Pseudolite layout method, apparatus, device and storage medium

Abstract

Embodiments of the application disclose a pseudolite layout method, device, equipment and storage medium, the method comprises: based on the positioning demand, determining the positioning area and the precision factor index of the target space to be laid out; initializing the pseudolite layout information and the user position for the target space; based on the positioning area, the precision factor index of the positioning area and the user position, calculating the first global precision factor of the pseudolite layout information; the first global precision factor is used as the optimization target to carry out the full-area layout optimization on the pseudolite layout information, and the optimal layout information is obtained. In this way, different precision factor indexes are set according to the positioning requirements of different positioning areas, and the global precision factor is used as the optimization target to search for the optimal layout, which can take into account the precision factor indexes of different positioning areas on the basis of ensuring the global positioning accuracy, so that the pseudolite layout is more in line with the positioning requirements of the actual space.

Description

Technical Field

[0001] This application relates to positioning technology, and more particularly to a pseudo-satellite deployment method, apparatus, device, and storage medium. Background Technology

[0002] A pseudosatellite (PL), also known as a "ground satellite," is a signal transmitter for a Global Navigation Satellite System (GNSS) deployed on the ground. This technology is used to enhance GNSS positioning or achieve independent positioning in environments with weak or absent GNSS signals. Current pseudosatellite deployment technologies typically consider the entire area without taking into account the positioning needs of users in different regions. This results in pseudosatellite deployments failing to meet actual positioning requirements and impacting positioning accuracy. Therefore, optimizing pseudosatellite deployment is a crucial objective of pseudosatellite positioning technology. Summary of the Invention

[0003] To address the aforementioned technical problems, embodiments of this application aim to provide a pseudo-satellite deployment method, apparatus, device, and storage medium.

[0004] The technical solution of this application is implemented as follows:

[0005] Firstly, a pseudo-satellite deployment method is provided, which includes: determining the positioning area and accuracy factor index of the target space to be deployed based on positioning requirements; wherein, the target space includes a first positioning area and a second positioning area, and the accuracy factor indexes of the first positioning area and the second positioning area are different.

[0006] Initialize pseudo-satellite layout information and user location for the target space; wherein, the pseudo-satellite layout information includes the number of pseudo-satellites and their locations;

[0007] Based on the positioning area, the accuracy factor index of the positioning area, and the user location, calculate the first global accuracy factor of the pseudo-satellite layout information;

[0008] The first global accuracy factor is used as the optimization target to optimize the layout information of the pseudo-satellites across the entire region, thereby obtaining the optimal layout information.

[0009] Secondly, a pseudo-satellite deployment device is provided, the device comprising:

[0010] A configuration unit is used to determine the positioning area and accuracy factor index of the target space to be laid out based on positioning requirements; wherein, the target space includes a first positioning area and a second positioning area, and the accuracy factor indexes of the first positioning area and the second positioning area are different.

[0011] An initialization unit is used to initialize pseudo-satellite layout information and user location for the target space; wherein, the pseudo-satellite layout information includes the number of pseudo-satellites and their locations;

[0012] The search unit is used to calculate a first global precision factor of the pseudo-satellite layout information based on the positioning area, the precision factor index of the positioning area, and the user location; and to perform full-area layout optimization of the pseudo-satellite layout information using the first global precision factor as the optimization target to obtain the optimal layout information.

[0013] Thirdly, a pseudo-satellite deployment device is provided, comprising: a processor and a memory configured to store a computer program capable of running on the processor.

[0014] Wherein, the processor is configured to execute the steps of the aforementioned method when running the computer program.

[0015] Fourthly, a computer-readable storage medium is provided having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the aforementioned method.

[0016] This application provides a pseudo-satellite deployment method, apparatus, device, and storage medium. The method includes: determining the positioning area and accuracy factor index of the target space to be deployed based on positioning requirements; wherein the target space includes a first positioning area and a second positioning area, and the accuracy factor indices of the first positioning area and the second positioning area are different; initializing pseudo-satellite deployment information and user location for the target space; wherein the pseudo-satellite deployment information includes the number of pseudo-satellites and the positions of pseudo-satellites; calculating a first global accuracy factor of the pseudo-satellite deployment information based on the positioning area, the accuracy factor index of the positioning area, and the user location; and performing full-area deployment optimization of the pseudo-satellite deployment information using the first global accuracy factor as the optimization target to obtain the optimal deployment information. In this way, different accuracy factor indices are set according to the positioning requirements of different positioning areas, and the global accuracy factor is used as the optimization target when searching for the optimal deployment. This ensures global positioning accuracy while taking into account the accuracy factor indices of different positioning areas, making the pseudo-satellite deployment more consistent with the positioning requirements of actual space. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the first process of the pseudo-satellite deployment method in the embodiments of this application;

[0018] Figure 2 This is a schematic diagram of the first component structure of the target space in an embodiment of this application;

[0019] Figure 3 This is a schematic diagram of the second process of the pseudo-satellite deployment method in the embodiments of this application;

[0020] Figure 4 This is a schematic diagram of the third process of the pseudo-satellite deployment method in the embodiments of this application;

[0021] Figure 5 This is a schematic diagram of the second component structure of the target space in an embodiment of this application;

[0022] Figure 6 This is a schematic diagram of the composition structure of the pseudo-satellite layout device in the embodiments of this application;

[0023] Figure 7 This is a schematic diagram of the composition structure of the pseudo-satellite deployment device in the embodiments of this application. Detailed Implementation

[0024] In order to gain a more detailed understanding of the features and technical content of the embodiments of this application, the implementation of the embodiments of this application will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for reference and illustration only and are not intended to limit the embodiments of this application.

[0025] Figure 1 This is a schematic diagram of the first process of the pseudo-satellite deployment method in the embodiments of this application, as shown below. Figure 1 As shown, the method may specifically include:

[0026] Step 101: Based on positioning requirements, determine the positioning area and accuracy factor of the target space to be deployed;

[0027] The target space includes a first positioning region and a second positioning region, and the accuracy factor indices of the first positioning region and the second positioning region are different.

[0028] The positioning area can be understood as the area in the target space that needs to be positioned by pseudo-satellite. In this embodiment of the application, considering the actual positioning needs, the target space is divided into at least a first positioning area and a second positioning area, and different accuracy factor indicators are set for different positioning needs.

[0029] For example, the Dilution of Precision (DOP) can be one of the following: Geometric Dilution Precision (GDOP), Position Dilution of Precision (PDOP), Horizontal Dilution of Precision (HDOP), Vertical Dilution of Precision (VDOP), or Time Dilution of Precision (TDOP).

[0030] For example, with the accuracy factor denoted as HDOP, the first positioning area must meet the requirement of HDOP < 1.2, and the second positioning area must meet the requirement of HDOP < 1.5. Here, the first positioning area can be considered as the core area, and the second positioning area can be considered as the area with lower positioning accuracy than the first positioning area.

[0031] For example, positioning requirements may include not only accuracy factor indicators for different positioning regions in the target space, but also geometric constraints on the target space. These geometric constraints are used to constrain the placement of pseudosatellites. For example, geometric constraints may include target space dimensions, obstacle locations, etc.

[0032] Step 102: Initialize pseudo-satellite layout information and user location for the target space; wherein, the pseudo-satellite layout information includes the number of pseudo-satellites and their locations;

[0033] For example, pseudo-satellite layout information and user location are initialized based on geometric constraints.

[0034] The number of pseudo-satellites in the pseudo-satellite layout information is initialized to 4, and the positions of the pseudo-satellites are randomly assigned according to geometric constraints.

[0035] Based on geometric constraints, a mathematical model of the actual indoor space is established. The indoor space can have a standard or non-standard geometric shape. A random function following a uniform distribution is used to generate n user locations within the indoor space, representing possible locations the user might reach. In some embodiments, user locations can be generated using other random functions, such as a Gaussian distribution, based on activity frequency.

[0036] Furthermore, a pre-defined optimization search algorithm is employed to optimize the pseudo-satellite layout information across the entire region, using the first global accuracy factor as the optimization objective. For example, the optimization search algorithm can be a particle swarm optimization algorithm, a genetic algorithm, an ant colony algorithm, a traversal method, or the maximum convex polyhedron criterion, among others.

[0037] Step 103: Based on the positioning area, the accuracy factor index of the positioning area, and the user location, calculate the first global accuracy factor of the pseudo-satellite layout information;

[0038] Here, the first global precision factor is the weighted precision factor of the entire region. When calculating the first global precision factor, the positioning focus area can be reflected according to the precision factor index of different positioning areas. The first global precision factor is used as the optimization target for the search. While ensuring the global positioning accuracy, the precision factor index of different positioning areas can be taken into account, making the pseudo-satellite layout more in line with the positioning needs of actual space.

[0039] For example, in some embodiments, calculating the first global precision factor of the pseudo-satellite layout information based on the positioning area, the precision factor index of the positioning area, and the user location includes: determining the target positioning area to which the user location belongs, and the membership degree relative to the target positioning area, based on a preset membership function; wherein the target positioning area is a positioning area in the target space; determining a first weight of the user location based on the target positioning area to which the user location belongs and the membership degree; determining a first precision factor for positioning the user location based on the pseudo-satellite positions in the pseudo-satellite layout information and the user location; and determining the first global precision factor of the pseudo-satellite layout information based on the first weight, the first precision factor, and the precision factor index of all user locations in the target space.

[0040] In other words, the positioning area is divided by combining the accuracy factor index, and the membership degree function is used to calculate the membership degree of each user's location relative to the positioning area. The first weight of the user's location is determined based on the membership degree, and the weighted accuracy factor of the entire area is calculated based on the first weight as the optimization target.

[0041] For example, in some embodiments, determining the target positioning region to which the user's location belongs, and the degree of membership relative to the target positioning region, based on a preset membership function, includes: determining the degree of membership of the user's location in the target space relative to the first positioning region, and the degree of membership relative to the second positioning region, based on a preset membership function; and determining that the target positioning region to which the user's location belongs is the positioning region corresponding to the maximum degree of membership.

[0042] In other words, the membership degree of the user's location and each location area is first calculated based on the membership function. Then, the location area corresponding to the maximum membership degree is selected as the target location area to which the user's location belongs. Accordingly, the maximum membership degree is the membership degree of the user's location relative to the target location area.

[0043] For example, in some embodiments, determining the first weight of the user location based on the target positioning region and membership degree to which the user location belongs includes: determining a set of user locations belonging to the target positioning region; calculating the cumulative value of the membership degree of each user location in the set of user locations relative to the target positioning region; and obtaining the first weight of each user location in the set of user locations based on the membership degree of each user location in the set of user locations relative to the target positioning region and the cumulative value.

[0044] For example, in some embodiments, determining the first global precision factor of the pseudo-satellite layout information based on the first weight, the first precision factor, and the precision factor index of all user locations in the target space includes: determining a set of user locations belonging to the target positioning area; performing a weighted summation based on the first weight and the first precision factor of each user location in the user location set to obtain a first local precision factor of the target positioning area; obtaining a second weight of the target positioning area based on the precision factor index of all positioning areas; and performing a weighted summation based on the second weight and the first local precision factor of all positioning areas to obtain the first global precision factor.

[0045] For example, the calculation method for the first global precision factor is as follows:

[0046] 1) Divide the target space according to positioning requirements. Figure 2 This is a schematic diagram of the first component structure of the target space in this embodiment of the application. The target space is divided into positioning area A, positioning area B, and positioning area C. A core area for user activity can be defined within this area. Within the core area, a certain DOP metric must be met, such as HDOP < 2. Outside the core area, the farther away from the core area, the lower the positioning accuracy requirement, and positioning may even be unnecessary.

[0047] 2) Select an appropriate membership function to calculate the membership degree of each user's location point. The distance from the location point to the positioning area is used as input to calculate the membership degree. Within the core area, the membership degree is 1, such as:

[0048]

[0049] x i Let be the distance from the user's location to the location region. If multiple location regions exist, calculate the membership degree of the same location point with respect to each region, and assign the point to the region with the highest membership degree. For example, if there are three location regions A, B, and C, the membership degree of user location point i is:

[0050] LMF(x i ) = max[LMF A (x i ), LMFB (x i ), LMF C (x i (2)

[0051] 3) Calculate the first weight of the user's location point. For n points belonging to location region A... A There are 1 user points, and the weight of each point is calculated as follows:

[0052]

[0053] Where x i Let LMF be the distance from the i-th user point to the location area. A (x i ) represents the membership degree of the user point to the location area A.

[0054] The final global weighted precision factor can be obtained as follows:

[0055]

[0056] In the formula This indicates the DOP (Domain of Production) index that must be met within the location area A. This indicates the DOP (Domain of Optimization) index that must be met within the location area B. This represents the first precision factor of the i-th user location point belonging to location region A. It represents the first precision factor of the i-th user location point belonging to the positioning area B. If other positioning areas are also included, the weighted sum is performed with reference to positioning areas A and B.

[0057] Equation (4) requires calculating the user's first accuracy factor at each location point. According to navigation theory, the calculation of various accuracy factors is as follows:

[0058]

[0059]

[0060]

[0061]

[0062]

[0063] In the formula, tr represents the matrix trace operator, and H represents the weight coefficient matrix.

[0064] The weight coefficient matrix is ​​calculated as follows:

[0065] H = (G T G) -1 (10)

[0066] G is the observation matrix, defined as:

[0067]

[0068] In the formula (a xi ,a yi ,a zi ) is a unit vector pointing from the user's location to the location of the i-th pseudosatellite; n represents the number of pseudosatellites that can be observed at the user's location, i.e., the number of visible satellites.

[0069] Step 104: Use the first global accuracy factor as the optimization target to perform full-area layout optimization on the pseudo-satellite layout information to obtain the optimal layout information.

[0070] For example, during the search process, if the first global precision factor of the current pseudosatellite layout information meets the corresponding global precision factor index, the current layout information is determined to be the optimal layout information.

[0071] The following example uses the Particle Swarm Optimization (PSO) algorithm to further illustrate the search process. Figure 3 This is a schematic diagram of the second process of the pseudo-satellite deployment method in the embodiments of this application, as shown below. Figure 3 As shown, the method specifically includes:

[0072] Step 301: Construct a target spatial model and generate multiple user locations based on the target spatial model;

[0073] Based on geometric constraints, a realistic planar graphical mathematical model is established. A uniformly distributed random function is used to generate n user locations within this region, representing possible user destinations. In some embodiments, user locations can be generated using other random functions, such as a Gaussian distribution, based on activity frequency.

[0074] Step 302: Initialize pseudo-satellite layout information;

[0075] The number of pseudo-satellites in the pseudo-satellite layout information is initialized to 4, and the positions of the pseudo-satellites are randomly assigned according to geometric constraints.

[0076] Step 303: Based on the constraints of the target space, iteratively update the pseudo-satellite positions in the pseudo-satellite layout information and calculate the first global accuracy factor of the pseudo-satellite layout information;

[0077] The layout optimization employs the PSO algorithm, taking the 3D coordinates of all pseudosatellites as particle positions (the number of pseudosatellites defaults to 4 when the algorithm is first called). Particle positions are randomly assigned, or they can be assigned using the traditional geometric configuration method. Simultaneously, particle velocities are initialized. Here, one particle represents one type of pseudosatellite layout information; initializing multiple particles initializes multiple pseudosatellite layout information.

[0078] Here, we can use the first global precision factor.

[0079] 1) Calculate the function fitness value of each particle, that is, the first global precision factor (DOP) calculated according to formulas (1) to (10). m ).

[0080] 2) Set the individual optimal value pbest of each particle to the initialized particle position, and select the DOP among them. m The position of the smallest particle is taken as the global optimum, gbest.

[0081] 3) Update the position and velocity of each particle. The position update formula is:

[0082] x i =x i-1 +v i (12)

[0083] In the formula x i For the new position, x i-1 For the old position, v i For the new velocity, the updated position of the particle needs to be corrected in conjunction with the actual constraints.

[0084] The speed update formula is:

[0085] v i =w·v i-1 +c1·R1·(pbest i-1 -x i-1 )+c2·R2·(gbest i-1 -x i-1 (13)

[0086] In the formula x i-1 For the old position, v i-1 For the old speed, pbest i-1 gbest is the individual optimal value obtained after the previous iteration. i-1 To obtain the global optimum after the previous iteration, c1 and c2 are learning factors, usually both set to 2; R1 and R2 represent random numbers following U(0,1); w is the inertia factor, a non-negative value, usually calculated using linearly decreasing weights.

[0087]

[0088] In the formula, k is the current iteration step, and K is the maximum iteration step. start Typically, 0.9 is used, w end The value is usually 0.4.

[0089] Step 304: Determine whether the first global precision factor of the layout information meets the index. If not, proceed to step 305; if yes, proceed to step 307.

[0090] Here, the indicator can be the first global precision factor indicator. When the first global precision factor is less than the first global precision factor indicator, it indicates that the indicator is met; otherwise, the indicator is not met, and it is necessary to iteratively update the pseudo-satellite positions and velocities in the layout and calculate the first global precision factor of the new layout information.

[0091] Step 305: Determine if the iteration has converged. If it has not converged, proceed to step 303; if it has converged, proceed to step 306.

[0092] Step 306: Add a pseudo-satellite and continue with step 303;

[0093] Furthermore, the functional fitness value (DOP) of each particle is evaluated. m The algorithm updates the historical best position of each particle and the global best position of the swarm. If the criteria are not met and the iteration has not converged, the algorithm continues to the next iteration; if the criteria are not met and the iteration has converged, a pseudo-satellite is added and the search is restarted.

[0094] Step 307: Search ends, optimal layout information is obtained.

[0095] By adopting the above technical solution, the weight is calculated based on the distance from the user's activity location to the positioning area. This ensures that the accuracy factor of special positioning areas meets the index requirements, while the requirements of other areas are reduced according to the weight. This reduces the difficulty of deployment and, in some cases, can also reduce the number of pseudo-satellites deployed.

[0096] To better reflect the purpose of this application, based on the above embodiments, and considering the failure probability of pseudo-satellites at different locations, redundant pseudo-satellites are added to further optimize the pseudo-satellite layout, such as... Figure 4 As shown, the method specifically includes:

[0097] Step 401: Based on positioning requirements, determine the positioning area and accuracy factor of the target space to be deployed;

[0098] The target space includes a first positioning region and a second positioning region, and the accuracy factor indices of the first positioning region and the second positioning region are different.

[0099] Step 402: Initialize pseudo-satellite layout information and user location for the target space; wherein, the pseudo-satellite layout information includes the number of pseudo-satellites and their locations;

[0100] Step 403: Based on the positioning area, the accuracy factor index of the positioning area, and the user location, calculate the first global accuracy factor of the pseudo-satellite layout information;

[0101] Step 404: Use the first global precision factor as the optimization target to perform full-area layout optimization on the pseudo-satellite layout information to obtain the optimal layout information;

[0102] Step 405: Obtain the failure probability of each pseudo-satellite in the optimal layout information;

[0103] Here, the probability of each pseudosatellite malfunctioning is estimated based on its installation location in the optimal layout information and practical experience. For example, pseudosatellites near entrances / exits are in harsher environments and have a higher probability of malfunctioning or becoming unusable.

[0104] Step 406: Add redundant pseudo-satellites to the optimal layout information and initialize the positions of the redundant pseudo-satellites to obtain redundant layout information;

[0105] Step 407: Based on the failure probability of each pseudosatellite in the optimal layout information, calculate the second global precision factor of the redundant layout information;

[0106] Here, the second global accuracy factor is the weighted accuracy factor for the entire area when redundant pseudosatellites are used for positioning in the event of a single or multiple pseudosatellite failures. The calculation of the second global accuracy factor takes into account the failure probability of pseudosatellites, making the redundant pseudosatellite layout more realistic and exhibiting higher robustness.

[0107] For example, in some embodiments, calculating the second global precision factor of the redundant layout information based on the failure probability of each pseudosatellite in the optimal layout information includes: determining a third weight for each pseudosatellite in the optimal layout information based on the failure probability of each pseudosatellite in the optimal layout information; determining a second precision factor for positioning the user location when a pseudosatellite failure occurs based on the pseudosatellite positions in the redundant layout information and the user location; and determining the second global precision factor of the redundant layout information based on the third weight, the second precision factor, and the precision factor index.

[0108] For example, in some embodiments, determining the second global precision factor of the redundant layout information based on the third weight, the second precision factor, and the precision factor index includes: determining a set of user locations belonging to the target positioning area; in the case of a faulty i-th pseudosatellite in the optimal layout information, performing a weighted sum based on the first weight and the second precision factor of each user location in the user location set to obtain a second local precision factor of the target positioning area; obtaining the second weight of the target positioning area based on the precision factor index of all positioning areas; performing a weighted sum based on the second weight and the second local precision factor of all positioning areas to obtain a third global precision factor in the case of a faulty i-th pseudosatellite; and performing a weighted sum based on the third weight and the third global precision factor of all pseudosatellites in the optimal layout information to obtain the second global precision factor.

[0109] Step 408: Use the second global accuracy factor as the optimization target to optimize the redundant pseudo-satellite positions in the redundant layout information to obtain the optimal redundant layout information.

[0110] In practical applications, when the original pseudo-satellites are working normally, the redundant pseudo-satellites are in a powered-off state. When a pseudo-satellite malfunctions, the redundant pseudo-satellites are powered on to participate in positioning, which can ensure the continuous normal operation of the pseudo-satellite system and has a certain degree of robustness and autonomy.

[0111] For example, suppose the optimal layout information includes m pseudo-satellites, and the failure probability of each satellite is p. i Furthermore, they are independent of each other, and the higher the probability of a pseudosatellite failure, the smaller its corresponding weight. The failure weights of each pseudosatellite satisfy the following relationship:

[0112]

[0113]

[0114] 1) Algorithm initialization. Add a redundant pseudo-satellite, that is, add 3 dimensions to each particle. The first 3m dimensions are the three dimensions of the m pseudo-satellites obtained from the optimal layout information, which remain unchanged during the redundancy optimization process. The last 3 dimensions are randomly initialized.

[0115] 2) Calculate the function fitness value for each particle, i.e., the second global precision factor (DOP) taking into account the failure probability. f ).

[0116]

[0117] In the formula This represents the second precision factor when the i-th user location point belongs to positioning area A and the j-th pseudo-satellite is faulty. In other words, the second global precision factor is obtained by performing a fault weighting operation considering the fault probability of each pseudo-satellite in formula (10).

[0118] Various second precision factors in equation (17) The calculation method is as follows:

[0119]

[0120]

[0121]

[0122]

[0123] In the formula H j To delete the matrix after the j-th row in H, i.e.:

[0124]

[0125] In some embodiments, the failure probabilities of pseudo-satellites can be equal, i.e., the third weight can be set to be equal, and the corresponding weighted DOP is... f Transform into mean DOP f .

[0126] 3) Set the individual optimal value pbest of each particle to the initialized particle position, and select the DOP among them. f The position of the smallest particle is taken as the global optimum, gbest.

[0127] 4) Update the position and velocity of redundant pseudo-satellites in each particle.

[0128] 5) Evaluate the functional fitness (DOP) of each particle. f The process involves updating the historical best position of each particle and updating the global best position of the swarm until the iteration converges, thus obtaining the optimal redundant layout information. If the iteration does not converge, the iteration continues to update the position and velocity of the redundant pseudo-satellites.

[0129] The layout scheme provided in this application embodiment is compared with other schemes. Figure 5 This is a schematic diagram of the second component structure of the target space in an embodiment of this application. The target space is divided into positioning area A, positioning area B, and other areas, such as... Figure 5 The indoor space shown is 100m long, 80m wide, and 5m high, and has geometric constraints. Location area A must meet the HDOP < 1.2 requirement, and location area B must meet the HDOP < 1.5 requirement.

[0130] For region A, x in equation (1) i Let represent the distance from the user's location point in the XOY plane to y = 24, and a = 8. Assuming that the failure probability of each satellite is the same, the pseudo-satellite installation locations can be obtained from this scheme as shown in Table 1:

[0131] Table 1. Pseudo-satellite installation locations

[0132]

[0133] In the table, PL_R represents redundant pseudo-satellites.

[0134] Table 2 shows the probability that the HDOP of each user location point meets the corresponding HDOP index for the three schemes, with 20,000 user location points randomly selected from positioning areas A and B respectively.

[0135] Table 2 Comparison of HDOP Compliance Rates

[0136]

[0137] As shown in Table 2, conventional scheme two has the highest compliance rate in positioning area A, but it does not consider positioning area B, resulting in the worst accuracy factor in positioning area B. In summary, this scheme can balance the indicators of both core areas A and core areas B, outperforming the conventional scheme and demonstrating its superiority.

[0138] In addition to meeting the accuracy factor requirements, this scheme also designs a redundant pseudo-satellite layout. The redundant pseudo-satellites are normally in a powered-off state. When a pseudo-satellite in the original layout fails or becomes unavailable, the redundant pseudo-satellites are powered on and used, which can ensure the continuous and normal operation of the system and has a certain degree of robustness and autonomy.

[0139] To implement the method of the embodiments of this application, based on the same inventive concept, the embodiments of this application also provide a pseudo-satellite deployment device, such as... Figure 6 As shown, the pseudo-satellite layout device 60 includes:

[0140] The configuration unit 601 is used to determine the positioning area and accuracy factor index of the target space to be laid out based on positioning requirements; wherein, the target space includes a first positioning area and a second positioning area, and the accuracy factor indexes of the first positioning area and the second positioning area are different.

[0141] An initialization unit 602 is used to initialize pseudo-satellite layout information and user location for the target space; wherein, the pseudo-satellite layout information includes the number of pseudo-satellites and their locations;

[0142] Search unit 603 is used to calculate a first global precision factor of the pseudo-satellite layout information based on the positioning area, the precision factor index of the positioning area and the user location; and to perform full-area layout optimization of the pseudo-satellite layout information using the first global precision factor as the optimization target to obtain the optimal layout information.

[0143] For example, in some embodiments, the search unit 603 is configured to determine, based on a preset membership function, the target positioning region to which the user's location belongs, and the membership degree relative to the target positioning region; wherein, the target positioning region is a positioning region in the target space; determine a first weight of the user's location based on the target positioning region to which the user's location belongs and the membership degree; determine a first accuracy factor for positioning the user's location based on the pseudo-satellite positions in the pseudo-satellite layout information and the user's location; and determine a first global accuracy factor of the pseudo-satellite layout information based on the first weight, the first accuracy factor, and the accuracy factor index of all user locations in the target space.

[0144] For example, in some embodiments, the search unit 603 is used to determine the membership degree of the user's location in the target space relative to the first positioning region and the membership degree relative to the second positioning region based on a preset membership function; and to determine that the target positioning region to which the user's location belongs is the positioning region corresponding to the maximum membership degree.

[0145] For example, in some embodiments, the search unit 603 is used to determine a set of user locations belonging to the target positioning region; calculate the cumulative value of the membership degree of each user location in the set of user locations relative to the target positioning region; and obtain a first weight of each user location in the set of user locations based on the membership degree of each user location in the set of user locations relative to the target positioning region and the cumulative value.

[0146] For example, in some embodiments, the search unit 603 is configured to determine a set of user locations belonging to the target positioning region; perform a weighted summation based on a first weight and a first precision factor for each user location in the set of user locations to obtain a first local precision factor for the target positioning region; obtain a second weight for the target positioning region based on the precision factor indices of all positioning regions; and perform a weighted summation based on the second weight and the first local precision factor of all positioning regions to obtain a first global precision factor.

[0147] For example, in some embodiments, the search unit 603 is further configured to obtain the failure probability of each pseudo-satellite in the optimal layout information; add redundant pseudo-satellites to the optimal layout information and initialize the positions of the redundant pseudo-satellites to obtain redundant layout information; calculate a second global precision factor of the redundant layout information based on the failure probability of each pseudo-satellite in the optimal layout information; and optimize the positions of the redundant pseudo-satellites in the redundant layout information using the second global precision factor as the optimization target to obtain the optimal redundant layout information.

[0148] For example, in some embodiments, the search unit 603 is configured to determine a third weight for each pseudosatellite in the optimal layout information based on the failure probability of each pseudosatellite in the optimal layout information; determine a second accuracy factor for positioning the user location when a pseudosatellite failure occurs based on the pseudosatellite positions in the redundant layout information and the user location; and determine a second global accuracy factor for the redundant layout information based on the third weight, the second accuracy factor, and the accuracy factor index.

[0149] For example, in some embodiments, the search unit 603 is used to determine a set of user locations belonging to the target positioning area; in the case of a faulty i-th pseudosatellite in the optimal layout information, a weighted sum is performed based on the first weight and the second precision factor of each user location in the user location set to obtain a second local precision factor of the target positioning area; a second weight of the target positioning area is obtained based on the precision factor indices of all positioning areas; a third global precision factor in the case of a faulty i-th pseudosatellite is obtained by weighted summing based on the second weight and the second local precision factor of all positioning areas; and a second global precision factor is obtained by weighted summing based on the third weight and the third global precision factor of all pseudosatellites in the optimal layout information.

[0150] Based on the hardware implementation of each unit in the aforementioned pseudo-satellite deployment device, this application embodiment also provides a pseudo-satellite deployment apparatus, such as... Figure 7 As shown, the pseudo-satellite deployment device 70 includes: a processor 701 and a memory 702 configured to store computer programs capable of running on the processor;

[0151] The processor 701 is configured to execute the method steps in the foregoing embodiments when running a computer program.

[0152] Of course, in practical applications, such as Figure 7As shown, the various components in this device are coupled together via bus system 703. It can be understood that bus system 703 is used to enable communication between these components. In addition to a data bus, bus system 703 also includes a power bus, a control bus, and a status signal bus. However, for clarity, all buses are labeled as bus system 703 in the figure.

[0153] In practical applications, the aforementioned processor can be at least one of the following: Application-Specific Integrated Circuit (ASIC), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field-Programmable Gate Array (FPGA), controller, microcontroller, and microprocessor. It is understood that, for different devices, the electronic devices used to implement the functions of the aforementioned processor can also be other types, and the embodiments of this application do not specifically limit this.

[0154] The aforementioned memory can be volatile memory, such as random-access memory (RAM); or non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); or a combination of the above types of memory, and provides instructions and data to the processor.

[0155] In practical applications, the aforementioned device can be a pseudo-satellite deployment device or a chip applied to a pseudo-satellite deployment device. In this application, the device can implement the functions of multiple units through software, hardware, or a combination of both, enabling the device to execute the pseudo-satellite deployment method provided in any of the above embodiments. Furthermore, the technical effects of each technical solution of this device can be referenced to the technical effects of the corresponding technical solutions in the pseudo-satellite deployment method, and will not be elaborated upon further in this application.

[0156] In an exemplary embodiment, this application also provides a computer-readable storage medium, such as a memory including a computer program, which can be executed by a processor of a pseudo-satellite deployment device to perform the steps of the aforementioned method.

[0157] This application also provides a computer program product, including computer program instructions.

[0158] Optionally, the computer program product can be applied to the pseudo-satellite layout device in the embodiments of this application, and the computer program instructions cause the computer to execute the corresponding processes implemented by the pseudo-satellite layout device in the various methods of the embodiments of this application. For the sake of brevity, they will not be described in detail here.

[0159] This application also provides a computer program.

[0160] Optionally, the computer program can be applied to the pseudo-satellite layout device in the embodiments of this application. When the computer program is run on a computer, it causes the computer to execute the corresponding processes implemented by the pseudo-satellite layout device in the various methods of the embodiments of this application. For the sake of brevity, it will not be described in detail here.

[0161] It should be understood that the terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items. The expressions “having,” “may have,” “comprising,” and “including,” or “may include” and “may contain” used herein may be used to indicate the presence of a corresponding feature (e.g., an element such as a number, function, operation, or component), but do not exclude the presence of additional features.

[0162] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, this information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another, and are not necessarily used to describe a specific order or sequence. For example, without departing from the scope of this invention, first information may also be referred to as second information, and similarly, second information may also be referred to as first information.

[0163] The technical solutions described in the embodiments of this application can be combined arbitrarily without conflict.

[0164] In the several embodiments provided in this application, it should be understood that the disclosed methods, apparatus, and devices can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical, or other forms.

[0165] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0166] In addition, each functional unit in the various embodiments of this application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0167] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A pseudo-satellite layout method, characterized in that, The method includes: Based on positioning requirements, the positioning area and accuracy factor index of the target space to be laid out are determined; wherein, the target space includes a first positioning area and a second positioning area, and the accuracy factor indexes of the first positioning area and the second positioning area are different. Initialize pseudo-satellite layout information and user location for the target space; wherein, the pseudo-satellite layout information includes the number of pseudo-satellites and their locations; Based on the positioning area, the accuracy factor index of the positioning area, and the user location, calculate the first global accuracy factor of the pseudo-satellite layout information; The first global precision factor is used as the optimization target to perform full-area layout optimization on the pseudo-satellite layout information to obtain the optimal layout information; The step of calculating the first global precision factor of the pseudo-satellite layout information based on the positioning area, the precision factor index of the positioning area, and the user location includes: Based on a preset membership function, the target location region to which the user's location belongs, and the membership degree relative to the target location region, are determined; wherein, the target location region is a location region in the target space; Based on the target location area and membership degree to which the user's location belongs, the first weight of the user's location is determined; Based on the pseudo-satellite positions in the pseudo-satellite layout information and the user's position, a first precision factor is determined when locating the user's position. Based on the first weight, the first precision factor, and the precision factor index of all user locations in the target space, the first global precision factor of the pseudo-satellite layout information is determined.

2. The method according to claim 1, characterized in that, The determination of the target location region to which the user's location belongs, and the degree of membership relative to the target location region, based on a preset membership function, includes: Based on a preset membership function, the membership degree of the user's location in the target space relative to the first positioning region and the membership degree relative to the second positioning region are determined. The target location area to which the user's location belongs is determined to be the location area corresponding to the maximum membership degree.

3. The method according to claim 1, characterized in that, The step of determining the first weight of the user's location based on the target location area and membership degree to which the user's location belongs includes: Determine the set of user locations belonging to the target positioning area; Calculate the cumulative value of the membership degree of each user location in the user location set relative to the target positioning region; Based on the membership degree of each user location in the user location set relative to the target positioning region and the accumulated value, the first weight of each user location in the user location set is obtained.

4. The method according to claim 1, characterized in that, The determination of the first global precision factor of the pseudosatellite layout information based on the first weight, the first precision factor, and the precision factor index of all user locations in the target space includes: Determine the set of user locations belonging to the target positioning area; The first local precision factor of the target positioning area is obtained by weighted summation based on the first weight and first precision factor of each user location in the user location set. Based on the accuracy factor index of all positioning areas, the second weight of the target positioning area is obtained; The first global precision factor is obtained by weighted summation of the second weight and the first local precision factor for all positioning regions.

5. The method according to any one of claims 1-4, characterized in that, After obtaining the optimal layout information, the method further includes: Obtain the failure probability of each pseudosatellite in the optimal layout information; Add redundant pseudo-satellites to the optimal layout information and initialize the positions of the redundant pseudo-satellites to obtain redundant layout information; Based on the failure probability of each pseudosatellite in the optimal layout information, the second global accuracy factor of the redundant layout information is calculated. The second global accuracy factor is used as the optimization target to optimize the positions of redundant pseudo-satellites in the redundant layout information, thereby obtaining the optimal redundant layout information.

6. The method according to claim 5, characterized in that, The calculation of the second global precision factor of the redundant layout information based on the failure probability of each pseudosatellite in the optimal layout information includes: Based on the failure probability of each pseudosatellite in the optimal layout information, a third weight for each pseudosatellite in the optimal layout information is determined. Based on the pseudo-satellite positions in the redundant layout information and the user positions, a second precision factor is determined when locating the user positions in the event of a pseudo-satellite failure. Based on the third weight, the second precision factor, and the precision factor index, the second global precision factor of the redundant layout information is determined.

7. The method according to claim 6, characterized in that, The step of determining the second global precision factor of the redundant layout information based on the third weight, the second precision factor, and the precision factor index includes: Determine the set of user locations belonging to the target positioning area; In the case of the i-th pseudo-satellite failure in the optimal layout information, the second local precision factor of the target positioning area is obtained by weighted summation based on the first weight and the second precision factor of each user position in the user position set. Based on the accuracy factor index of all positioning areas, the second weight of the target positioning area is obtained; The third global accuracy factor is obtained by weighted summation of the second weight and the second local accuracy factor of all positioning areas in the case of the i-th pseudo-satellite failure. The second global precision factor is obtained by weighted summation of the third weight and third global precision factor of all pseudo-satellites in the optimal layout information.

8. A pseudo-satellite layout device, characterized in that, The pseudo-satellite deployment device includes: A configuration unit is used to determine the positioning area and accuracy factor index of the target space to be laid out based on positioning requirements; wherein, the target space includes a first positioning area and a second positioning area, and the accuracy factor indexes of the first positioning area and the second positioning area are different. An initialization unit is used to initialize pseudo-satellite layout information and user location for the target space; wherein, the pseudo-satellite layout information includes the number of pseudo-satellites and their locations; The search unit is used to calculate a first global precision factor of the pseudo-satellite layout information based on the positioning area, the precision factor index of the positioning area, and the user location; and to perform full-area layout optimization on the pseudo-satellite layout information using the first global precision factor as the optimization target to obtain the optimal layout information. The search unit is configured to determine, based on a preset membership function, the target positioning region to which the user's location belongs, and the membership degree relative to the target positioning region; wherein the target positioning region is a positioning region in the target space; determine a first weight of the user's location based on the target positioning region to which the user's location belongs and the membership degree; determine a first accuracy factor for positioning the user's location based on the pseudo-satellite positions in the pseudo-satellite layout information and the user's location; and determine a first global accuracy factor of the pseudo-satellite layout information based on the first weight, the first accuracy factor, and the accuracy factor index of all user locations in the target space.

9. A pseudo-satellite deployment device, characterized in that, The pseudo-satellite deployment device includes: a processor and a memory configured to store computer programs capable of running on the processor. Wherein, when the processor is configured to run the computer program, it performs the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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