Indoor positioning method and related equipment

Abstract

The invention relates to the technical field of positioning, in particular to an indoor positioning method and related equipment. The method comprises the following steps: in a process of positioning an indoor position of a target terminal with a Bluetooth function, determining an alternative first position, a second area and a third position; wherein the first position is determined based on the high-precision base station; the second area is determined according to a signal intensity fingerprint map, the signal intensity fingerprint map indicates a corresponding relation between the signal intensity of a Bluetooth signal received by the target terminal and the indoor position, and the Bluetooth signal is sent by a beacon; the third position is determined by performing iterative optimization processing on a plurality of indoor positions according to the Bluetooth signal; determining the actual position of the target terminal in the first position, the second area and the third position according to a preset decision rule; according to the invention, the technical problems of high layout cost and low indoor positioning accuracy in the prior art can be solved.

Description

Technical Field

[0001] The present application relates to the field of positioning technology, and in particular to an indoor positioning method and related equipment. Background Art

[0002] In the prior art, indoor positioning is a positioning method for accurately locating a target terminal in a closed indoor environment, such as Bluetooth positioning, ultrasonic positioning, and infrared positioning; Bluetooth positioning is a positioning method for determining the location of a target terminal based on the signal strength of a Bluetooth signal received by the terminal device from a Bluetooth base station or other Bluetooth signal transmitting device (such as a beacon).

[0003] In actual applications, the target terminal in Bluetooth positioning is usually a terminal device with Bluetooth function such as a mobile phone, and the Bluetooth base station in Bluetooth positioning is usually fixed in an indoor environment; according to the difference in positioning accuracy, Bluetooth base stations can be divided into low-precision base stations and high-precision base stations. The positioning accuracy of low-precision base stations is usually at the meter level, and the positioning accuracy of high-precision base stations can reach the centimeter level.

[0004] In actual applications, although high-precision base stations can perform indoor positioning relatively accurately, if a large number of high-precision base stations are deployed indoors, the deployment cost will be very high. In addition, due to the complex indoor environment, such as indoor walls and indoor decorations, the Bluetooth signal will be blocked and reflected, resulting in the predicted position of the target terminal determined by the signal strength being inconsistent with the actual position of the target terminal, ultimately resulting in a low accuracy rate for indoor positioning. Summary of the invention

[0005] In view of this, the purpose of the present application is to provide an indoor positioning method and related equipment to solve the technical problems of high deployment cost and low indoor positioning accuracy existing in the prior art.

[0006] In a first aspect, the present application provides an indoor positioning method, wherein a plurality of high-precision base stations and a plurality of beacons are arranged indoors; the method comprises:

[0007] In the process of positioning the indoor position of a target terminal having a Bluetooth function, determining a first position, a second area, and a third position as an alternative;

[0008] The first location is determined based on the high-precision base station; the second area is determined based on a signal strength fingerprint map, the signal strength fingerprint map indicates the corresponding relationship between the signal strength of the Bluetooth signal received by the target terminal and the indoor location, the Bluetooth signal is sent by the beacon; the third location is determined by iterative optimization processing for multiple indoor locations based on the Bluetooth signal;

[0009] According to a preset decision rule, the actual location of the target terminal is determined among the first location, the second area, and the third location.

[0010] In a second aspect, the present application provides an electronic device, which includes a processor and a memory, wherein the memory is used to store an application program, and the processor runs or executes a software program stored in the memory so that the electronic device implements the indoor positioning method as described above.

[0011] In a third aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a program code executed by a processor, wherein the program code is used to implement the above-mentioned indoor positioning method.

[0012] In a fourth aspect, the present application provides a computer program product, which includes computer instructions. When the computer instructions are executed on an electronic device, the electronic device implements the above-mentioned indoor positioning method.

[0013] Beneficial effects:

[0014] The present application provides an indoor positioning method, wherein a plurality of high-precision base stations and a plurality of beacons are arranged indoors; the method comprises: in the process of positioning the indoor position of a target terminal having a Bluetooth function, determining a first position, a second area and a third position as candidates; wherein the first position is determined based on the high-precision base station; the second area is determined according to a signal strength fingerprint map, the signal strength fingerprint map indicates the correspondence between the signal strength of the Bluetooth signal received by the target terminal and the indoor position, the Bluetooth signal being sent by the beacon; the third position is determined by iteratively optimizing the Bluetooth signal for a plurality of indoor positions; according to a preset decision rule, determining the actual position of the target terminal in the first position, the second area and the third position;

[0015] In summary, the present application provides a high-precision base station and beacon for indoor positioning, which is used to provide an indoor positioning solution that takes into account both positioning accuracy and deployment cost for users who have high requirements for indoor positioning accuracy and have limited deployment costs; the present application determines the second area through a signal strength fingerprint map and determines the third position through iterative optimization processing, and then collaboratively determines the actual position of the target terminal according to the decision rules, so as to avoid the technical problem of inaccurate positioning caused by directly performing indoor positioning based on the signal strength of the received Bluetooth signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. The following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 A schematic diagram of the structure of an indoor positioning system provided in an embodiment of the present application;

[0018] Figure 2 A schematic diagram of the process of the indoor positioning method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution of the present application will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0020] First, the present application provides an indoor positioning method, which is applied to an indoor positioning system, such as Figure 1 , Figure 1 The schematic diagram of the structure of the indoor positioning system provided in the embodiment of the present application, the indoor positioning system comprises: a server 100, a target terminal 200, a high-precision base station 300 and a beacon 400;

[0021] Among them, the server 100 is a network device; the target terminal 200 is a terminal device with Bluetooth function worn by the target user who needs to perform indoor positioning, such as a mobile phone or bracelet with Bluetooth function; in this embodiment of the application, the indoor position of the target user is approximated to the indoor position of the target terminal 200, so the indoor positioning process for the target terminal 200 in the subsequent description is actually the indoor positioning process for the target user; the number of high-precision base stations 300 and beacons 400 is multiple.

[0022] Before the indoor positioning method provided in the embodiment of the present application is implemented, it is necessary to deploy multiple high-precision base stations 300 and multiple beacons 400 at different locations indoors. The deployment process includes: steps (1) to (2), the details of which are as follows:

[0023] Step (1): Determine the on-site situation;

[0024] Specifically, before deploying the high-precision base station 300 and beacon 400, it is necessary to first determine the indoor site conditions, which include: indoor room layout, wireless network conditions, power supply layout, and other information that affects Bluetooth signal transmission and network information transmission.

[0025] (2): Determine the deployment information according to the on-site conditions and deployment rules;

[0026] Specifically, the deployment rules include: the need to consider indoor functional zoning, the frequency of use of the functional zoning by target users, the minimum deployment interval, and the deployment requirements of the high-precision base station 300 and the beacon 400;

[0027] The functional zoning of the room mainly refers to areas with different functions such as the kitchen, bathroom and bedroom; for example, the high-precision base station 300 and / or beacon 400 can be arranged in the bathroom and the top wall of the bathroom; for another example, the high-precision base station 300 and / or beacon 400 can be arranged 2 meters above the head of the bed and be arranged in a manner of tilting downward 45 degrees and facing the bed surface.

[0028] Different target users usually have different usage frequencies for different functional partitions; the functional partitions used frequently by target users need to be deployed with high precision, and adjacent high-precision base stations 300 or beacons 400 need to ensure that the minimum deployment interval is less than 1.5 meters. In actual applications, the distance between adjacent high-precision base stations 300 or beacons 400 can be 1 meter to 1.5 meters.

[0029] The deployment requirements of the high-precision base station 300 and beacon 400 deployment are specifically determined based on the performance parameters of the high-precision base station 300 and beacon 400 deployment;

[0030] For example, the deployment of the high-precision base station 300 is required to be carried out according to the following requirements:

[0031] 1) Requirements for the deployment of a functional zone: If the coverage of the functional zone is large, a high-precision base station 300 is deployed at a maximum interval of 5 meters, and the high-precision base stations 300 are required to have unobstructed line of sight to each other;

[0032] 2) Requirements for the deployment of multiple functional zones: The high-precision base stations 300 deployed in different functional zones need to ensure line of sight as much as possible, where line of sight means that the target user can directly see them. If line of sight cannot be guaranteed, the door positions of the functional zones can be determined as connection points to indirectly achieve line of sight between the two functional zones.

[0033] 3) The number of high-precision base stations 300 should be kept small and the coverage rate high;

[0034] For another example, the deployment of the beacon 400 is required to be carried out according to the following requirements:

[0035] 4) 2 to 3 beacons 400 are deployed in each functional area;

[0036] 5) There should be no obstructions between the beacons 400.

[0037] In practical applications, other sensors, such as ultrasonic positioning base stations and millimeter wave radar equipment, can also be deployed indoors where indoor positioning is required to assist the high-precision base station 300 and beacon 400 in locating the actual position of the target terminal 200 indoors, so as to improve the accuracy of indoor positioning.

[0038] like Figure 2 As shown, Figure 2 The schematic diagram of the process of the indoor positioning method provided in the embodiment of the present application includes: S110 to S120, and the details are as follows:

[0039] S110: in the process of positioning the indoor position of the target terminal with Bluetooth function, determining a first position, a second area, and a third position as candidates;

[0040] Among them, the first position is determined based on a high-precision base station; the second area is determined based on a signal strength fingerprint map, which indicates the correspondence between the signal strength of the Bluetooth signal received by the target terminal and the indoor position, and the Bluetooth signal is sent by a beacon; the third position is determined by iterative optimization processing of the Bluetooth signal for multiple indoor locations.

[0041] Specifically, Figure 2 As shown, the first location is determined based on the server 100 , the target terminal 200 and the high-precision base station 300 ; the second area and the third location are determined based on the server 100 , the target terminal 200 and the beacon 400 .

[0042] In one implementation, S110 includes: Step (3) to Step (4), the details of which are as follows:

[0043] Step (3): Obtain multiple signal reception times of the first Bluetooth signal.

[0044] Among them, the first Bluetooth signal is sent by the target terminal to multiple high-precision base stations; the multiple signal receiving times correspond one-to-one to the multiple high-precision base stations.

[0045] Specifically, the embodiment of the present application uses a "first Bluetooth signal" and a "second Bluetooth signal" to distinguish between the sending and receiving ends of different Bluetooth signals; the first Bluetooth signal is sent by the target terminal 200 and received by the high-precision base station 300; the second Bluetooth signal is sent by the beacon 400 and received by the target terminal 200.

[0046] The target terminal 200 sends a first Bluetooth signal at a first preset time frequency. At least three high-precision base stations 300 that are within line of sight of the target terminal 200 receive the first Bluetooth signal respectively. The high-precision base stations 300 need to record the signal reception time when the first Bluetooth signal is received; at least three high-precision base stations 300 transmit the signal reception time to the server 100 respectively.

[0047] Step (4): Determine the first position based on the time difference between any two signal reception times, the air propagation speed of the Bluetooth signal, and the indoor position of the high-precision base station.

[0048] Specifically, under normal circumstances, the propagation speed of the Bluetooth signal in the air is determined, so the server 100 can determine the first position of the target terminal 200 based on a TDOA (Time Difference Of Arrival) algorithm according to at least three signal reception times.

[0049] In one implementation, S110 includes: Step (5) to Step (7), the details of which are as follows:

[0050] Step (5): Obtain multiple receiving end signal strengths of the second Bluetooth signal.

[0051] The second Bluetooth signal is sent by the beacon to the target terminal; the signal strengths of multiple receiving terminals correspond to the multiple beacons in a one-to-one correspondence.

[0052] Specifically, multiple beacons 400 send a second Bluetooth signal at a second preset time frequency. When the target terminal 200 receives the second Bluetooth signal, the target terminal 200 encapsulates the second Bluetooth signal to obtain a locPackage and transmits the locPackage to the server 100. The server 100 decapsulates the locPackage and determines the receiving end signal strength of the second Bluetooth signal.

[0053] Among them, since the Bluetooth signal will attenuate during the propagation process, the signal strength of the second Bluetooth signal received by the target terminal 200 is different from the signal strength of the second Bluetooth signal sent by the beacon. Therefore, the "receiving end" is used to indicate that the signal strength here is received by the target terminal 200, and it is not the signal strength when the beacon is sent.

[0054] Step (6): Determine the second area based on the maximum signal strength voting according to the signal strengths of multiple receiving ends and the signal strength fingerprint map.

[0055] Specifically, the signal strength fingerprint map indicates the corresponding relationship between the signal strength of the receiving end of the Bluetooth signal and the indoor position, so the server 100 can calculate the second area based on the signal strength fingerprint map and the maximum signal strength voting method.

[0056] In one implementation, before executing S110, a signal strength fingerprint map is determined through steps (7) to (11), as shown in detail below:

[0057] Step (7): Determine multiple calibration positions indoors.

[0058] Specifically, before determining the signal strength fingerprint map, it is necessary to determine the calibration position indoors; the calibration position is an indoor position that is convenient for statistics on information such as position coordinates; in actual applications, the coordinate system is constructed with the position of the lower left corner of the room as the point to ensure that the position coordinates of any indoor position are positive numbers.

[0059] After the coordinate system is established, the indoor area can be divided into multiple unit areas according to the coordinate system; in actual operation, the unit area can be a square area of ​​1 meter * 1 meter; the endpoints of the unit area are the calibration positions (i.e., sampling points) for sampling the second Bluetooth signal sent by the beacon in the process of determining the signal strength fingerprint map.

[0060] Step (8): Obtain the receiving end signal strength P of the second Bluetooth signal sent by the jth beacon and received by the target terminal at the i-th calibration position ij ;

[0061] Wherein, 1≤i≤I, I represents the number of calibrated positions; 1≤j≤J, J represents the number of beacons.

[0062] Specifically, in an indoor environment, due to the influencing factors such as multipath effects, obstacles and device power, the receiving-end signal strength of the second Bluetooth signal sent by the same beacon received by the target terminal 200 at different times at an indoor location will not always be equal, but will show certain fluctuations. The fluctuations conform to the Gaussian distribution. Therefore, it can be seen that the process of constructing a signal strength fingerprint map is essentially a process of determining the parameters (mean and standard deviation) of the Gaussian distribution that the specific values ​​of the receiving-end Bluetooth signal received at any indoor location at multiple times conform to. When the actual signal strength of the second Bluetooth signal sent by a beacon is received at a certain indoor location at the target time, the Gaussian distribution can be used to optimize the actual signal strength to obtain the receiving-end signal strength, which is used to remove the real-time measurement errors caused by influencing factors such as multipath effects, obstacles and device power.

[0063] In the embodiment of the present application, the Gaussian parameters of the Gaussian distribution to which the signal strength data corresponding to one calibration position conforms are determined as the Gaussian parameters of the Gaussian distribution to which the signal strength data corresponding to all indoor positions conform;

[0064] In the process of determining the Gaussian parameters, the target terminal 200 receives the second Bluetooth signal sent by the J beacons at each of the I calibration positions, and the server 100 determines the receiving end signal strength of the second Bluetooth signal accordingly, a total of (I×J) receiving end signal strengths; wherein the receiving end signal strength of the second Bluetooth signal sent by the jth beacon received by the target terminal at the i-th calibration position can be expressed as P ij .

[0065] Step (9): summing up the J receiving end signal strengths received at the i-th calibration position among the I calibration positions to obtain the superimposed signal strength corresponding to the i-th calibration position.

[0066] Specifically, for each of the i calibration positions, the J receiving end signal strengths received at the calibration position are summed to obtain the superimposed signal strength, and the superimposed signal strength conforms to the Gaussian distribution; in actual operation, in order to improve the accuracy of the determined Gaussian parameters, Gaussian noise can be added to the superimposed signal strength.

[0067] Step (10): determining signal strength distribution data according to the i superimposed signal strengths;

[0068] The signal strength distribution data indicates the corresponding relationship between the superimposed signal strength and the calibrated position.

[0069] Specifically, each calibrated position corresponds to a superimposed signal strength, and i calibrated positions correspond to I superimposed signal strengths; in an embodiment of the present application, the coordinate of the calibrated position in the coordinate system is determined as the x-axis coordinate and the superimposed signal strength corresponding to the calibrated position is determined as the y-axis coordinate to obtain the signal strength data corresponding to the calibrated position, and the I signal strength data corresponding to I calibrated positions are signal strength distribution data.

[0070] Step (11): determining a signal strength fingerprint map according to the signal strength distribution data;

[0071] Among them, the signal strength fingerprint map indicates the corresponding relationship between the superimposed signal strength and the indoor location.

[0072] Specifically, when T groups of signal strength distribution data corresponding to I calibration positions are obtained, Gaussian parameters of the Gaussian distribution corresponding to each calibration position are determined according to the T groups of signal strength distribution data.

[0073] In the process of determining Gaussian parameters, the kernel function can use a radial basis function (or covariance function matrix) to evaluate the similarity between any two signal strength data. The radial basis function is as follows:

[0074]

[0075] In the formula, the kernel function parameters σ and l can be determined by maximizing the marginal log-likelihood to determine the optimal value;

[0076] In the process of determining Gaussian parameters, the prior distribution of Gaussian distribution is expressed as f(x)~N(u f ,K ff ); When the superimposed signal intensity corresponding to each calibration position in each group of signal intensity distribution data in the T groups of signal intensity distribution data is superimposed on the prior distribution, the Gaussian distribution can be adjusted to

[0077] In actual use, when the actual signal strength of the second Bluetooth signal received at any indoor location in the room is input into the formula That is, the signal strength at the receiving end is obtained.

[0078] In one implementation, S120 further includes: Step (12) to Step (14), the details of which are as follows:

[0079] Step (12): Determine a plurality of indoor locations randomly selected indoors as candidate locations.

[0080] Step (13): performing multiple rounds of iterative optimization processing on multiple candidate positions until a stopping condition is reached;

[0081] The stopping conditions include: the number of iteration rounds reaches a first threshold and the number of candidate positions reaches a second threshold; the optimization process of any round includes: steps (13.1) to (13.2), as shown in detail below:

[0082] Step (13.1): Determine the fitness values ​​of all candidate positions according to the preset fitness function.

[0083] Specifically, the first threshold and the second threshold can be determined according to actual conditions, and this application does not make any specific limitations on this.

[0084] In one implementation, step (13.1) includes: step (13.1.1) to step (13.1.5), the details of which are as follows:

[0085] Step (13.1.1): for the nth candidate location, determine M beacons whose indoor distances to the nth candidate location are within a preset threshold.

[0086] Specifically, the preset threshold can be determined according to actual needs, and this application does not make any specific limitations on this.

[0087] Step (13.1.2): Obtain the receiving end signal strength of the second Bluetooth signal respectively sent by the M beacons and received by the target terminal at the nth candidate position.

[0088] Specifically, since the Bluetooth signal will attenuate during the propagation process, the receiving end signal strength of the second Bluetooth signal received by the user terminal 200 is usually smaller than the transmitting end signal strength of the corresponding beacon when sending the second Bluetooth signal; therefore, if the transmitting end signal strength of the beacon is to be determined, a corresponding estimation is required based on the receiving end signal strength; it should be emphasized that the receiving end signal strength is optimized through the signal strength fingerprint map.

[0089] Step (13.1.3): Determine the signal strength of the second Bluetooth signal sent by each beacon to the nth candidate position according to the signal strengths of the M receiving ends and by using the signal attenuation model corresponding to each beacon;

[0090] The signal attenuation model indicates the attenuation characteristics of the Bluetooth signal when it propagates indoors. The formula used in the signal attenuation model is as follows:

[0091]

[0092] Where, d ij represents the indoor distance between the hth beacon and the i-th calibration position; d 0 Indicates the reference distance; Indicates that it corresponds to d ijThe average value of the receiving end signal strength received during multiple rounds of signal strength measurement; P 0 is the first attenuation parameter, indicating that at the reference distance d 0 The reference signal strength at n p is the second attenuation parameter, which represents the attenuation factor.

[0093] In one implementation, before executing S110, the attenuation parameter in the signal attenuation model is determined through step (15), as shown in detail below:

[0094] Step (15): According to the receiving end signal strength P of the second Bluetooth signal sent by the jth beacon received by the target terminal at the I calibration position Ij , based on the invasive weed algorithm and according to the signal strength fingerprint map, the attenuation parameter in the signal attenuation model is optimized to obtain the attenuation parameter corresponding to the jth beacon;

[0095] The signal attenuation model indicates the corresponding relationship between the signal strength of the second Bluetooth signal and the calibration distance, and the calibration distance is the distance between the calibration position and the beacon.

[0096] Specifically, the discrete binary invasive weed algorithm targets the decay parameter P 0 and n p Encode; the encoding accuracy is retained to 6 decimal places, and P 0 The search space is set from 0 to min(P ij ), n p The search space is set to between 2 and 4;

[0097] The encoding is divided into equal parts according to the encoding accuracy, and the length of each step is 10 -N , N represents the number of digits after the decimal point, and the encoding length can be calculated by L=log 2 [10 N (U max -U min ) calculation, where U max is the maximum value of the search space, U min is the minimum value of the search space;

[0098] In the process of optimizing the attenuation parameters, the initial population parameters are 40, the maximum value of the diffusion variance is 15, and the final value is 3; the change of any bit value conforms to the normal diffusion law, and the diffusion value is processed by a mapping function based on the mapping function. The mapping function is as follows:

[0099]

[0100] In the formula, represents the change value of the current bit iteration round;

[0101] After mapping it Then, after comparing it with a random number between 0 and 1, it is replaced with 0 or 1. Then, the final value bit value in the previous iteration is modulo 2 to obtain the latest change value and restore it to a natural number, and substitute it into Calculated in Then the fitness function is evaluated to determine the seeds that can be diffused in the next round. After the above steps are completed, the attenuation parameter P of each beacon can be obtained. 0 and n p .

[0102] Step (13.1.4): Determine the K adjacent signal strengths and the average signal strength corresponding to the nth candidate position;

[0103] Among them, the adjacent signal strength indicates the signal strength of the transmitting end of the candidate position adjacent to the nth candidate position; the average signal strength indicates the average value of K adjacent signal strengths.

[0104] Step (13.1.5): Determine the fitness value of the nth candidate position according to the corresponding transmitter signal strength, receiver signal strength, adjacent signal strength and average signal strength of the nth candidate position and a preset fitness function.

[0105] Specifically, in the embodiment of the present application, the fitness function is as follows:

[0106]

[0107] Where P k.map Indicates the adjacent signal strength; represents the average signal strength; P ij ′ Indicates the signal strength of the sending end; P ij Indicates the signal strength at the receiving end. In practical applications, the value range of K can be set between 2 and 4.

[0108] Step (13.2): according to the fitness value, determine the secondary candidate positions arranged around each candidate position to obtain a candidate position group corresponding to each candidate position;

[0109] Among them, the fitness value is positively correlated with the number of sub-level candidate positions; the distribution of multiple sub-level candidate positions obeys the normal distribution.

[0110] Step (14): Determine a third position based on the multiple candidate position groups obtained after the stop condition has been reached.

[0111] In one implementation, step (14) includes: step (14.1) to step (14.3), the details of which are as follows:

[0112] Step (14.1): Determine the fitness value of each candidate position group among the multiple candidate position groups obtained after the stop condition of the iterative optimization process has been reached.

[0113] Step (14.2): The candidate position group with the smallest fitness value among the multiple candidate position groups is confirmed as the optimal position group.

[0114] Step (14.3): Determine the average value of all candidate positions included in the optimal position group as the third position.

[0115] In one implementation, if the stopping condition is not reached after t rounds of iterative optimization processing is performed on the candidate positions, the remaining candidate positions after t rounds of iterative optimization processing are screened, and the A target candidate position groups obtained by the screening are respectively subjected to multiple rounds of iterative optimization processing until the stopping condition is reached;

[0116] The target candidate position group includes: the ath candidate position among the A candidate positions with the highest fitness value among the remaining candidate positions, and B candidate positions whose indoor distances to the ath candidate position are less than or equal to a third threshold.

[0117] Specifically, t, A, B and the third threshold can be determined according to actual needs; in one implementation, t can be set to 4, A can be set to 4, and B can be set to 3; in one implementation, the third threshold can be a multiple of the distance between any two candidate positions in the target candidate position group. In actual operation, the multiple can be set to 4 times.

[0118] S120: Determine the actual location of the target terminal in the first location, the second area, and the third location according to a preset decision rule.

[0119] Specifically, in the embodiment of the present application, the decision rules are as follows:

[0120] 1) In the case where at least one of the first position and the third position is not located in the second area, the second area is determined as the actual position;

[0121] 2) In the case where both the first position and the third position are located in the second area, if the functional subarea where the actual position pointed to by the first position and the third position is located is covered by the high-precision base station 300, the first position is determined as the actual position, otherwise the third position is determined as the actual position;

[0122] 3) In the case where the first position is not located in the second area, but the third position is located in the second area, the third position is determined as the actual position;

[0123] 4) In the case where the first position is located in the second area but the third position is not located in the second area, the first position is determined as the actual position.

[0124] In actual operation, other types of sensor devices can be used to correct the actual position determined by the above steps; for example, if the actual position is determined to be in a functional area indoors, but other types of sensor devices installed in the functional area fail to collect corresponding human body data to assist in confirming the actual position, the abnormal situation needs to be reported to the server 100; in actual applications, if the frequency of occurrence of abnormal situations is too high, it indicates that it is necessary to adjust the deployment of high-precision base stations 300 and beacons 400 and update the signal strength fingerprint map.

[0125] Second, the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, steps S110 to S120 provided in the above embodiment are implemented.

[0126] Third, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, steps S110 to S120 of the above embodiment are executed.

[0127] Fourth, the computer program product provided in the present application includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the method in the previous method embodiment. The specific implementation can refer to steps S110 to S120 of the method embodiment, which will not be repeated here.

[0128] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0129] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0130] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0131] It should be noted that if the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can essentially be embodied in the form of a software product, or the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM) random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0132] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0133] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. An indoor positioning method, characterized in that: The indoor space is provided with a plurality of high-precision base stations and a plurality of beacons; the method comprises: In the process of positioning the indoor position of a target terminal having a Bluetooth function, determining a first position, a second area, and a third position as an alternative; The first location is determined based on the high-precision base station; the second area is determined based on a signal strength fingerprint map, the signal strength fingerprint map indicates the corresponding relationship between the signal strength of the Bluetooth signal received by the target terminal and the indoor location, the Bluetooth signal is sent by the beacon; the third location is determined by iterative optimization processing for multiple indoor locations based on the Bluetooth signal; According to a preset decision rule, the actual location of the target terminal is determined among the first location, the second area, and the third location.

2. The method according to claim 1, characterized in that The step of determining the first position comprises: Acquire multiple signal receiving moments of the first Bluetooth signal; Wherein, the first Bluetooth signal is sent by the target terminal to the multiple high-precision base stations; the multiple signal receiving times correspond to the multiple high-precision base stations one by one; The first position is determined according to the time difference between any two signal reception moments, the air propagation speed of the Bluetooth signal and the indoor position of the high-precision base station.

3. The method according to claim 1, characterized in that The step of determining the second area comprises: Acquire multiple receiving end signal strengths of the second Bluetooth signal; Wherein, the second Bluetooth signal is sent by the beacon to the target terminal; there is a one-to-one correspondence between the signal strengths of the multiple receiving ends and the multiple beacons; The second area is determined based on the maximum signal strength voting according to the plurality of receiving end signal strengths and the signal strength fingerprint map.

4. The method according to claim 1, characterized in that The step of determining the signal strength fingerprint map comprises: determining a plurality of calibration locations within the chamber; Obtain the receiving end signal strength P of the second Bluetooth signal sent by the jth beacon and received by the target terminal at the i-th calibrated position ij ; Wherein, 1≤i≤I, I represents the number of the calibrated positions; 1≤j≤J, J represents the number of the beacons; Summing the J receiving end signal strengths received at the i-th calibration position among the I calibration positions to obtain a superimposed signal strength corresponding to the i-th calibration position; Determining signal strength distribution data according to the I superimposed signal strengths; Wherein, the signal strength distribution data indicates the corresponding relationship between the superimposed signal strength and the calibrated position; Determining the signal strength fingerprint map according to the signal strength distribution data; The signal strength fingerprint map indicates the corresponding relationship between the superimposed signal strength and the indoor location.

5. The method according to claim 4, characterized in that The step of determining the third position comprises: Determine multiple indoor locations randomly selected indoors as candidate locations; Performing multiple rounds of iterative optimization processing on the multiple candidate positions until a stopping condition is reached; Determining the third position according to a plurality of candidate position groups obtained after the stop condition has been reached; The stopping condition includes: the number of iterations reaches a first threshold and the number of candidate positions reaches a second threshold; the optimization process of any one round includes: Determining the fitness values ​​of all the candidate positions according to a preset fitness function; According to the fitness value, the secondary candidate positions arranged around each candidate position are determined to obtain the candidate position group corresponding to each candidate position; wherein the fitness value is positively correlated with the number of secondary candidate positions arranged; and the distribution of multiple secondary candidate positions obeys a normal distribution.

6. The method according to claim 5, characterized in that Determining the fitness values ​​of all the candidate positions according to a preset fitness function includes: For the nth candidate position, determine M beacons whose indoor distances from the nth candidate position are within a preset threshold; Acquire a receiving end signal strength of a second Bluetooth signal respectively sent by the M beacons and received by the target terminal at the nth candidate position; According to the M receiving end signal strengths, determining the sending end signal strength of the second Bluetooth signal sent by each beacon to the nth candidate position through a signal attenuation model corresponding to each beacon; Wherein, the signal attenuation model indicates the attenuation characteristics of the Bluetooth signal when propagating indoors; Determine K adjacent signal strengths and an average signal strength corresponding to the nth candidate position; The adjacent signal strength indicates the signal strength of the transmitting end of the candidate position adjacent to the nth candidate position; the average signal strength indicates the average value of K adjacent signal strengths; The fitness value of the nth candidate position is determined according to the transmitting end signal strength, the receiving end signal strength, the adjacent signal strength and the average signal strength corresponding to the nth candidate position and a preset fitness function.

7. The method according to claim 5, characterized in that The method further comprises: According to the receiving end signal strength P of the second Bluetooth signal sent by the jth beacon received by the target terminal at the I calibrated positions Ij , based on the invasive weed algorithm and according to the signal strength fingerprint map, optimizing the attenuation parameter in the signal attenuation model to obtain the attenuation parameter corresponding to the j-th beacon; The signal attenuation model indicates a corresponding relationship between the signal strength of the second Bluetooth signal and a calibrated distance, and the calibrated distance is a distance between the calibrated position and the beacon.

8. The method according to claim 5, characterized in that The determining the third position according to the plurality of candidate position groups obtained after the stop condition has been reached includes: Determining the fitness value of each of the plurality of candidate position groups obtained after a stop condition of the iterative optimization process has been reached; Confirming the candidate position group with the smallest fitness value among the multiple candidate position groups as the optimal position group; An average value of all candidate positions included in the optimal position group is determined as the third position.

9. The method according to claim 5, characterized in that If the stopping condition is still not met after t rounds of iterative optimization processing is performed on the candidate positions, the remaining candidate positions after t rounds of iterative optimization processing are screened, and the A target candidate position groups obtained by the screening are respectively subjected to multiple rounds of iterative optimization processing until the stopping condition is met; Among them, the target candidate position group includes: the ath candidate position among the A candidate positions whose adaptation values ​​are the highest among the remaining candidate positions, and the B candidate positions whose indoor distances to the ath candidate position are less than or equal to a third threshold.

10. An electronic device, characterized in that: The electronic device includes a processor and a memory, the memory is used to store an application program, and the processor runs or executes a software program stored in the memory so that the electronic device implements the indoor positioning method as described in any one of claims 1 to 9.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store program codes executed by a processor, and the program codes are used to implement the indoor positioning method according to any one of claims 1 to 9.

12. A computer program product, characterized in that The computer program product includes computer instructions. When the computer instructions are executed on an electronic device, the electronic device implements the indoor positioning method as claimed in any one of claims 1 to 9.

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