, wherein there are multiple obstructions; Determining the visibility probability value of the satellite for the candidate position according to the spatial position relationship includes: Determining, based on the spatial position relationship, a candidate visibility probability value of the satellite for each candidate position under each of the obstructions; From the candidate visibility probability values of each of the obstructions, the candidate visibility probability value with the smallest value is determined as the visibility probability value of the satellite for the candidate position.

12. A device for determining visual probability, the device comprising: a modeling module for determining an obstruction of the object to be located, and based on a space occupancy parameter of the obstruction, shrinking and expanding an outer contour of the obstruction represented by the space occupancy parameter to obtain error modeling data; an error space range construction module, configured to determine, based on the error modeling data, an inward contraction boundary determined by the inward contraction and an outward expansion boundary determined by the outward expansion, and construct the error space range of the obstruction using the inward contraction boundary and the outward expansion boundary; a spatial position relationship determination module, configured to obtain a candidate position of the object to be positioned, and determine a spatial position relationship between the straight-line signal propagation path and the error space range based on a straight-line signal propagation path between the satellite position of the satellite and the candidate position; The visibility probability value determination module is used to determine the visibility probability value of the satellite for the candidate position according to the spatial position relationship, and the visibility probability value is used to determine the satellite positioning position of the object to be positioned in combination with the candidate position.

13. A computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method according to any one of claims 1 to 11 when executing the computer program.

14. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 11 are implemented.

15. A computer program product comprising a computer program, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 11.

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