Method and device for estimating longitude and latitude of base station

Abstract

The invention provides a method and device for estimating longitude and latitude of a base station, and solves the problem that the geographic position of the base station cannot be effectively estimated under the condition that only GPS longitude and latitude and corresponding RSRP data reported by a mobile terminal are known. The method comprises the following steps: acquiring a measurement data set containing position information and an RSRP value; mapping each RSRP value into a circle radius, and determining a circular area by taking each piece of position information as a circle center; and performing pairwise combination on all the circular areas to calculate intersection points, performing weighted average calculation according to coordinates of all the intersection points, and outputting latitude and longitude coordinates of the base station to be positioned. According to the method, the signal intensity is mapped into the geometric radius, and the circle intersection principle and frequency weighted average are utilized, so that stable and efficient estimation of the position of the base station in a data limited scene is realized, and the dependence of an existing positioning method on multi-dimensional measurement data is effectively overcome; and the automation level and the coverage checking efficiency of base station positioning in network optimization are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of 5G communication technology, in particular to a method and device for estimating longitude and latitude of a base station. BACKGROUND

[0002] In a mobile communication system, network optimization is a crucial task. The primary task of network optimization is to determine the coverage of a base station, and the prerequisite for determining the coverage of a base station is to accurately determine the location of the base station, i.e., the longitude and latitude of the base station. At present, common base station positioning methods mainly include the following four methods: positioning method according to signal strength (RSS), positioning method according to signal time of arrival (TOA), positioning method according to signal time difference of arrival (TDOA), and positioning method according to signal angle of arrival (AOA).

[0003] In actual operation, the above methods usually need to obtain multiple physical quantities, such as RSS, RSRP (reference signal received power), signal arrival time, frequency angle, and base station antenna transmission power. However, in actual scenarios, it is more common that only the longitude and latitude data obtained by a mobile terminal using a GPS-based software measurement tool and the RSRP value of the base station signal received by the terminal are available. Therefore, it is of great significance to position the base station according to the longitude and latitude data provided by the mobile terminal and the received base station signal RSRP value. SUMMARY

[0004] The present application provides a method and device for estimating the longitude and latitude of a base station, which solves the problem that the geographic location of a base station cannot be effectively estimated when only the GPS longitude and latitude reported by a mobile terminal and the corresponding reference signal received power (RSRP) data are known.

[0005] In a first aspect, the embodiments of the present application provide a method for estimating the longitude and latitude of a base station, which comprises: obtaining a set of measurement data; the set of measurement data contains multiple position information and reference signal received power values corresponding to each position information; mapping each reference signal received power value to a circle radius and each position information to a circle center to determine a circular area with the circle radius and the circle center; calculating the intersection points of each pair of circular areas, and outputting the longitude and latitude coordinates of the base station to be positioned by weighted average calculation of the coordinates of all intersection points.

[0006] In one of the embodiments, before obtaining the set of measurement data, the method further comprises the steps of: receiving raw measurement data from one or more mobile terminals; grouping the raw measurement data according to the base station identifier to obtain the set of measurement data corresponding to the base station to be positioned.

[0007] In one embodiment, after acquiring the measurement data set, the method further includes the following step: The measurement data set is filtered based on the dispersion of the location information in the measurement data set.

[0008] In one embodiment, after acquiring the measurement data set, the method further includes the following step: The amount of data in the measurement dataset is compared with a preset threshold. If the amount of data does not reach a preset threshold, the measurement data set is removed.

[0009] In one embodiment, the step of mapping the reference signal received power value to a circle radius includes: The received power value of the reference signal is subjected to numerical conversion and normalization. The radius of the circle is obtained by taking the square root of the normalized value.

[0010] Furthermore, the numerical conversion and normalization process specifically includes: The reference signal received power value is inversely taken and then subjected to maximum-minimum normalization to map the value to a preset positive number range.

[0011] In one embodiment, a verification step is included before outputting the estimated latitude and longitude coordinates: The estimated latitude and longitude coordinates are compared with the existing base station locations on the electronic map. If the distance difference is greater than the alarm threshold, an abnormal location alarm is output.

[0012] Secondly, embodiments of this application also provide an apparatus for estimating the latitude and longitude of a base station, used to implement the base station latitude and longitude estimation method described in any embodiment of the first aspect, comprising: an acquisition module, used to acquire a measurement data set; the measurement data set includes multiple location information and a reference signal received power value corresponding to each location information; a determination module, used to map each reference signal received power value to a circle radius; and further used to determine a circular region with each location information as the center, using the circle radius and the circle center; and a calculation module, used to calculate the intersection points of the circular regions pairwise, and calculate the latitude and longitude coordinates of the base station to be located by weighted averaging the coordinates of all intersection points.

[0013] Thirdly, embodiments of this application also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any one of the embodiments of the first aspect.

[0014] Fourthly, embodiments of this application also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method as described in any embodiment of the first aspect.

[0015] The above-described technical solutions adopted in the embodiments of this application can achieve the following beneficial effects: This application maps the received power value of the reference signal to the radius of a geometric circle and constructs a circular region based on the location information of the mobile terminal. By utilizing the principle of circle intersection and the intersection point weighted average algorithm, it achieves efficient and stable estimation of the base station location by relying only on the single parameter of terminal location and signal strength. This effectively overcomes the dependence of existing positioning methods on multi-dimensional measurement data and significantly improves the base station positioning capability and network optimization efficiency in data-constrained scenarios. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart illustrating a method for estimating the latitude and longitude of a base station according to an embodiment of this application; Figure 2 This is an example diagram of the 5G base station signal acquisition data in an embodiment of this application; Figure 3 This is a partial data diagram of a base station ID in an embodiment of this application; Figure 4 This is a structural diagram of a device for estimating the latitude and longitude of a base station according to an embodiment of this application; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0018] The technical solutions provided by the various embodiments of this application are described in detail below with reference to the accompanying drawings.

[0019] Figure 1 The present application provides a flowchart of a method for estimating the latitude and longitude of a base station, the method including steps 110-130.

[0020] In one embodiment, before obtaining the measurement data set in step 110, the method further includes the following step: Step 100-1: Receive raw measurement data from one or more mobile terminals; To achieve base station positioning, raw observational data must first be collected from the physical world. This step aims to accomplish this data collection task.

[0021] The system continuously receives measurement data automatically reported by one or more mobile terminals via a communication interface. This data forms the basis for all subsequent processing.

[0022] For example, the data includes GPS latitude and longitude, RSRP values, and base station IDs obtained from mobile terminal measurement tools.

[0023] The raw measurement data refers to the initial set of unfiltered or ungrouped data measured and reported by the mobile terminal. Its core data format is (base station identifier, mobile terminal latitude and longitude, reference signal received power value).

[0024] One or more mobile terminals define the diversity of data sources, which can be measurements from a single device in different locations or measurements from a group of a large number of user devices.

[0025] For example, it could be a professional mobile phone on a road test vehicle, or it could be a smartphone used by tens of thousands of ordinary users.

[0026] The data processed in this step, in terms of its specific structure and source, is defined in the inventive concept as follows: The 5G base station signal acquisition data is shown in the following dataset. Formula 1 Where N is the total amount of data, ( ( ) represents the GPS latitude and longitude coordinates of the mobile terminal. For reference signal received power, This is the base station identifier. Some of its data is as follows: Figure 2 As shown, Step 100-2: Group the original measurement data according to the base station identifier to obtain the measurement data set corresponding to the base station to be located.

[0027] After acquiring the mixed raw data, it needs to be processed to enable independent positioning calculations for individual base stations. This step completes the data preprocessing work.

[0028] The system reads the base station identifier (ID) from each piece of raw data and divides all data records into different logical groups based on this identifier. Each group corresponds to a base station to be located, forming a clean subset of data specific to that base station.

[0029] The base station identifier is a code that uniquely identifies a base station in the network and is a key basis for data packet processing.

[0030] The grouping refers to classifying the mixed raw data according to the base station to which it belongs.

[0031] The positioning target of this application is a single base station, therefore all measurement points related to that base station must be separated from massive amounts of data.

[0032] For example, assuming the raw data contains data from base station IDs 12345 and 67890, this step will create two separate sets of measurement data, one specifically for estimating the location of base station 12345 and the other for estimating the location of base station 67890.

[0033] The specific logic and screening criteria of this preprocessing procedure are described in the invention as follows: For data preprocessing, the data is grouped according to base station ID. For a specific base station IDi, its data subset is: Formula 2 Set a data volume threshold If the amount of data under the base station IDi If the base station is deemed not to meet the positioning requirements, it will be excluded.

[0034] Step 110: Obtain a set of measurement data; the set of measurement data includes multiple location information and a reference signal received power value corresponding to each location information.

[0035] After data preprocessing is completed, the positioning algorithm is deployed for a single base station. This step formally initiates the process by loading the core dataset to be processed.

[0036] The measurement data set obtained in this step is a subset of valid data associated with a specific base station to be located, obtained after the aforementioned grouping and filtering. This set forms the basis for the subsequent construction of the geometric model.

[0037] Specifically, for example, each data record in the set explicitly contains the location coordinates of a mobile terminal and the corresponding reference signal received power value.

[0038] The measurement data set specifically refers to a subset of data that has passed quality screening and is bound to a single base station.

[0039] For example, after grouping in step 100-2, the collection of all data related to a base station to be located.

[0040] In this application, the location information specifically refers to the latitude and longitude coordinates of the mobile terminal, provided by the terminal's GPS or other positioning system. This is the location of the geometric center.

[0041] In one embodiment, the measurement data set originates from a single mobile terminal.

[0042] This embodiment illustrates the implementation of the present invention with minimal hardware configuration, demonstrating the flexibility of the method in terms of data sources.

[0043] All data records in the measurement dataset were obtained by the same mobile terminal at different times and in different geographical locations. During its movement, the terminal continuously measures the reference signal received power between its current location and the base station to be located, thus forming a data sequence for positioning.

[0044] A single mobile terminal refers to a unique data acquisition device, such as a dedicated mobile phone used for road testing or a regular user's mobile phone with measurement software installed.

[0045] This method does not require the integration of data from multiple terminals, is simple to implement, and is especially suitable for specialized drive test and troubleshooting tasks for network optimization personnel.

[0046] In another embodiment, the measurement data set originates from multiple different mobile terminals.

[0047] This embodiment demonstrates the typical data format of the present invention in a large-scale application scenario, showcasing its ability to perform efficient network optimization using group data.

[0048] The data records in the measurement dataset originate from a large number of different mobile terminals. Each terminal, at its own location, independently measures and reports the reference signal received power value from the same base station to be located. These data are collected and aggregated into the measurement dataset by the network-side platform.

[0049] Multiple different mobile terminals refer to a group of devices used by numerous users and geographically distributed.

[0050] This method can quickly and cost-effectively acquire massive amounts of measurement data with wide geographical coverage, making it particularly suitable for operators' routine and automated network monitoring and optimization.

[0051] In this application, the reference signal received power value specifically refers to the reference signal power received by the mobile terminal at the location information from the base station to be located, in dBm. This is the raw input for calculating the radius of the circle.

[0052] The precise definition of this dataset is given in the invention: In one embodiment, after obtaining the measurement data set in step 110, the method further includes the following step: Step 110-1: Filter the measurement data set according to the distribution dispersion of the location information in the measurement data set.

[0053] To further improve positioning accuracy, this embodiment adds a screening checkpoint at the data entry point based on the quality of spatial distribution.

[0054] This step calculates the dispersion index (such as standard deviation) of all location coordinates and filters them accordingly. The aim is to retain high-quality datasets that have a wider geographical distribution of measurement points and can provide effective geometric constraints on base stations from multiple directions.

[0055] The dispersion of the data points is an indicator that measures how geographically dispersed they are. A higher dispersion indicates a wider distribution of measurement points, meaning they are more likely to surround the base station from different directions, and the positioning effect is generally better.

[0056] In this embodiment, datasets with overly concentrated measurement points are filtered out because the intersection area of ​​the circles constructed from these data would be very large, leading to a sharp decrease in positioning accuracy or even failure.

[0057] For example, one dataset might have all its points concentrated within a single building (low dispersion), while another dataset might have points distributed across an entire city block (high dispersion). This step will prioritize or retain the latter for subsequent processing.

[0058] In one embodiment, after obtaining the measurement data set in step 110, the method further includes the following step: Step 110-2-1: Compare the amount of data in the measurement data set with a preset threshold; The preset threshold is a pre-defined minimum data volume threshold, for example, T. min = 10. This threshold needs to be determined experimentally to ensure that there are enough data points to generate valid circular intersection geometry.

[0059] To ensure the effectiveness and stability of the positioning algorithm, if the amount of data is too small, there may be no effective intersections between the circles, or the number of intersections may be too small, leading to unreliable weighted average results.

[0060] Step 110-2-2: In response to the fact that the amount of data has not reached the preset threshold, the measurement data set is removed.

[0061] To ensure that the algorithm has the most basic operational conditions, this embodiment provides a minimum data volume check.

[0062] The system will use data subset D i Data volume M and preset threshold T min A comparison is performed. If the amount of data is insufficient, it is determined that reliable positioning cannot be performed, and therefore further processing of this set is abandoned.

[0063] Preset threshold (T) min This is the minimum data threshold set to ensure the effectiveness of the positioning model.

[0064] Step 120 maps each of the reference signal received power values ​​to a circle radius, and each of the position information is a circle center, and determines a circular region using the circle radius and the circle center.

[0065] This is the core step in transforming a communication problem into a geometric problem, using a series of mathematical transformations to construct a spatial region where a base station might exist for each data point.

[0066] This step iterates through the data set D. i For each record in the array, its RSRP value is converted into a circle radius r through a defined mapping process. j and its location (Lon m Lat m Using as the center, a circular region is ultimately determined for each point.

[0067] The mapping is one of the core operations of this application, which refers to converting the signal strength (dBm) into a distance quantity (circle radius) for geometric construction through a specific set of mathematical transformations.

[0068] The circular region is the geometric model constructed in this application. Its physical meaning is that the base station has a high probability of being located in the vicinity of a circle with the terminal location as the center and the mapping radius as the radius.

[0069] In one embodiment, the circular region is constructed in a two-dimensional Cartesian coordinate system.

[0070] To simplify the computational model and align with the representation methods of most electronic maps, this method approximates the Earth's surface as a two-dimensional plane within a small area, thereby constructing a geometric model.

[0071] This invention processes all geographical locations (latitude and longitude coordinates) and geometric structures (circular regions, intersection calculations) within a two-dimensional plane. Specifically, the spherical coordinates formed by the Earth's longitude (Lon) and latitude (Lat) are approximated as Cartesian coordinates within the local coverage area of ​​the base station to be located, either through map projection (such as Web Mercator projection) or by direct approximation, thereby transforming all calculations into a two-dimensional geometric problem.

[0072] A two-dimensional plane here refers to a planar geometric space that contains only the X-axis (e.g., representing longitude) and the Y-axis (e.g., representing latitude), ignoring third-dimensional information such as elevation or altitude.

[0073] This approximation greatly simplifies the computational complexity. Solving the equations for intersecting circles is a mature, stable, and computationally efficient process in two-dimensional space. However, if we consider three-dimensional space, we need to define a "signal sphere" instead of a "signal circle" and transform the intersection calculation into a spherical intersection, which becomes extremely complex in terms of data processing and computation, and is usually unnecessary for the accuracy requirements of base station positioning.

[0074] The technical solution for this mapping process is specified in detail in the invention: regarding the data volume... For base station IDi, take the negative of its RSRP value to convert it to a positive scale, denoted as Then, through max-min normalization, Mapping to the specified interval [a, b] yields the normalized value. The normalization formula is shown below. Formula 2 Formula 3 In this invention, a = 0.0001 and b = 0.001 are set for... Take the square root to obtain the radius of the circle for each data point. .

[0075] In one embodiment, step 120, mapping the reference signal received power value to a circle radius, includes: Step 120-1: Perform numerical conversion and normalization on the received power value of the reference signal; This is the first step in the mapping process, which aims to preprocess the original signal strength values ​​to a regular and uniform numerical range in preparation for generating the geometric radius.

[0076] This step performs two operations in sequence: first, a numerical conversion is performed, taking the opposite of the negative RSRP value to obtain the positive scale signal strength value; then, a normalization process is performed, scaling the positive scale value to a preset positive range.

[0077] The numerical conversion mentioned in this application specifically refers to the inverse operation. Because the RSRP value is negative (e.g., -95dBm), inversion makes it positive (e.g., 95), which facilitates subsequent processing.

[0078] The normalization process involves scaling the inverted values ​​to a fixed, small range of positive numbers [a, b] (e.g., a = 0.0001, b = 0.001). The aim is to eliminate differences in the absolute size of the original data, unifying them to a scale suitable for generating the circle radius.

[0079] Step 120-2: Obtain the radius of the circle by performing a square root operation on the normalized value.

[0080] This step follows the normalization result from the previous step, completing the conversion from the preprocessed signal strength value to the final geometric radius.

[0081] This step performs a square root operation on the normalized values, and the result is the final radius value used to determine the circular region.

[0082] The square root operation refers to the final step in mapping signal strength to a distance scale. The square root operation can adjust the sensitivity of the numerical values, making the final generated circle radius more consistent with the needs of actual positioning scenarios.

[0083] Furthermore, the numerical conversion and normalization process specifically includes: Step 120-1-1: Take the opposite of the received power value of the reference signal and perform maximum-minimum normalization to map the value to a preset positive number range.

[0084] This step provides a more specific definition and expansion of the overarching concept of "numerical transformation and normalization".

[0085] This step clearly specifies that the numerical conversion is "taking the opposite number", the normalization process is "maximum-minimum normalization", and clearly indicates that the output target is a preset positive number range.

[0086] The maximum-minimum normalization is a specific normalization algorithm that uses a linear transformation to scale data to a given minimum value a and a maximum value b.

[0087] The specific processing method is described in the invention as follows: taking the negative of its RSRP value to convert it into a positive scale, denoted as... Then, through max-min normalization, Map to the specified interval [a, b].

[0088] For example, in this application, a = 0.0001 and b = 0.001 are set.

[0089] Step 130 involves calculating the intersection points of the circular regions in pairs, and then calculating the latitude and longitude coordinates of the base station to be located based on the weighted average of the coordinates of all intersection points.

[0090] After all the circular regions have been constructed, this step enters the location calculation stage, where the final location of the base station is estimated from numerous regions using geometric intersection and statistical methods.

[0091] This step first involves pairing all circular regions together, calculating the coordinates of the intersection point for each pair of circles, and compiling all valid intersection points into an intersection set. Then, the frequency of each unique intersection point appearing in this set is counted, and using this frequency as a weight, the latitude and longitude coordinates of all unique intersection points are weighted and averaged. The resulting value is the latitude and longitude coordinates of the base station to be located.

[0092] The calculation of the intersection point by pairwise combination refers to traversing all possible pairs of circles and solving for the coordinates of the intersection point between the two circles. For M circles, there are C(M,2) combinations. Each pair of circles may produce 0, 1, or 2 real intersection points.

[0093] The weighted average calculation is the core algorithm of this application. Its weights are not arbitrarily set; for example, they are determined by the frequency of each unique intersection point appearing in the set of all intersection points. An intersection point that appears more frequently represents more circles intersecting nearby, increasing the likelihood that the location is the true location of the base station, and therefore carries a higher weight in the final estimate.

[0094] The solution process is fully defined by the following invention: Intersection calculation: for each data point With the center as the corresponding r j Let C be the radius, and construct a circular region on a two-dimensional plane. Then calculate the coordinates of the intersection points of all pairs of circles under this base station ID. For any two circles C... k and C l (The centers of the circles are P) k P l The radii are r k r l The coordinates of their intersection point can be obtained by solving the following system of nonlinear equations: Formula 4 Where (x, y) are the latitude and longitude coordinates of the intersection points. Solving this system of equations yields 0, 1, or 2 real solutions. If no solution exists, record it as ['none', 'none']. If a solution exists, record the coordinates of all valid intersection points. Repeat this process for all pairwise circle pairs to obtain the intersection set E = {E1, E2, …, E} for the base station ID. H}, where H is the total number of intersections.

[0095] Weighted average: For all valid intersection points E obtained from the intersection calculation, the final estimated location of the base station is calculated using a frequency-weighted average method. , First, count the frequency of each unique intersection point. Let there be U unique intersection point coordinates, and let the u-th intersection point be E. u The frequency is f u (That is, the number of times it appears in the set E of all pairwise intersections of circles). Therefore, the formula for calculating the latitude and longitude of a base station is: Formula 5 Formula 6 in,( , () is the intersection point E u The latitude and longitude coordinates are used. This weighting method ensures that intersections that occur more frequently contribute more to the final estimation result, thus improving the stability and accuracy of the estimation results.

[0096] To more intuitively illustrate the process of finding the intersection points, the following combines... Figure 3 The measured data of a certain base station shown below provides a specific calculation example.

[0097] Partial data of a certain base station ID, such as Figure 3As shown, the process of finding the intersection point of the two circles is explained below. First, find the intersection points of each pair of circles. Based on the indices, we can construct 10 pairs of circles, as shown below: [(23160, 23161), (23160, 23218), (23160, 23226), (23160, 23227), (23161, 23218), (23161, 23226), (23161, 23227), (23218, 23226), (23218, 23227), (23226, 23227)]. Then, find the intersection points of each pair. This gives us the latitude and longitude coordinates of all intersection points, i.e., [[102.746592, 26.380888], [102.790213, 26.369514], [102.743474, 26.378763], [102.793774, 26.360141], [102.746569,26.380874], [102.766157, 26.385183], [102.748684, 26.382033], [102.763778,26.385346], [102.789734, 26.394199], [102.748657, 26.391107], [102.746593,26.380851], [102.758154, 26.401689], [102.746731, 26.38408], [102.755496,26.39987], [102.744553, 26.383267], [102.761172, 26.400386], [102.745642,26.386038], [102.758455, 26.399225], ['None', 'None'], ['None', 'None']] (None means the intersection point does not exist).

[0098] Where ['None', 'None'] indicates that there are no real intersection points for the pair of circular regions. This example clearly demonstrates the complete process from the original data to generating the set of intersection points.

[0099] This specific calculation process is a detailed explanation and data verification of the calculation of intersection points by pairwise combinations of circular regions in step 130 above, providing clear input for the subsequent weighted average calculation.

[0100] In one embodiment, a verification step is included before outputting the estimated latitude and longitude coordinates in step 130: The estimated latitude and longitude coordinates are compared with the existing base station locations on the electronic map. If the distance difference is greater than the alarm threshold, an abnormal location alarm is output.

[0101] This is the final output step of the method, which not only outputs the results but also applies them to actual operation and maintenance scenarios for effectiveness verification and risk warning.

[0102] This step compares the new location of the base station calculated by this method with the original location of the base station recorded in the electronic map database. If the planar distance between the two exceeds the set alarm threshold, a location anomaly alarm message is automatically generated and output.

[0103] The existing base station locations in the electronic map refer to the theoretically planned or initial locations of the base stations, as recorded by the operator.

[0104] The alarm threshold is a preset distance threshold (e.g., 50 meters). When the deviation between the estimated location and the recorded location exceeds this threshold, it indicates that the base station may have physically moved, or that the initial record was incorrect.

[0105] The location results of the method described in this application can be applied to actual network operation and maintenance to achieve automated verification and anomaly monitoring of base station locations.

[0106] Figure 4 A structural diagram of an apparatus for estimating the latitude and longitude of a base station is provided for embodiments of this application, used to implement the base station latitude and longitude estimation method described in any embodiment of the first aspect, comprising: The acquisition module 401 is used to acquire a set of measurement data; the set of measurement data includes multiple location information and a reference signal received power value corresponding to each location information.

[0107] The determining module 402 is used to map each of the reference signal received power values ​​to a circle radius; and is also used to determine a circular region with each of the position information as the center, and with the circle radius and the circle center.

[0108] The calculation module 403 is used to calculate the intersection points of the circular area in pairs, and to calculate the latitude and longitude coordinates of the base station to be located by weighted average of the coordinates of all intersection points.

[0109] In one embodiment, the acquisition module includes: The first acquisition unit is used to acquire a set of measurement data; the set of measurement data includes multiple location information and a reference signal received power value corresponding to each location information; The determining module includes: The first determining unit is used to map each of the reference signal received power values ​​to a circle radius; The second determining unit is used to determine a circular region with each of the location information as the center and the radius of the circle; The computing module includes: The first calculation unit is used to calculate the intersection points of the circular regions by combining them pairwise. The second calculation unit is used to perform a weighted average calculation based on the coordinates of all intersection points and output the latitude and longitude coordinates of the base station to be located.

[0110] In one embodiment, the acquisition module further includes: The second acquisition unit is configured to receive raw measurement data from one or more mobile terminals; and group the raw measurement data according to the base station identifier to obtain the measurement data set corresponding to the base station to be located.

[0111] The above embodiments are used to implement the features of steps 100-1 and 100-2 in the specification.

[0112] In one embodiment, the acquisition module further includes: The third acquisition unit is used to compare the amount of data in the measurement data set with a preset threshold; and in response to the data amount not reaching the preset threshold, to remove the measurement data set.

[0113] The above embodiments are used to implement the features of steps 110-2-1 and 110-2-2 in the specification.

[0114] In one embodiment, the acquisition module further includes: The fourth acquisition unit is used to filter the measurement data set based on the distribution dispersion of the location information in the measurement data set.

[0115] The above embodiments are used to implement the features of step 110-1 in the specification.

[0116] In one embodiment, the determining module further includes: The third determining unit is used to perform numerical conversion and normalization on the received power value of the reference signal; and to obtain the radius of the circle by square root operation.

[0117] The above embodiments are used to implement the features of steps 120-1 and 120-2 in the specification.

[0118] In one embodiment, the third determining unit is specifically used to perform maximum-minimum normalization after taking the inverse of the reference signal received power value, and to map the value to a preset positive number range.

[0119] The above embodiments are used to implement the features of step 120-1-1 in the specification.

[0120] In one embodiment, the computing module further includes: The third calculation unit is used to count the frequency of each unique intersection point coordinate appearing in all intersection points; and to perform a weighted average calculation on the latitude and longitude of the unique intersection point coordinates using the frequency as the weight.

[0121] The above embodiments are used to implement the features of frequency-weighted average calculation of base station location as described in the specification.

[0122] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0123] Therefore, this application also proposes a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the methods described in any embodiment of this application.

[0124] Furthermore, this application also proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in any embodiment of this application.

[0125] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0126] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The function specified in one or more boxes.

[0127] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0128] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory. Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0129] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device 500 shown is merely an example and should not impose any limitations on the function and scope of use of the embodiments of this application. It includes: one or more processors 520; and a storage device 510 for storing one or more programs, which, when run by the one or more processors 520, cause the one or more processors 520 to implement the method for estimating the latitude and longitude of a base station provided in the embodiments of this application, the method including: Acquire a set of measurement data; the set of measurement data includes multiple location information and a reference signal received power value corresponding to each location information; Each of the reference signal received power values ​​is mapped to a circle radius, and each of the position information is a circle center, with the circle radius and the circle center determining a circular region; The circular regions are combined in pairs to calculate the intersection points. The latitude and longitude coordinates of the base station to be located are then calculated based on the weighted average of the coordinates of all intersection points.

[0130] The electronic device 500 also includes an input device 530 and an output device 540; the processor 520, storage device 510, input device 530 and output device 540 in the electronic device can be connected by a bus or other means, as shown in the figure, which is connected by a bus 550.

[0131] Storage device 510, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and module units, such as the program instructions corresponding to the method for estimating the latitude and longitude of a base station in the embodiments of this application. Storage device 510 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the terminal, etc. Furthermore, storage device 510 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, storage device 510 may further include memory remotely located relative to processor 520, and these remote memories can be connected via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0132] Input device 530 can be used to receive input digital, character, or voice information, and to generate key signal inputs related to user settings and function control of the electronic device. Output device 540 may include electronic devices such as a display screen and a speaker.

[0133] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0134] Those skilled in the art will understand that, unless otherwise stated, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be understood that when a device or component is “connected” to another device or component, it may be directly connected to the other device or component, or there may be an intermediary device or component. Furthermore, the term “connection” as used herein may include partially wireless connections as well as partially wired connections.

[0135] In the description of this application, it should be understood that the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances. Furthermore, in the description of this application, unless otherwise stated, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship.

[0136] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of this application should be included within the scope of the claims of this application.

Claims

1. A method for estimating the latitude and longitude of a base station, characterized in that, The method includes: Acquire a set of measurement data; the set of measurement data includes multiple location information and a reference signal received power value corresponding to each location information; Each of the reference signal received power values ​​is mapped to a circle radius, and each of the position information is a circle center, with the circle radius and the circle center determining a circular region; The circular regions are combined in pairs to calculate the intersection points. The latitude and longitude coordinates of the base station to be located are then calculated based on the weighted average of the coordinates of all intersection points.

2. The method for estimating the latitude and longitude of a base station as described in claim 1, characterized in that, Before acquiring the measurement data set, the following steps are also included: Receive raw measurement data from one or more mobile terminals; The original measurement data is grouped according to the base station identifier to obtain the measurement data set corresponding to the base station to be located.

3. The method for estimating the latitude and longitude of a base station as described in claim 1, characterized in that, After obtaining the measurement data set, the method further includes the following steps: The amount of data in the measurement dataset is compared with a preset threshold. If the amount of data does not reach a preset threshold, the measurement data set is removed.

4. The method for estimating the latitude and longitude of a base station as described in claim 1, characterized in that, After obtaining the measurement data set, the method further includes the following steps: The measurement data set is filtered based on the dispersion of the location information in the measurement data set.

5. The method for estimating the latitude and longitude of a base station as described in claim 1, characterized in that, The step of mapping the received power value of the reference signal to the radius of a circle includes: The received power value of the reference signal is subjected to numerical conversion and normalization. The radius of the circle is obtained by taking the square root of the normalized value.

6. The method for estimating the latitude and longitude of a base station as described in claim 5, characterized in that, The numerical conversion and normalization process is as follows: The reference signal received power value is inversely taken and then subjected to maximum-minimum normalization to map the value to a preset positive number range.

7. The method for estimating the latitude and longitude of a base station as described in claim 1, characterized in that, Before outputting the estimated latitude and longitude coordinates, a verification step is also included: The estimated latitude and longitude coordinates are compared with the existing base station locations on the electronic map. If the distance difference is greater than the alarm threshold, an abnormal location alarm is output.

8. An apparatus for estimating the latitude and longitude of a base station, used to implement the base station latitude and longitude estimation method according to any one of claims 1 to 7, characterized in that, include: An acquisition module is used to acquire a set of measurement data; the set of measurement data includes multiple location information and a reference signal received power value corresponding to each location information; The determining module is configured to map each of the reference signal received power values ​​to a circle radius; and is also configured to determine a circular region with each of the position information as the center, using the circle radius and the circle center; The calculation module is used to calculate the intersection points of the circular areas in pairs, and to calculate the latitude and longitude coordinates of the base station to be located by weighted averaging the coordinates of all intersection points.

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

10. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1-7.

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