Vehicle-mounted bluetooth positioning parameter processing method and device, electronic equipment and storage medium

Abstract

The application provides a vehicle-mounted Bluetooth positioning parameter processing method and device, electronic equipment and a storage medium, relates to the technical field of Internet of Vehicles, and can automatically determine target positioning parameters corresponding to a target mobile terminal which has not been calibrated through a preset algorithm based on positioning equipment data corresponding to the target vehicle model, wherein the positioning equipment data comprises Bluetooth information corresponding to the target mobile terminal, Bluetooth information corresponding to a calibrated reference mobile terminal and reference positioning parameters corresponding to the target vehicle model, that is, the target vehicle model is calibrated for a limited number of times, such as one or two mobile terminals, and the preset algorithm can be used to match other mobile terminals, so that the calibration workload and calibration cost of the vehicle-mounted Bluetooth positioning parameters are greatly reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Vehicles, and in particular to a vehicle-mounted Bluetooth positioning parameter processing method and device, electronic equipment and a storage medium. BACKGROUND

[0002] Due to the wide application of Bluetooth and its low-cost characteristics, more and more vehicles choose the Bluetooth communication of a mobile phone as the only or main communication carrier of a digital vehicle key. The RSSI (Received Signal Strength Indication) field strength value of Bluetooth can be used as a common means to determine the relative distance and position of the mobile phone and the vehicle, so that the vehicle can determine whether the user is in the vehicle or close to the vehicle by the change of the RSSI field strength, thereby performing some vehicle operations such as automatic unlocking, automatic greeting, etc.

[0003] Since different brands and different models of mobile phones are affected by factors such as transmission power, antenna, shell, frame, etc., the signal transmission strength of the mobile phone, at present, each vehicle model can only be manually calibrated once, and the calibration result is used as a basic parameter to match different models of mobile phones to meet the user experience of most people. This brings a lot of workload: assuming that there are N mobile phones on the market and M vehicle models, the calibration times are N*M, which is an exponential growth number. With the increase of the models of mobile phones and vehicles, the calibration times will increase more and more, and the calibration cost will also increase exponentially. SUMMARY

[0004] The present application aims to provide a vehicle-mounted Bluetooth positioning parameter processing method, device, electronic equipment and storage medium to reduce the calibration workload and calibration cost of vehicle-mounted Bluetooth positioning parameters.

[0005] In a first aspect, the present application provides a vehicle-mounted Bluetooth positioning parameter processing method, comprising:

[0006] Obtaining positioning device data corresponding to a target vehicle model, the positioning device data comprising Bluetooth information corresponding to a target mobile terminal to be processed, Bluetooth information corresponding to a calibrated reference mobile terminal, and reference positioning parameters corresponding to the target vehicle model, the Bluetooth information comprising basic signal strength data;

[0007] According to the positioning device data, determining target positioning parameters corresponding to the target mobile terminal and the target vehicle model by a preset algorithm.

[0008] Further, the obtaining of the positioning device data corresponding to the target vehicle model comprises:

[0009] acquire the Bluetooth information corresponding to the target mobile terminal from a pre-established Bluetooth fingerprint database; wherein the Bluetooth fingerprint database stores Bluetooth information corresponding to each mobile terminal.

[0010] Further, the reference mobile terminal includes a first mobile terminal and a second mobile terminal, and the basic signal strength data includes a basic signal strength matrix composed of RSSI values of multiple preset directions; and the determining of the target positioning parameter corresponding to the target vehicle model of the target mobile terminal according to the positioning device data through a preset algorithm includes:

[0011] calculating the target positioning parameter corresponding to the target vehicle model of the target mobile terminal through a first preset algorithm according to the basic signal strength matrix corresponding to the target mobile terminal, the basic signal strength matrix corresponding to the first mobile terminal, the reference positioning parameter corresponding to the target vehicle model, and the basic signal strength matrix corresponding to the second mobile terminal and the reference positioning parameter corresponding to the target vehicle model.

[0012] Further, the first preset algorithm includes the following formula:

[0013]

[0014] wherein M xi represents the target positioning parameter corresponding to the target vehicle model i of the target mobile terminal x, ABS represents taking an absolute value, M ai represents the reference positioning parameter corresponding to the target vehicle model i of the first mobile terminal a, M bi represents the reference positioning parameter corresponding to the target vehicle model i of the second mobile terminal b, || represents taking a matrix norm, N a represents the basic signal strength matrix corresponding to the first mobile terminal a, N b represents the basic signal strength matrix corresponding to the first mobile terminal b, N x represents the basic signal strength matrix corresponding to the target mobile terminal x.

[0015] Further, the positioning device data further includes a Bluetooth anchor point position of the target vehicle model, the Bluetooth information further includes a device antenna position, and the basic signal strength data includes a basic signal strength matrix composed of RSSI values of multiple preset directions; and the determining of the target positioning parameter corresponding to the target vehicle model of the target mobile terminal according to the positioning device data through a preset algorithm includes:

[0016] determining a weight value of each preset direction according to the device antenna position corresponding to the target mobile terminal and the Bluetooth anchor point position of the target vehicle model;

[0017] According to the weight value of each preset direction, the base signal strength matrix corresponding to the target mobile terminal, and the base signal strength matrix corresponding to the reference mobile terminal and the reference positioning parameter corresponding to the target vehicle type, the target positioning parameter of the target mobile terminal corresponding to the target vehicle type is calculated through a second preset algorithm.

[0018] Further, after the target positioning parameter of the target mobile terminal corresponding to the target vehicle type is determined through the preset algorithm according to the positioning device data, the vehicle-mounted Bluetooth positioning parameter processing method further comprises:

[0019] The target positioning parameter of the target mobile terminal corresponding to the target vehicle type is saved into a cloud database.

[0020] When a positioning parameter query request of a vehicle factory server is acquired, the positioning parameter corresponding to the positioning parameter query request is searched from the cloud database.

[0021] The searched positioning parameter is sent to the vehicle factory server, so that the vehicle factory server sends the searched positioning parameter to a corresponding vehicle.

[0022] Further, the vehicle-mounted Bluetooth positioning parameter processing method further comprises:

[0023] When the preset algorithm is iteratively updated, each positioning parameter stored in the cloud database is updated based on the updated preset algorithm.

[0024] In a second aspect, an embodiment of the present application further provides a vehicle-mounted Bluetooth positioning parameter processing device, comprising:

[0025] An acquisition module is configured to acquire positioning device data corresponding to a target vehicle type, wherein the positioning device data comprises Bluetooth information corresponding to a target mobile terminal to be processed, and Bluetooth information corresponding to a reference mobile terminal and a reference positioning parameter corresponding to the target vehicle type, and the Bluetooth information comprises base signal strength data.

[0026] A determination module is configured to determine a target positioning parameter of the target mobile terminal corresponding to the target vehicle type through a preset algorithm according to the positioning device data.

[0027] In a third aspect, an embodiment of the present application further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program capable of running on the processor, and the processor implements the vehicle-mounted Bluetooth positioning parameter processing method of the first aspect when executing the computer program.

[0028] In a fourth aspect, the embodiments of the present application further provide a storage medium, which has a computer program stored thereon, and the computer program, when executed by a processor, performs the vehicle-mounted Bluetooth positioning parameter processing method in the first aspect.

[0029] The vehicle-mounted Bluetooth positioning parameter processing method, device, electronic equipment and storage medium provided by the embodiments of the present application can automatically determine the target positioning parameter corresponding to the target mobile terminal which has not been calibrated by a preset algorithm based on the positioning device data corresponding to the target vehicle model, wherein the positioning device data includes the Bluetooth information corresponding to the target mobile terminal, and the Bluetooth information corresponding to the calibrated reference mobile terminal and the reference positioning parameter corresponding to the target vehicle model, that is, the target vehicle model is calibrated for a limited number of times, such as only one or two mobile terminals, and the preset algorithm can be used to match other mobile terminals, thereby greatly reducing the calibration workload and calibration cost of the vehicle-mounted Bluetooth positioning parameter. BRIEF DESCRIPTION OF DRAWINGS

[0030] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings needed in the specific embodiments or the prior art description will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can also obtain other drawings according to these drawings without creative labor.

[0031] Figure 1 A calibration diagram between a mobile phone model and a vehicle model in the prior art;

[0032] Figure 2 A calibration diagram between a mobile phone model and a vehicle model provided by the embodiments of the present application;

[0033] Figure 3 A flowchart of a vehicle-mounted Bluetooth positioning parameter processing method provided by the embodiments of the present application;

[0034] Figure 4 A flowchart of another vehicle-mounted Bluetooth positioning parameter processing method provided by the embodiments of the present application;

[0035] Figure 5 A flowchart of a positioning parameter query service provided by the embodiments of the present application;

[0036] Figure 6 A structural diagram of a vehicle-mounted Bluetooth positioning parameter processing device provided by the embodiments of the present application;

[0037] Figure 7 A structural diagram of an electronic equipment provided by the embodiments of the present application. DETAILED DESCRIPTION

[0038] The technical solutions of the present application will be described clearly and completely in combination with the embodiments. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0039] Currently, each vehicle model needs to be calibrated for all mobile phones, such as Figure 1 As shown, for 3 mobile phone models (i.e. 3 mobile phones) and 2 vehicle models (i.e. 2 vehicle models), the calibration times are 3*2=6 times. With the increase of mobile phone and vehicle models, the calibration times will be more and more. How to reduce the cost of calibration is a direction that vehicle enterprises pay great attention to. Based on this, the present application provides a vehicle-mounted Bluetooth positioning parameter processing method, device, electronic equipment and storage medium. By collecting the Bluetooth information of all mobile phone (including wearable devices such as smart watches, smart glasses, etc. which can be used as a car Bluetooth digital key) device models on the market in a big data way, the calibration of all mobile phone models is not required when the vehicle uses the Bluetooth key, and the user can be provided with the optimal user experience of the currently used mobile phone device, which can save the calibration workload of the vehicle-mounted Bluetooth non-inductive positioning, thereby reducing the calibration cost.

[0040] As shown in Figure 2 The present application aims to establish a mobile phone full database to calibrate a limited number of times (such as one or two mobile phone models for one vehicle model), and then use an algorithm to match other mobile phone models and provide a query service of the positioning parameters corresponding to each mobile phone model, so as to achieve the effect of exponentially reducing the calibration cost. Assuming that the vehicle has M models, the cost curve changes from exponential to linear: M or 2*M times. In order to facilitate the understanding of the present application, first, a vehicle-mounted Bluetooth positioning parameter processing method is described in detail.

[0041] The present application provides a vehicle-mounted Bluetooth positioning parameter processing method, which can be executed by an electronic equipment with data processing capability, which can be a cloud server. Referring to Figure 3 As shown in a flowchart of a vehicle-mounted Bluetooth positioning parameter processing method, the method mainly includes the following steps S302-S304:

[0042] In step S302, the positioning device data corresponding to the target vehicle model is obtained, which includes the Bluetooth information corresponding to the target mobile terminal to be processed, the Bluetooth information corresponding to the calibrated reference mobile terminal, and the reference positioning parameters corresponding to the target vehicle model.

[0043] The target mobile terminal is a mobile terminal that has not been calibrated, and the target mobile terminal can be one or more; the reference mobile terminal is a mobile terminal that has been calibrated, and the reference mobile terminal can be one or two or a smaller number of mobile terminals. In the embodiments of the present application, the mobile terminal can be, but is not limited to, a mobile phone. In other embodiments, the mobile terminal can also be a smart watch, smart glasses, etc. For the convenience of understanding, the mobile phone is taken as an example for description in the following.

[0044] The Bluetooth information includes basic signal strength data, and can also include device antenna position and device basic information. The basic signal strength data can include RSSI values of a plurality of preset directions, for example, the basic signal strength of the mobile phone includes signal strengths in six directions (front, back, left, right, up, and down) of the mobile phone one meter away from the mobile phone in an open location, and the signal strengths in oblique directions (for example, left front, right front, left back, right back, left up, right up, left down, and right down) can also be added. The device antenna position includes the antenna position of the mobile phone, which can be abstracted as upper, middle, and lower. The device basic information includes mobile phone basic information, such as mobile phone brand, model, Bluetooth protocol version, mobile phone ROM (Read-Only Memory) version, Bluetooth protocol stack version, etc.

[0045] In order to facilitate the acquisition of Bluetooth information of the mobile terminal, in some possible embodiments, a Bluetooth fingerprint database can be established, in which the Bluetooth information of all mobile terminals is stored. For example, the Bluetooth information of all mobile phones on the market can be acquired by an artificial testing method to establish a mobile phone Bluetooth fingerprint database, and the accuracy of the basic signal strength data can be improved by a plurality of testing collection methods. The Bluetooth fingerprint database is continuously updated with the online of new models (i.e., new mobile terminals). Based on this, the Bluetooth information corresponding to the target mobile terminal and the Bluetooth information corresponding to the reference mobile terminal can be acquired from the Bluetooth fingerprint database established in advance; the Bluetooth fingerprint database stores the Bluetooth information corresponding to each mobile terminal, and the Bluetooth fingerprint database is continuously updated with the online of new mobile terminals.

[0046] The benchmark mobile terminal corresponding to the benchmark positioning parameter of the target vehicle model is obtained by pre-calibration. Since the deployment position and number of Bluetooth modules of different vehicle models and the size and material of the vehicle are different, the first calibration test of the benchmark mobile terminal needs to be performed for different vehicle models to calibrate the universal algorithm for verifying the position of the mobile terminal. The specific verification algorithm of the vehicle end is not limited in the embodiment of the application, for example, the single Bluetooth node scheme of the vehicle end, the one master and one slave Bluetooth node scheme, the one master and three slave node scheme, and the one master and four slave node scheme. The algorithm logic is that when the mobile phone and the master node of the vehicle establish a connection, the master node and the slave node can obtain the signal strength transmitted by the mobile phone end, and then the relative position of the mobile phone and the vehicle is judged according to the signal strength obtained by each node. After calibration, the benchmark mobile terminal corresponding to the benchmark positioning parameter of each vehicle model can be obtained, and the benchmark positioning parameter is, for example, a set of positioning parameters for the optimal user experience of the current mobile phone (the positioning parameter is a set of combinations of RSSI).

[0047] In step S304, the target positioning parameter corresponding to the target vehicle model of the target mobile terminal is determined by a preset algorithm according to the positioning device data.

[0048] The target positioning parameter corresponding to the target vehicle model of the target mobile terminal is calculated based on the benchmark positioning parameter corresponding to the target vehicle model of the benchmark mobile terminal, and the Bluetooth information comparison between the target mobile terminal and the benchmark mobile terminal is performed during the calculation. For example, the difference between the basic signal strength data of the calibration mobile phone (i.e. the benchmark mobile terminal) and the mobile phone of other models (i.e. the target mobile terminal) is compared, and the optimal positioning parameter of the mobile phone of other models is calculated by a preset algorithm. The preset algorithm can be iteratively optimized, and the specific setting can be performed according to the actual demand, which is not limited here.

[0049] The embodiment of the application provides two preset algorithms, which will be specifically introduced as follows.

[0050] The first preset algorithm is as follows:

[0051] Each vehicle model is calibrated with two mobile terminals to obtain two sets of positioning parameters, and a linear method is used to predict the positioning parameters of other mobile terminals. The basic signal strength data used in the prediction can be regarded as a multi-dimensional vector, and the dimension of the vector is equal to the number of preset directions. For example, the basic signal strength data includes the RSSI values in six directions of the mobile phone, and the basic signal strength data can be regarded as a six-dimensional vector (i.e. a matrix with only one column). The algorithm uses the signal strength of the mobile phone in six directions to form a numerical value, and considers that the relationship between the basic signal strength data and the optimal positioning parameter obtained by calibration is an approximately linear relationship within a certain range. Preferably, the two mobile terminals calibrated are the mobile terminal with the best signal strength and the mobile terminal with the worst signal strength in the Bluetooth fingerprint database.

[0052] Based on this, the above-mentioned reference mobile terminal includes a first mobile terminal and a second mobile terminal, the basic signal strength data includes a basic signal strength matrix composed of RSSI values of a plurality of preset directions, and the step S304 can be implemented by the following process: according to the basic signal strength matrix corresponding to the target mobile terminal, the basic signal strength matrix corresponding to the first mobile terminal, and the reference positioning parameter corresponding to the target vehicle type, and the basic signal strength matrix corresponding to the second mobile terminal and the reference positioning parameter corresponding to the target vehicle type, the target positioning parameter of the target mobile terminal corresponding to the target vehicle type is calculated by the first preset algorithm.

[0053] Optionally, the first preset algorithm can adopt the following formula:

[0054]

[0055] Wherein, M xi represents the target positioning parameter of the target mobile terminal x corresponding to the target vehicle type i, ABS represents taking absolute value, M ai represents the reference positioning parameter of the first mobile terminal a corresponding to the target vehicle type i, M bi represents the reference positioning parameter of the second mobile terminal b corresponding to the target vehicle type i, || represents taking the modulus of the matrix, N a represents the basic signal strength matrix corresponding to the first mobile terminal a, N b represents the basic signal strength matrix corresponding to the first mobile terminal b, N x represents the basic signal strength matrix corresponding to the target mobile terminal x.

[0056] The above-mentioned first preset algorithm has the advantages of small calculation amount and fast processing speed.

[0057] The second preset algorithm is:

[0058] The weight of each preset method of the mobile terminal can be set according to the habit of the user (for example, the user generally holds the mobile phone and walks to the vehicle, so the weight of the signal strength of the head direction of the mobile phone is higher than that of the bottom direction), and the specific position of the Bluetooth anchor point of the specific vehicle (for example, the anchor point is deployed at the door and the tail, and the requirement for the strength of the signal also affects the weight of the 6 dimensions of the mobile phone), and then the positioning parameter of each mobile terminal which has not been calibrated is determined.

[0059] Based on this, the positioning device data of the above also includes the Bluetooth anchor point position of the target vehicle model, the Bluetooth information also includes the device antenna position, the basic signal strength data includes a basic signal strength matrix composed of RSSI values of multiple preset directions, and the step S304 can be realized by the following process: determining the weight value of each preset direction according to the device antenna position corresponding to the target mobile terminal and the Bluetooth anchor point position of the target vehicle model; and calculating the target positioning parameter corresponding to the target vehicle model of the target mobile terminal by the second preset algorithm according to the weight value of each preset direction, the basic signal strength matrix corresponding to the target mobile terminal, and the basic signal strength matrix corresponding to the reference mobile terminal and the reference positioning parameter corresponding to the target vehicle model. The specific calculation formula of the second preset algorithm is not limited in the embodiment of the application.

[0060] The second preset algorithm has the advantage of being closer to the use habits of users.

[0061] It should be noted that the specific calculation formula corresponding to the first preset algorithm and the second preset algorithm can be continuously iteratively optimized.

[0062] The vehicle-mounted Bluetooth positioning parameter processing method provided by the embodiment of the application can automatically determine the target positioning parameter corresponding to the target mobile terminal which has not been calibrated by a preset algorithm based on the positioning device data corresponding to the target vehicle model, wherein the positioning device data includes the Bluetooth information corresponding to the target mobile terminal and the Bluetooth information corresponding to the reference mobile terminal which has been calibrated and the reference positioning parameter corresponding to the target vehicle model, that is, the target vehicle model is calibrated only a limited number of times, such as only one or two mobile terminals, and the preset algorithm can be used to match other mobile terminals, thereby greatly reducing the calibration workload and calibration cost of the vehicle-mounted Bluetooth positioning parameter.

[0063] Further, the embodiment of the application also provides a cloud-based positioning parameter query service, and based on this, the method further includes: saving the target positioning parameter corresponding to the target vehicle model of the target mobile terminal into a cloud database; when a positioning parameter query request of a vehicle factory server is acquired, searching for the positioning parameter corresponding to the positioning parameter query request from the cloud database; and sending the searched positioning parameter to the vehicle factory server, so that the vehicle factory server sends the searched positioning parameter to the corresponding vehicle. The vehicle factory server can directly send the searched positioning parameter to the corresponding vehicle, or can send the searched positioning parameter to the corresponding vehicle through the transfer of a mobile terminal such as a mobile phone.

[0064] For example, for a certain vehicle model, a positioning parameter query service for all mobile phone models and ROM version numbers is provided, so that the vehicle can use the latest positioning parameter to provide the user with the best user experience in real time.

[0065] Since the cloud database is saved in the cloud, the preset algorithm can be continuously iterated and optimized in the future, and after iteration and optimization, the optimal positioning parameter of each mobile terminal in each vehicle model in the cloud database can be updated in real time and take effect in real time. Based on this, the above method further comprises: when the preset algorithm is iterated and updated, the various positioning parameters stored in the cloud database are updated based on the updated preset algorithm.

[0066] Further, after the positioning parameters in the cloud database are updated, a reminder message can also be sent to the corresponding vehicle factory server, so that the vehicle can use the latest positioning parameters to provide the user with the best user experience as soon as possible.

[0067] For ease of understanding, taking a mobile phone as an example, the embodiment of the application further provides another vehicle-mounted Bluetooth positioning parameter processing method as shown in Figure 4 The specific process is as follows:

[0068] 1. New mobile phone model test storage.

[0069] After the new mobile phone model tests the basic signal strength data in the Bluetooth information, the Bluetooth information is saved to the mobile phone Bluetooth fingerprint database.

[0070] 2. New vehicle model calibration standard parameter storage.

[0071] The standard parameters (i.e. reference positioning parameters) obtained after the new vehicle model is calibrated are saved to the cloud database.

[0072] 3. Calculate the parameters of all mobile phones according to each vehicle model.

[0073] For each vehicle model, the positioning parameters corresponding to all mobile phones are calculated.

[0074] 4. Continuously update the mobile phone model.

[0075] 5. Provide a query service for vehicles.

[0076] Based on the cloud database, a mobile phone & vehicle model calibration parameter query service (i.e. positioning parameter query service) is provided.

[0077] For ease of understanding, the following refers to Figure 5 The above positioning parameter query service is exemplarily introduced. As shown in Figure 5As shown, the vehicle digital key service (which can be provided by a vehicle factory server) can request the cloud query service (which can be provided by a cloud server) to query the optimal parameters of a certain vehicle model and a certain mobile phone model; the cloud query service can query the vehicle mobile phone optimal parameter database and return the found parameters to the vehicle digital key service; the vehicle digital key service can send the parameters to the vehicle through the Internet of Vehicles, or the vehicle digital key service can send the parameters to the mobile phone. The mobile phone forwards the parameters to the vehicle.

[0078] In summary, the vehicle-mounted Bluetooth positioning parameter processing method provided by the embodiments of the present application has the following advantages:

[0079] 1. Using big data, the manual calibration workload is reduced, greatly reducing the calibration cost;

[0080] 2. If the mobile phone changes the Bluetooth transmission parameters due to ROM update, the positioning parameters can also be distinguished according to different ROM versions;

[0081] 3. The scheme is universal. In addition to being used in vehicle digital key positioning, it can also be promoted to other fields, such as indoor positioning;

[0082] 4. The database can be continuously updated, and the algorithm can be continuously optimized. In the future, more signal influencing factors can be explored, a more optimized mathematical model can be established, and after optimization, it can be applied to supported vehicles in real time to provide users with a high-quality update experience.

[0083] Corresponding to the above-mentioned vehicle-mounted Bluetooth positioning parameter processing method, the embodiments of the present application also provide a vehicle-mounted Bluetooth positioning parameter processing device, which is described with reference to Figure 6 As shown in a structural schematic diagram of a vehicle-mounted Bluetooth positioning parameter processing device, the device comprises:

[0084] The acquisition module 601 is configured to acquire positioning device data corresponding to a target vehicle model, the positioning device data comprising Bluetooth information corresponding to a target mobile terminal to be processed, Bluetooth information corresponding to a calibrated reference mobile terminal, and reference positioning parameters corresponding to the target vehicle model, the Bluetooth information comprising basic signal strength data.

[0085] The determination module 602 is configured to determine target positioning parameters corresponding to the target mobile terminal and the target vehicle model by a preset algorithm according to the positioning device data.

[0086] Further, the acquisition module 601 is specifically configured to acquire the Bluetooth information corresponding to the target mobile terminal from a pre-established Bluetooth fingerprint database; wherein the Bluetooth fingerprint database stores Bluetooth information corresponding to each mobile terminal.

[0087] In some possible embodiments, the reference mobile terminal includes a first mobile terminal and a second mobile terminal, and the basic signal strength data includes a basic signal strength matrix composed of RSSI values of a plurality of preset directions; and the determining module 602 is specifically configured to: according to the basic signal strength matrix corresponding to the target mobile terminal, the basic signal strength matrix corresponding to the first mobile terminal, the reference positioning parameter corresponding to the target vehicle model, the basic signal strength matrix corresponding to the second mobile terminal, and the reference positioning parameter corresponding to the target vehicle model, calculate the target positioning parameter corresponding to the target vehicle model of the target mobile terminal by using a first preset algorithm.

[0088] Further, the first preset algorithm includes the following formula:

[0089]

[0090] wherein, M xi represents the target positioning parameter corresponding to the target vehicle model i of the target mobile terminal x, ABS represents taking an absolute value, M ai represents the reference positioning parameter corresponding to the target vehicle model i of the first mobile terminal a, M bi represents the reference positioning parameter corresponding to the target vehicle model i of the second mobile terminal b, || represents taking a matrix norm, N a represents the basic signal strength matrix corresponding to the first mobile terminal a, N b represents the basic signal strength matrix corresponding to the first mobile terminal b, N x represents the basic signal strength matrix corresponding to the target mobile terminal x.

[0091] In some possible embodiments, the reference mobile terminal includes a first mobile terminal and a second mobile terminal, and the basic signal strength data includes a basic signal strength matrix composed of RSSI values of a plurality of preset directions; and the determining module 602 is specifically configured to: according to the basic signal strength matrix corresponding to the target mobile terminal, the basic signal strength matrix corresponding to the first mobile terminal, the reference positioning parameter corresponding to the target vehicle model, the basic signal strength matrix corresponding to the second mobile terminal, and the reference positioning parameter corresponding to the target vehicle model, calculate the target positioning parameter corresponding to the target vehicle model of the target mobile terminal by using a first preset algorithm.

[0092] Further, the apparatus further includes:

[0093] The saving module is configured to save the target positioning parameter corresponding to the target vehicle model of the target mobile terminal into a cloud database.

[0094] The query module is configured to, when the positioning parameter query request of the vehicle factory server is acquired, search the cloud database for the positioning parameter corresponding to the positioning parameter query request.

[0095] The sending module is configured to send the searched positioning parameter to the vehicle factory server, so that the vehicle factory server sends the searched positioning parameter to the corresponding vehicle.

[0096] Further, the device further comprises:

[0097] The updating module is configured to, when the preset algorithm is iteratively updated, update each positioning parameter stored in the cloud database based on the updated preset algorithm.

[0098] The vehicle-mounted Bluetooth positioning parameter processing device provided in the embodiment has the same implementation principle and generated technical effects as the vehicle-mounted Bluetooth positioning parameter processing method, and for brevity of description, the part of the vehicle-mounted Bluetooth positioning parameter processing device embodiment not mentioned can refer to the corresponding content in the vehicle-mounted Bluetooth positioning parameter processing method embodiment.

[0099] As shown in Figure 7 The embodiment of the present application provides an electronic device 700, which comprises a processor 701, a memory 702 and a bus, the memory 702 stores a computer program capable of running on the processor 701, the processor 701 and the memory 702 communicate through the bus when the electronic device 700 runs, and the processor 701 executes the computer program to realize the vehicle-mounted Bluetooth positioning parameter processing method.

[0100] Specifically, the memory 702 and the processor 701 can be general memory and processor, which are not specifically limited here.

[0101] The embodiment of the present application further provides a storage medium, which stores a computer program, and the computer program is run by a processor to execute the vehicle-mounted Bluetooth positioning parameter processing method described in the foregoing method embodiment. The storage medium comprises a U disk, a mobile hard disk, a read-only memory (ROM), a RAM, a magnetic disk or an optical disk and various program code storage media.

[0102] In all the examples shown and described herein, any specific value should be interpreted as merely exemplary and not as a limitation, and thus other examples of the example embodiments can have different values.

[0103] The flow diagrams and the block diagrams in the drawings are presented to illustrate the architecture, functionality, and operation of possible implementations of apparatuses, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flow diagrams or block diagrams can represent a module, a segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks can sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flow diagrams, and combinations thereof, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

[0104] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented by other manners. The apparatus embodiments described above are merely illustrative, for example, the division of the modules is merely a logical function division, and actual implementation can have another division manner, and for example, a plurality of modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed ones can be indirect coupling or communication connection through some communication interfaces, devices or modules, and can be electrical, mechanical or other forms.

[0105] The modules described as separate components can or can not be physically separated, and the components shown as modules can or can not be physical modules, i.e., can be located in one place or distributed to a plurality of network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment.

[0106] In addition, the functional modules in each embodiment of the present application can be integrated into a processing module, or each module can exist physically, or two or more modules can be integrated into one module.

[0107] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for processing vehicle-mounted Bluetooth positioning parameters, characterized in that: include: Obtaining positioning device data corresponding to the target vehicle model, the positioning device data including Bluetooth information corresponding to the target mobile terminal to be processed, as well as Bluetooth information corresponding to a calibrated reference mobile terminal and reference positioning parameters corresponding to the target vehicle model, the Bluetooth information including basic signal strength data; Determining target positioning parameters of the target mobile terminal corresponding to the target vehicle type through a preset algorithm based on the positioning device data; When the preset algorithm is the first preset algorithm, the reference mobile terminal includes a first mobile terminal and a second mobile terminal, and the basic signal strength data includes a basic signal strength matrix consisting of RSSI values ​​in multiple preset directions; The determining, based on the positioning device data, target positioning parameters of the target mobile terminal corresponding to the target vehicle model by a preset algorithm includes: According to the basic signal strength matrix corresponding to the target mobile terminal, the basic signal strength matrix corresponding to the first mobile terminal and the benchmark positioning parameters corresponding to the target vehicle model, and the basic signal strength matrix corresponding to the second mobile terminal and the benchmark positioning parameters corresponding to the target vehicle model, the target positioning parameters of the target mobile terminal corresponding to the target vehicle model are calculated by a first preset algorithm.

2. The vehicle-mounted Bluetooth positioning parameter processing method according to claim 1, characterized in that: The step of obtaining positioning device data corresponding to the target vehicle model includes: The Bluetooth information corresponding to the target mobile terminal is obtained from a pre-established Bluetooth fingerprint database; wherein the Bluetooth information corresponding to various mobile terminals is stored in the Bluetooth fingerprint database.

3. The method for processing vehicle-mounted Bluetooth positioning parameters according to claim 1, wherein: The first preset algorithm includes the following formula: ； in, M xi Indicates the target mobile terminal x Corresponding to the target model i The target positioning parameters, ABS Indicates taking the absolute value, M ai Indicates the first mobile terminal a Corresponding to the target model i The reference positioning parameters, M bi Indicates the second mobile terminal b Corresponding to the target model i The reference positioning parameter, | | represents the matrix modulus, N a Indicates the first mobile terminal a The corresponding basic signal strength matrix, N b Indicates the first mobile terminal b The corresponding basic signal strength matrix, N x Indicates the target mobile terminal x The corresponding basic signal strength matrix.

4. The method for processing vehicle-mounted Bluetooth positioning parameters according to claim 1, wherein: When the preset algorithm is the second preset algorithm, the positioning device data further includes the Bluetooth anchor point position of the target vehicle model, the Bluetooth information further includes the device antenna position, and the basic signal strength data includes a basic signal strength matrix composed of RSSI values ​​in multiple preset directions; The determining, based on the positioning device data, target positioning parameters of the target mobile terminal corresponding to the target vehicle model by a preset algorithm includes: Determining a weight value for each of the preset directions according to a device antenna position corresponding to the target mobile terminal and a Bluetooth anchor point position of the target vehicle model; According to the weight values ​​of each of the preset directions, the basic signal strength matrix corresponding to the target mobile terminal, the basic signal strength matrix corresponding to the reference mobile terminal and the reference positioning parameters corresponding to the target vehicle model, the target positioning parameters of the target mobile terminal corresponding to the target vehicle model are calculated by a second preset algorithm.

5. The vehicle-mounted Bluetooth positioning parameter processing method according to claim 1, characterized in that: After determining the target positioning parameters of the target mobile terminal corresponding to the target vehicle model through a preset algorithm based on the positioning device data, the in-vehicle Bluetooth positioning parameter processing method further includes: Saving the target positioning parameters of the target mobile terminal corresponding to the target vehicle model in a cloud database; When a location parameter query request is received from the vehicle manufacturer server, searching the cloud database for location parameters corresponding to the location parameter query request; The found positioning parameters are sent to the vehicle factory server, so that the vehicle factory server sends the found positioning parameters to the corresponding vehicle.

6. The method for processing vehicle-mounted Bluetooth positioning parameters according to claim 5, characterized in that: The vehicle-mounted Bluetooth positioning parameter processing method further includes: When the preset algorithm is iteratively updated, each positioning parameter stored in the cloud database is updated based on the updated preset algorithm.

7. A vehicle-mounted Bluetooth positioning parameter processing device, characterized in that: include: an acquisition module, configured to acquire positioning device data corresponding to a target vehicle model, the positioning device data including Bluetooth information corresponding to a target mobile terminal to be processed, Bluetooth information corresponding to a calibrated reference mobile terminal, and reference positioning parameters corresponding to the target vehicle model, the Bluetooth information including basic signal strength data; A determination module, configured to determine, based on the positioning device data, a target positioning parameter of the target mobile terminal corresponding to the target vehicle model using a preset algorithm; When the preset algorithm is the first preset algorithm, the reference mobile terminal includes a first mobile terminal and a second mobile terminal, and the basic signal strength data includes a basic signal strength matrix composed of RSSI values ​​in multiple preset directions; the determination module is specifically used to: calculate the target positioning parameters of the target mobile terminal corresponding to the target vehicle model through the first preset algorithm according to the basic signal strength matrix corresponding to the target mobile terminal, the basic signal strength matrix corresponding to the first mobile terminal and the benchmark positioning parameters corresponding to the target vehicle model, and the basic signal strength matrix corresponding to the second mobile terminal and the benchmark positioning parameters corresponding to the target vehicle model.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

9. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the vehicle-mounted Bluetooth positioning parameter processing method according to any one of claims 1 to 6 is executed.

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