Position data acquisition method and related device

Abstract

The invention provides a position data acquisition method and a related device, and the method comprises the steps: obtaining measurement data and time data, the measurement data comprises sensor data and wireless signal data, the sensor data is obtained through a sensor arranged on a terminal, and the time data represents the acquisition time of the measurement data; the method comprises the following steps: acquiring position data of a terminal entering a room on the basis of sensor data, acquisition time of the sensor data, outdoor positioning data and acquisition time of the outdoor positioning data, and determining the position of the terminal entering the room on the basis of related information of the outdoor positioning data and the sensor data. The problem that information cannot be timely transmitted to the network under the condition that the communication quality between the terminal and the network becomes poor after the terminal enters the room is avoided, and the timeliness of terminal positioning is enhanced. The accuracy of the outdoor positioning data and the sensor data is high, so that the accuracy of the position data of the terminal entering the room is improved. The sensor data has higher stability, and the positioning requirement of a user can be met in time.

Description

Technical Field

[0001] The present application relates to the field of electronic information technology, and in particular to a method for acquiring location data and a related device. Background Art

[0002] In the field of mobile communications, the network can locate the terminal and obtain the terminal's location data to provide the terminal with positioning-related services.

[0003] However, since the environment in which the terminal is located is changing, the positioning performance between the network and the terminal varies with the environment. For example, in some scenarios, the communication quality between the network and the terminal is poor, and the network cannot obtain the terminal's position in time, resulting in positioning errors and poor timeliness of positioning. The accuracy of positioning between the network and the terminal needs to be improved. Summary of the invention

[0004] The present application provides a method and a related device for obtaining location data to achieve the purpose of obtaining location data with higher accuracy. The disclosed technical solution is as follows: The first aspect of the present application provides a method for obtaining location data, which is applied to an artificial intelligence AI model, and the method includes: obtaining measurement data and time data, the measurement data includes sensor data and wireless signal data, the sensor data is obtained by a sensor set on the terminal, the time data indicates the acquisition time of the measurement data, and based on the sensor data, the acquisition time of the sensor data, the outdoor positioning data, and the acquisition time of the outdoor positioning data, the location data of the terminal entering the room is obtained. In this method, the location of the terminal entering the room is determined based on the relevant information of the outdoor positioning data and the relevant information of the sensor data, so as to avoid the problem of not being able to transmit information with the network in time when the communication quality between the terminal and the network deteriorates after entering the room, and enhance the timeliness of the terminal positioning. In addition, the accuracy of the outdoor positioning data and the sensor data is high, which can further improve the accuracy of the location data of the terminal entering the room. In addition, the sensor data has higher stability (such as the wireless signal in the underground environment is not easy to obtain but the sensor data is easy to obtain), which can meet the user's positioning needs in time.

[0005] In some implementations, obtaining the location data of the terminal entering the room includes: obtaining the location data of the terminal entering the room based on a pedestrian dead reckoning algorithm or a vehicle dead reckoning algorithm, wherein the pedestrian dead reckoning algorithm is determined based on the terminal being in a low-speed moving state, and the vehicle dead reckoning algorithm is determined based on the terminal being in a high-speed moving state, and the terminal being in a low-speed moving state or a high-speed moving state is determined based on acceleration sensor data, or is determined based on navigation data and map data. Selecting a dead reckoning algorithm based on the moving speed of the terminal is conducive to obtaining more accurate location data of entering the room based on the dead reckoning algorithm.

[0006] In some implementations, the interval between the acquisition time of the outdoor positioning data and the first time satisfies the first condition, and the first time is the time when the terminal enters the room. Outdoor positioning data, such as satellite positioning data, has high positioning accuracy, and when the outdoor positioning data is used to derive indoor position data, the closer the acquisition time of the outdoor positioning data is to the time when the terminal enters the room from the outdoor, the higher the accuracy of the derived indoor position data. Therefore, screening the outdoor positioning data based on the acquisition time is conducive to further improving the accuracy of the position data entering the room.

[0007] In some implementations, the outdoor positioning data is obtained based on the wireless signal data, including: the outdoor positioning data is obtained by correcting the first positioning data based on the geographic location coordinates, the first positioning data is obtained based on the wireless signal data, the geographic location coordinates are the coordinates of the exit or entrance, the terminal goes from indoors to outdoors via the exit, and the terminal goes from outdoors to indoors via the entrance. Because the location of the exit or entrance of a building is fixed, therefore, correcting the outdoor positioning data based on the coordinates of the exit or entrance is conducive to reducing the "drift" of satellite positioning data or cellular communication data caused by outdoor obstruction, etc., improving the accuracy of the outdoor positioning data, and further improving the accuracy of the location data of the terminal entering the room.

[0008] In some implementations, the distance between the location represented by the geographic location coordinates and the location represented by the outdoor positioning data is less than or equal to a distance threshold. In the case where a building has multiple exits or entrances, the locations of the exits or entrances are filtered based on the outdoor positioning data, so that the correction of the outdoor positioning data is more accurate.

[0009] In some implementations, the geographic location coordinates are determined based on a driving trajectory, which is obtained based on navigation data of the terminal. The location data of the exit or entrance obtained based on the navigation data is more accurate, making the correction of the outdoor positioning data more accurate.

[0010] In some implementations, the first location data does not meet the accuracy condition, but the outdoor positioning data (i.e., the first location data) obtained based on the wireless signal data meets the accuracy condition and does not need to be corrected, which is beneficial for saving computing resources while ensuring the accuracy of the outdoor positioning data.

[0011] In some implementations, whether a terminal enters a room is determined based on measurement data, so that based on the state of the terminal entering the room from the outdoors, corresponding data and algorithms are used to obtain the location data of the terminal, which is beneficial to improving the accuracy of the location data of the terminal.

[0012] In some implementations, the terminal entering indoors is determined based on at least one of the light intensity reduction being greater than or equal to a first threshold and the quality degradation of the satellite positioning signal being greater than or equal to a second threshold, the light intensity reduction being the reduction of the second light intensity compared to the first light intensity, the second light intensity being represented by the visible light sensor data corresponding to the third time, the first light intensity being represented by the visible light sensor data corresponding to the second time, the quality degradation of the satellite positioning signal being the degradation of the second quality parameter compared to the first quality parameter, the second quality parameter being represented by the satellite positioning data corresponding to the third time, the first quality parameter being represented by the satellite positioning data corresponding to the second time, and the second time being earlier than the third time. In other words, when the GNSS quality is monitored to suddenly deteriorate or even disappear and / or the light is monitored to suddenly dim through the optical sensor, it is determined that the terminal has entered indoors from outdoors. This judgment method makes full use of the differences in wireless signals and sensor data between outdoors and indoors, and has high accuracy and feasibility.

[0013] In some implementations, the terminal entering the room is determined based on sensor data, which includes at least one of visible light sensor data, gyroscope data, acceleration data, and air pressure data. This determination method and the characteristic setting of wireless signals and sensor data when the terminal enters the room from the outdoors, especially when entering the indoor underground, are conducive to accurately identifying this scene.

[0014] In some implementations, the location data of the terminal entering the room is obtained based on the sensor data, the acquisition time of the sensor data, the outdoor positioning data, and the acquisition time of the outdoor positioning data, including: based on the short-range signal data obtained after the terminal enters the room, the credibility of the sensor data, at least one of the credibility of the outdoor positioning data, and the sensor data, the acquisition time of the sensor data, the outdoor positioning data, and the acquisition time of the outdoor positioning data, the location data of the terminal entering the room is obtained. The short-range signal is used as the characteristic data of the indoor environment, and the credibility can be used to filter out the sensor data and outdoor positioning data with higher credibility. These, together with the sensor data, the outdoor positioning data and the acquisition time, are used as the input of the AI ​​model, which is conducive to further improving the accuracy of the location data output by the AI ​​model.

[0015] The second aspect of the present application provides an electronic device, which includes: one or more processors and a memory; the memory is used to store program code; the processor is used to run the program code, so that the electronic device implements the method provided by the first aspect of the present application.

[0016] The third aspect of the present application provides a computer-readable storage medium having instructions stored thereon. When the instructions are executed on an electronic device, the electronic device executes the method provided by the first aspect of the present application.

[0017] The fourth aspect of the present application provides a computer program product having an executable program stored thereon. When the computer program product is run on an electronic device, the electronic device implements the method provided by the first aspect of the present application.

[0018] The fifth aspect of the present application provides a communication device, including: a communication module and a processing module, the communication module is used to obtain measurement data and time data, the measurement data includes sensor data and wireless signal data, the sensor data is obtained through a sensor set on a terminal, the wireless signal data includes at least one of satellite positioning data and cellular communication data, and the time data indicates the acquisition time of the measurement data; the processing module is used to obtain the position data of the terminal entering the room based on the sensor data, the acquisition time of the sensor data, outdoor positioning data, and the acquisition time of the outdoor positioning data, the outdoor positioning data indicates the position data of the terminal outdoors, and the outdoor positioning data is obtained based on the wireless signal data.

[0019] In some implementations, obtaining the position data of the terminal entering the room includes: obtaining the position data of the terminal entering the room based on a pedestrian dead reckoning algorithm or a vehicle dead reckoning algorithm, the pedestrian dead reckoning algorithm is determined based on the terminal being in a low-speed moving state, the vehicle dead reckoning algorithm is determined based on the terminal being in a high-speed moving state, and whether the terminal is in a low-speed moving state or a high-speed moving state is determined based on acceleration sensor data, or is determined based on navigation data and map data.

[0020] In some implementations, an interval between the acquisition time of the outdoor positioning data and a first time satisfies a first condition, and the first time is the time when the terminal enters indoors.

[0021] In some implementations, the outdoor positioning data is obtained based on the wireless signal data, including: the outdoor positioning data is obtained based on the first position data corrected by the geographic location coordinates, the first position data is obtained based on the wireless signal data, the geographic location coordinates are the coordinates of the exit or entrance, the terminal goes from indoors to outdoors via the exit, and the terminal goes from outdoors to indoors via the entrance.

[0022] In some implementations, the distance between the location represented by the geographic location coordinates and the location represented by the outdoor positioning data is less than or equal to a distance threshold.

[0023] In some implementations, the geographic location coordinates are determined based on a driving trajectory, and the driving trajectory is obtained based on navigation data of the terminal.

[0024] In some implementations, the first position data does not satisfy an accuracy condition.

[0025] In some implementations, the terminal entering the indoor space is determined based on at least one of a light intensity reduction amount being greater than or equal to a first threshold and a satellite positioning signal quality degradation amount being greater than or equal to a second threshold, the light intensity reduction amount being a reduction amount of the second light intensity compared to the first light intensity, the second light intensity being represented by visible light sensor data corresponding to a third time, the first light intensity being represented by visible light sensor data corresponding to the second time, the satellite positioning signal quality degradation amount being a degradation amount of a second quality parameter compared to a first quality parameter, the second quality parameter being represented by the satellite positioning data corresponding to the third time, the first quality parameter being represented by the satellite positioning data corresponding to the second time, and the second time being earlier than the third time.

[0026] In some implementations, the terminal entering the room is determined based on the sensor data, and the sensor data includes at least one of visible light sensor data, gyroscope data, acceleration data, and air pressure data.

[0027] In some implementations, the acquiring of the location data of the terminal when it enters the room based on the sensor data, the time of acquiring the sensor data, the outdoor positioning data, and the time of acquiring the outdoor positioning data includes acquiring the location data of the terminal when it enters the room based on at least one of the short-range signal data acquired after the terminal enters the room, the credibility of the sensor data, and the credibility of the outdoor positioning data, as well as the sensor data, the time of acquiring the sensor data, the outdoor positioning data, and the time of acquiring the outdoor positioning data.

[0028] The fifth aspect of the present application provides a chip system, which includes one or more processors for calling and running instructions stored in the memory from the memory, so that the method for obtaining position data provided in the first aspect of the present application is executed. The chip system can be composed of a chip, or it can include a chip and other discrete devices.

[0029] The sixth aspect of the present application provides a communication system, including: a terminal and a network device, the terminal is used to obtain measurement data and time data, the measurement data includes sensor data and wireless signal data, the sensor data is obtained through a sensor set on the terminal, the wireless signal data includes at least one of satellite positioning data and cellular communication data, and the time data indicates the acquisition time of the measurement data; the network device is used to obtain the position data of the terminal entering the room based on the sensor data, the acquisition time of the sensor data, outdoor positioning data, and the acquisition time of the outdoor positioning data, the outdoor positioning data indicates the position data of the terminal outdoors, and the outdoor positioning data is obtained based on the wireless signal data. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0031] Figure 1 This is an example diagram of an application scenario of obtaining location data of a terminal through a network provided in an embodiment of the present application; Figure 2 is an example diagram of the architecture of a communication system for implementing a method for acquiring location data provided in an embodiment of the present application; Figure 3 This is an example diagram of a scenario in which a user carries a terminal from outdoors to indoors; Figure 4 is a flow chart of a method for obtaining location data provided by an embodiment of the present application; Figure 5 is an example diagram of an architecture for obtaining training data provided by an embodiment of the present application; Figure 6 It is an architecture example of a communication system for implementing a method for acquiring location data provided by an embodiment of the present application; Figure 7 is a structural example diagram of a terminal provided in an embodiment of the present application; Figure 8 is a structural example diagram of a communication device provided in an embodiment of the present application; Fig. 9 This is a structural example diagram of a communication device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The terms "first", "second", "third", etc. in the specification, claims and drawings of this application are used to distinguish different objects rather than to limit a specific order.

[0033] In the embodiments of the present application, words such as "in some implementations" or "for example" are used to indicate examples, illustrations or descriptions and should not be interpreted as being more preferred or more advantageous than other embodiments or designs.

[0034] The communication system to which the embodiments of the present application can be applied may be a second generation (2G) communication system, a third generation (3G) communication system, a long term evolution (LTE) system, a fifth generation (5G) communication system, an LTE and 5G hybrid architecture, a 5G new radio (5G NR) system, and new communication systems that may emerge in future communication developments.

[0035] The communication system includes terminals and network equipment. The network equipment includes access network equipment and core network equipment.

[0036] The terminal may be in various forms, for example, a mobile phone, a tablet computer, a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal in industrial control, a vehicle-mounted terminal device, a wireless terminal in self-driving, a wireless terminal in remote medical, a wireless terminal in smart grid, a wireless terminal in transportation safety, a wireless terminal in smart city, a wireless terminal in smart home, a wearable terminal device, etc. The terminal may also be sometimes referred to as a terminal device, a user equipment (UE), an access terminal device, a vehicle-mounted terminal, an industrial control terminal, a UE unit, a UE station, a mobile station, a mobile station, a remote station, a remote terminal device, a mobile device, a UE terminal device, a terminal device, a wireless communication device, a UE agent or a UE device, etc. The terminal may also be a fixed terminal or a mobile terminal.

[0037] The access network equipment includes a base station, which is any device located on the network side and has wireless transceiver functions, including but not limited to: an evolved base station (NodeB or eNB or e-NodeB, evolutionary Node B) in LTE, a base station (gNodeB or gNB) or a transmission receiving point / transmission reception point (TRP) in new radio (NR), a base station of subsequent evolution of 3GPP, an access node in a Wi-Fi system, a wireless relay node, a wireless backhaul node, etc. The base station can be: a macro base station, a micro base station, a micro-micro base station, a small station, a relay station, or a balloon station, etc. The base station can include one or more co-sited or non-co-sited TRPs. The base station can also be a wireless controller, a centralized unit (CU), and / or a distributed unit (DU) in a cloud radio access network (CRAN) scenario. The base station can communicate with the terminal, or communicate with the terminal through a relay station.

[0038] The core network device and the base station can be independent and different physical devices, or the functions of the core network device and the logical functions of the base station can be integrated on the same physical device, or part of the functions of the core network device and part of the functions of the base station can be integrated on one physical device. Figure 1 For example, LMF is run in the core network equipment.

[0039] In the following text, core network equipment and access network equipment are collectively referred to as network equipment.

[0040] Figure 1 This is an example of a process for obtaining the terminal's location data, combined with Figure 1 As shown, the UE obtains wireless local area networks (WLAN) signals, positioning reference signals (PRS) and Bluetooth signals sent by the base station (gNB), and sends wireless signal data to the location management function (LMF) based on the obtained signals. The wireless signal data can be understood as data obtained by parsing or measuring at least one of the WLAN signal, PRS and Bluetooth signal. The LMF module is configured with a position estimation model (or positioning model), and the position estimation model outputs a position estimation result based on the wireless signal data.

[0041] However, since the environment in which the terminal is located is changing, the positioning performance between the network device and the terminal varies with the changes in the environment. For example, in some scenarios, the communication quality between the network device and the terminal is poor, and the terminal cannot obtain the above-mentioned PRS, Bluetooth signals, etc. in time, and may not be able to feedback wireless signal data in time, resulting in the network device being unable to obtain the terminal's position in time, causing positioning errors, and the timeliness of positioning is also poor. Therefore, the accuracy of positioning between the network device and the terminal needs to be improved.

[0042] In view of this, the present application provides a method and related device for acquiring location data to achieve more accurate location data.

[0043] Figure 2 The invention is an example diagram of the architecture of a communication system for implementing a method for acquiring location data.

[0044] Combination Figure 2 The terminal includes: a global navigation satellite system (GNSS) module, a cellular module, a wireless local area network (WLAN) module and a Bluetooth module.

[0045] The GNSS module is used to implement the GNSS positioning function. Specifically, the GNSS module receives signals sent by satellites and obtains GNSS data carried in the signals sent by satellites. GNSS data includes the location data of the terminal obtained based on the GNSS method and the evaluation parameters of the location data. The evaluation parameters represent the accuracy of the location data of the terminal obtained based on the satellite positioning method. Examples of the evaluation parameters are at least one of the horizontal dilution of precision (HDOP) and the carrier-to-noise ratio. GNSS data may also include the number of satellite searches. The GNSS positioning function obtains more accurate terminal location data in an environment with better satellite signals, such as an open outdoor area, while in a relatively closed or severely obstructed environment, such as indoors, the GNSS module may not be able to receive GNSS signals of a quality that meets the positioning requirements. GNSS is an example of satellite positioning and can be replaced by other satellite positioning technologies or used together with other satellite positioning technologies.

[0046] The cellular module is used to implement cellular communication functions. Cellular communication data related to positioning include but are not limited to: PRS, angle-of-arrival (AOA), and timing advance (TA). Taking PRS as an example, the terminal receives PRS sent by access network equipment such as base stations. PRS is used to assist positioning services in mobile communications. PRS that meets positioning requirements may be received indoors or outdoors. The terminal can measure PRS to obtain cellular communication data.

[0047] The WLAN module is used to implement wireless local area network functions such as wireless fidelity (Wi-Fi). The wireless local area network functions related to positioning include but are not limited to: after receiving the Wi-Fi signal sent by the access point (AP), obtaining Wi-Fi data from the Wi-Fi signal, the Wi-Fi data includes AP information, Wi-Fi signal strength, basic service set identified (BSSID), service set identified (SSID), and received signal strength indication (RSSI).

[0048] The Bluetooth module is used to implement Bluetooth functions. Bluetooth functions related to positioning include but are not limited to detecting Bluetooth signals sent by other electronic devices and obtaining Bluetooth data carried in the Bluetooth signals. Bluetooth data includes information about the device sending the Bluetooth signal and the strength of the Bluetooth signal.

[0049] Both WLAN and Bluetooth are short-range communications. Therefore, it is possible that short-range communication data that meets positioning requirements cannot be obtained outdoors.

[0050] The terminal also includes sensors, and the sensors related to the technical solution provided in the embodiments of the present application include but are not limited to: a gyroscope, an accelerometer, a visible light sensor, and a barometer.

[0051] The sensor is used to sense the corresponding environmental data. For example, the gyroscope senses the terminal's posture data, such as the horizontal angle, the accelerometer is used to sense the acceleration data of the terminal, the visible light sensor is used to sense the visible light intensity data of the terminal's environment, and the barometer is used to sense the air pressure value of the terminal's environment.

[0052] In the embodiments of the present application, wireless signal data and sensor data are collectively referred to as measurement data.

[0053] LMF is equipped with an artificial intelligence (AI) model, which is used to implement the positioning function. LMF is also equipped with a scene judgment module to determine the scene of the terminal based on at least one of the wireless signal data and sensor data, that is, indoors, from outdoor to indoor or outdoor. The positioning function of the AI ​​model includes obtaining the terminal's location data using different methods and data for different scenes.

[0054] Figure 2 The various modules in the terminal are only examples and not limitations. For example, the terminal may include Figure 2 More or fewer types of sensors are given as examples. For example, LMF is an example of a network element, and other network elements in the network may also interact with the UE.

[0055] Figure 3 This is a scene example diagram. Figure 3 In the example, it is assumed that a user carries a terminal and travels along a certain path, part of which is outdoors and part of which is indoors. Figure 3 The circles in represent positions on the path, which are position 1 to position 7.

[0056] exist Figure 3 In the scenario shown, Figure 4 is a flowchart of a method for obtaining location data provided in an embodiment of the present application, Figure 4 The following steps are included: S101. The terminal obtains measurement data and time data.

[0057] The measurement data includes wireless signal data and sensor data.

[0058] The wireless signal data is data related to the wireless communication signal. The terminal obtains the wireless signal data by parsing the received wireless signal, or by measuring the received wireless signal, or by parsing and measuring the wireless signal.

[0059] Wireless signal data includes but is not limited to: GNSS data, cellular communication data, Wi-Fi data and Bluetooth data. It is understandable that the terminal Figure 2 The example wireless communication module obtains wireless signal data.

[0060] Combination Figure 3In the scenario shown, it can be understood that when the terminal is outdoors, the terminal can usually obtain GNSS data and cellular communication data that meet the requirements, but may not be able to obtain short-range communication data that meet the requirements, such as Bluetooth data and Wi-Fi data. When the terminal is indoors, the terminal can usually obtain cellular communication data and short-range communication data that meet the requirements, but it is difficult to obtain GNSS data that meets the requirements.

[0061] The sensor data includes but is not limited to: at least one of posture data, acceleration data, visible light intensity data, and air pressure value. Figure 2 The example's sensor acquires sensor data.

[0062] In one way that the terminal acquires data, the terminal acquires data at a preset period. The period at which the terminal acquires wireless signal data may be the same as or different from the period at which the sensor data is acquired. In another way that the terminal acquires data, the terminal acquires data in response to a preset trigger condition, and the condition for acquiring wireless signal data may be the same as or different from the condition for acquiring sensor data. It is understandable that the acquisition period or trigger condition for each type of wireless signal data or each type of sensor data may be the same or different.

[0063] The time data indicates the acquisition time of the measurement data. The acquisition time of the measurement data is the time when the terminal acquires the measurement data. The time data can be a moment value or a time interval.

[0064] It is understandable that different types of data may have different acquisition times. For example, GNSS signals have certain transmission time slots, so the acquisition time of GNSS data is related to the time domain resources for transmitting GNSS signals, and the terminal acquires sensor data collected by the sensor with an inherent period. Therefore, the acquisition time of GNSS data may be different from the acquisition time of certain sensor data. For example, there may be a certain delay.

[0065] S102: The terminal sends measurement data and time data to the network device, and correspondingly, the network device receives the measurement data and time data.

[0066] In some implementations, the terminal filters the data and then sends the filtered data to the network device. Data filtering can be understood as removing data that does not meet the requirements, including but not limited to: positioning requirements, model training requirements, and at least one of data quality requirements. For example, if the strength of the Wi-Fi signal in a piece of Wi-Fi data does not meet the threshold, the Wi-Fi data is deleted.

[0067] In other implementations, in order to reduce the complexity of subsequent data processing, in some implementations, the terminal aligns data with close acquisition times (i.e., the interval between acquisition times does not exceed a preconfigured threshold) to the same time. For example, 18:10:20 and 18:10:22 are aligned to 18:10:22, that is, the acquisition time of the data acquired at 18:10:20 is modified to 18:10:22.

[0068] The above-mentioned screening of data and processing of time data may also be performed by a network device instead of a terminal.

[0069] It is understandable that the terminal may not be able to obtain some data, such as being unable to obtain Wi-Fi data outdoors. In this case, the terminal can send the obtained data and the corresponding time data. Alternatively, the terminal can send data based on a pre-configured content template. All data included in the content template must be sent. For data that is not obtained, the terminal uses a preset value to indicate that the data is not obtained. The content template includes the type of data that the terminal needs the base station to send, such as visible light sensor data, gyroscope data, GNSS data, and wireless cellular data. The type of data included in the content template can be adjusted as needed.

[0070] In some implementations, the network device described in the embodiments of the present application may be a core network device, and the interaction between the terminal and the network device is the interaction between the terminal and a network element in the core network. An example of a network element is Figure 2 LMF in.

[0071] S103. The network device determines, based on the measurement data and the time data, whether the terminal is outdoors, moving from outdoors to indoors, or indoors at the first time.

[0072] It is understandable that the judgment result of the network device may coincide with the real-time location of the terminal, and may not represent the real-time location of the terminal. Therefore, the judgment result obtained in this step represents the result obtained by the network device based on the received data and the time when the data was acquired, and does not necessarily represent the real-time location status of the terminal.

[0073] The opposite state of being outdoors is not outdoors. Not outdoors includes entering indoors from outdoors and being indoors. Entering indoors from outdoors can be referred to as "entering indoors". The first state after entering indoors from outdoors is entering indoors from outdoors. Figure 3 For example, the user carries a terminal and moves from position 2 to position 3, position 4, etc. in chronological order. Position 3 is the first position after entering the room, that is, entering the room from the outdoor. Positions 3 to 7 are indoor positions.

[0074] It is understandable that the embodiments of the present application are not limited to the first position where the terminal enters indoors from outdoors as "entering indoors from outdoors". For example, the position corresponding to "entering indoors from outdoors" can be any position indoors. For another example, the position corresponding to "entering indoors from outdoors" can be a position in the process of moving from outdoors to indoors. In other words, the position corresponding to "entering indoors from outdoors" is not distinguished by the geographical boundary between indoors and outdoors, and can depend on specific application scenarios and needs.

[0075] In some implementations, the GNSS data with the first acquisition time includes a carrier-to-noise ratio and a number of searched satellites. Based on the carrier-to-noise ratio being greater than or equal to a carrier-to-noise ratio threshold and the number of searched satellites being greater than or equal to a number threshold, it is determined that the data indicates that the terminal is outdoors at the first acquisition time.

[0076] In other implementations, the carrier-to-noise ratio of the GNSS data with the second acquisition time is less than the carrier-to-noise ratio threshold, and the number of searched satellites is less than the number threshold, and it is determined that the data indicates that the terminal is indoors at the second acquisition time.

[0077] One way to determine whether the terminal enters indoors from outdoors is to make a determination based on data at different acquisition times (such as adjacent acquisition times) and a comparison result between the data.

[0078] For example: the data with the third acquisition time includes acceleration data, GNSS data and visible light sensor data. Based on the acceleration data, it is determined that the terminal is in a low-speed moving state, such as the user carrying the terminal is in a walking state, and based on the GNSS data with the third acquisition time and the visible light sensor data, it is determined that the terminal is outdoors, that is, based on the data with the third acquisition time, it is determined that the terminal is in a low-speed moving state outdoors.

[0079] The data with the fourth acquisition time includes GNSS data and visible light sensor data, the fourth acquisition time is after the third acquisition time, and in order of the acquisition time from first to last, the previous data of the data with the fourth acquisition time is the data with the third acquisition time. Compared with the visible light sensor data with the third acquisition time, the visible light sensor data with the fourth acquisition time represents a decrease in light intensity greater than or equal to a first threshold, that is, the quality of the GNSS signal has significantly decreased, and compared with the GNSS data with the third acquisition time, the GNSS data with the fourth acquisition time represents a quality degradation of the GNSS signal greater than or equal to a second threshold, that is, the light intensity has significantly decreased, then it is determined that the terminal has entered indoors from outdoors.

[0080] The terminal is in a low-speed moving state outdoors, and the changes between the successively collected data are relatively slow, so judging whether the terminal has entered the room by successively acquired data has a high accuracy. However, whether the terminal is in a low-speed moving state is not a prerequisite for the above method of judging whether the terminal has entered the room from the outdoors, that is, before judging whether the terminal has entered the room from the outdoors, it is not necessary to judge whether the terminal is in a low-speed moving state.

[0081] For another example, the data with the third acquisition time and the data with the fourth acquisition time both include acceleration data, posture data, and air pressure data. Based on the acceleration data acquired at multiple different times, it is determined that the terminal is in a high-speed moving state (such as a driving state), and based on the posture data and air pressure data acquired at multiple different times, it is determined that the terminal is in a downward driving state. It can also be combined with at least one of the visible light sensor data and GNSS data to determine that the terminal is not outdoors, and then it is determined that the terminal is in a state of entering indoors such as an underground parking lot. Similarly, determining that the terminal is in a high-speed moving state is an optional step.

[0082] Regardless of which judgment method is used or which judgment result is obtained, the first time is determined based on the acquisition time of the data used as the basis for judgment: for example, the first time is the acquisition time of the data used as the basis for judgment, or for example, the first time is obtained based on the acquisition time of the data used as the basis for judgment.

[0083] Combination Figure 3 For example, LMF determines that the terminal is outdoors based on the data obtained by the terminal near position 2, and takes the time when the data is obtained near position 2 (assuming that the acquisition time of the data obtained near position 2 is aligned, referred to as the time corresponding to position 2) as the first time. For another example, LMF determines that the terminal enters indoors from outdoors at the first time between the time corresponding to position 2 and the time corresponding to position 3 based on the data obtained by the terminal near position 2 and position 3.

[0084] Combination Figure 3 , the position from outdoor to indoor refers to the first position after entering indoors from outdoor, such as Figure 3 Position 3 in .

[0085] When it is determined that the terminal is outdoors, S104 is executed.

[0086] When it is determined that the terminal is moving from outdoor to indoor, in this embodiment, based on the sensor data and its acquisition time, as well as the last GNSS coordinates acquired outdoors and its acquisition time, the location coordinates of the terminal after moving from outdoor to indoor are derived, that is, S105-S106 are executed.

[0087] When it is determined that the terminal is already indoors, the position coordinates of the terminal indoors are derived using a correction method for the short-range positioning result, as in S107.

[0088] S104. The network device obtains the outdoor position coordinates of the terminal at the first time based on the GNSS data corresponding to the first time.

[0089] As mentioned above, GNSS data is satellite positioning data, including the location coordinates of the terminal acquired by satellite positioning. Therefore, one example is to use the location coordinates in the GNSS data corresponding to the first time as the location coordinates of the terminal.

[0090] The GNSS coordinates corresponding to the first time may be GNSS coordinates acquired at the first time, or may be GNSS coordinates acquired at a time close to the first time (ie, the interval with the first time is within a preset range).

[0091] S105. The network device determines the starting coordinates based on the GNSS coordinates acquired before the first time.

[0092] In this embodiment, the GNSS coordinates acquired by the terminal outdoors are used as the starting coordinates for deriving the indoor position coordinates.

[0093] Combination Figure 3 As shown, both position 1 and position 2 are outdoors and can be used as starting coordinates, but it is understandable that the closer the distance to the indoors, the more accurate the derivation result may be. Therefore, in this embodiment, position 2 is used as the derivation starting position. Position 2 is the position represented by the last GNSS data obtained before the terminal enters the indoors.

[0094] A specific way to find the starting coordinates is to find the coordinates of the last outdoor location of the terminal before it enters the outdoor location from the indoor location, that is, in the GNSS coordinates indicating that the terminal is outdoor, find the GNSS coordinates whose interval between the acquisition time and the first time satisfies the first condition, and the first condition is less than or equal to a preset interval threshold, or within a preset range. The first condition can be configured as needed, combined with Figure 3 , assuming that position 3 corresponds to the first time, the interval between the time when the data is obtained at position 2 and the first time is less than or equal to the interval threshold, so the GNSS coordinates obtained at position 2 are used as the starting coordinates. It is understandable that the accuracy of the GNSS coordinates at position 2 may be insufficient. In this case, other outdoor position coordinates may be selected, such as the GNSS coordinates at position 1. The interval threshold may be pre-configured.

[0095] It is understandable that GNSS coordinates may not be accurate enough, for example, Figure 3Position 2 in the figure is near buildings such as bridges, which reduces the accuracy of GNSS positioning and causes "drift" of GNSS coordinates. Therefore, in order to improve the accuracy of GNSS coordinates and improve the accuracy of subsequent indoor position derivation results, in some implementations, if the accuracy of the GNSS coordinates used to derive the starting coordinates of the indoor position does not meet the accuracy condition, the starting coordinates are corrected. The accuracy condition is that the GNSS evaluation data does not meet the preset accuracy threshold. It can be understood that the accuracy of the GNSS coordinates not meeting the accuracy condition is an optional step, and the accuracy can be directly corrected without determining it.

[0096] One way to correct the GNSS coordinates is to obtain the coordinates of the entrance and correct the GNSS coordinates based on the coordinates of the entrance, such as Figure 3 For example, a user needs to pass through an entrance to carry a terminal from outdoors to indoors, and the entrance coordinates are relatively fixed, so the GNSS coordinates can be corrected. LMF can obtain the entrance coordinates by calling a map or other means.

[0097] It is understandable that the building that the terminal enters may have multiple entrances. In this case, one way is to use the GNSS coordinates as the starting coordinates to select an entrance coordinate from the multiple entrance coordinates, for example, select the entrance coordinates closest to the GNSS coordinates as the starting coordinates, and then correct the GNSS coordinates as the starting coordinates based on the selected entrance coordinates. Another way is to obtain navigation data from the terminal, obtain the driving trajectory of the terminal based on the navigation data, and determine the coordinates of the entrance of the terminal entering the building based on the driving trajectory. Generally, navigation data includes map data and driving trajectory data.

[0098] S106. The network device obtains the position coordinates of the terminal entering the room at the first time based on the starting coordinates, the time when the starting coordinates are obtained, the sensor data, and the time when the sensor data is obtained.

[0099] In some implementations, if the terminal is determined to be in a low-speed moving state, the network device calls the pedestrian dead reckoning (PDR) algorithm based on the starting coordinates, the acquisition time corresponding to the starting coordinates, the posture data from the gyroscope, the acceleration data from the accelerometer and other sensor data and the corresponding acquisition time to obtain the position coordinates at the first time. Or if the terminal is determined to be in a high-speed moving state, the network device calls the vehicle dead reckoning (VDR) algorithm to obtain the position coordinates at the first time. It can be understood that the position coordinates at the first time are the position coordinates of the terminal when it enters the indoor state from the outdoor.

[0100] Based on the different states of the terminal: low-speed mobile state (such as the user carrying the terminal on foot) or high-speed mobile state (such as driving), determining (or selecting) the corresponding algorithm is conducive to obtaining more accurate location coordinates of entering the room.

[0101] In addition to the aforementioned methods, such as determining that the terminal is in a low-speed moving state or a high-speed moving state based on acceleration data, other methods can also be used to determine, such as obtaining a moving trajectory based on navigation data, and then combining the road information and moving trajectory represented by map data to obtain the location data of the entrance from indoors to indoors, and determining walking or driving based on the type of pre-configured entrance represented by the map data. If the entrance type is a garage entrance, driving is determined, otherwise walking is determined. For another example, the terminal can also be determined to be in a downward moving state at a relatively high speed, that is, a high-speed moving state, based on the posture data collected by the gyroscope, combined with the acceleration data and the air pressure data collected by the barometer.

[0102] It can be understood that, in combination with the first time described in S103, the data used as a basis for determining whether the terminal is in a low-speed moving state or a high-speed moving state is data acquired before the first time.

[0103] In addition, the step of determining whether the terminal is in a low-speed moving state or a high-speed moving state can be performed in S103 as described above, and can also be performed before S106 when it is determined that the terminal is in a state of moving from outdoor to indoor.

[0104] In some implementations, in addition to the starting coordinates, the time of obtaining the starting coordinates, the sensor data, and the time of obtaining the sensor data as the input data of the AI ​​model, at least one of the short-range signal data obtained at the first time, the credibility of the sensor data, and the credibility of the outdoor positioning data (such as outdoor GNSS data) will also be used as the network device to obtain the location coordinates of the terminal entering the indoor space at the first time, so as to further improve the accuracy of the obtained terminal location data.

[0105] S107. The network device obtains the indoor position coordinates of the terminal at the first time by correcting the short-range signal positioning result.

[0106] Combination Figure 3 As shown, position 3 is the state of entering indoors from outdoor, and positions 4 to 7 are all indoors. In this step, obtaining the coordinates of position 4 is taken as an example.

[0107] Use short-range signal positioning to obtain indoor position coordinates. Short-range signal positioning methods include but are not limited to at least one of Wi-Fi data and Bluetooth data, and obtain the indoor position coordinates of the terminal through a triangulation positioning algorithm or a fingerprint matching algorithm. For example, the triangulation positioning algorithm is based on the Wi-Fi data generated by the signals of at least three access points at one location, and the position coordinates of at least three access points, to obtain the coordinates of this location. For another example, a fingerprint library of various indoor locations is pre-established, and the fingerprint library includes fingerprints of multiple locations. The fingerprint of any location includes the Bluetooth data features and coordinates of the location. When positioning based on the fingerprint library, the Bluetooth features of the location to be located are matched with the Bluetooth data features in the fingerprint library, and a matching fingerprint is found. Then, based on the coordinates included in the matching fingerprint, the coordinates of the location to be located are obtained.

[0108] Combination Figure 3 In the scenario shown, during the movement of the terminal, if it is already at position 4 or later, it means that the terminal has passed position 3. Therefore, in order to improve the accuracy of the short-range signal positioning result, the offset is used to correct the short-range signal positioning result, that is, based on the sensor data (which may also include wireless signal data) and its acquisition time, the position offset from position 3 to position 4 is calculated, and then the position offset and the short-range signal positioning result are used to obtain a new short-range signal positioning result. This method can improve the accuracy of the short-range signal positioning result.

[0109] In some implementations, S104-S108 are implemented by a network device calling an AI model.

[0110] In the method for obtaining location data provided in this embodiment, the network device distinguishes between situations where the terminal is outdoors, entering indoors from outdoors, and is indoors, uses different data based on different situations, and calls different algorithms based on different moving speeds to obtain the location data of the terminal, which is beneficial to improving the accuracy of the obtained location data.

[0111] For example, when entering indoors from outdoors, the GNSS coordinates outdoors before entering indoors are used as the starting coordinates for deriving the position coordinates after entering indoors. Combined with the sensor data and corresponding time data obtained by the terminal, and an algorithm matching the terminal's moving speed, the network device obtains the position coordinates of the terminal after entering indoors. Compared with the method of obtaining indoor position coordinates based on short-range signals, on the one hand, the accuracy of outdoor GNSS coordinates is higher, and therefore can lay a good foundation for obtaining accurate indoor position coordinates. On the other hand, compared with short-range signals, sensor data is more stable, which improves the reliability of obtaining indoor position coordinates.

[0112] Especially for scenarios such as underground parking lots where the quality of short-range signals, cellular communication signals, and satellite positioning signals are all poor, in this embodiment, the network device obtains indoor location coordinates based on outdoor coordinates and corresponding time, sensor data, and acquisition time, which is conducive to obtaining more accurate location data in such scenarios.

[0113] The above is a detailed description of the process of interaction between the terminal and the network device. It is understandable that the data processing method in the previous article can also be applied to the training of AI models. The following is an introduction.

[0114] In order to make the AI ​​model output more accurate location data, it is necessary to train the AI ​​model with labeled data. The following is a detailed description of the AI ​​model training process.

[0115] The difficulty in training AI models at present is that it is difficult to obtain sufficient and accurate location tags. For example, the quality of wireless signals in some scenarios is not enough to support the acquisition of location tags, such as underground parking lots. Whether it is WLAN, gNB or Bluetooth, the signal quality is relatively poor, so location tags cannot be obtained. For another example, in indoor scenarios, the current positioning method based on short-range signals such as WLAN or Bluetooth is generally based on triangulation positioning or fingerprint positioning. Triangulation positioning usually requires the location data of known access points, and fingerprint positioning requires a large amount of fingerprint library data, so it is difficult to obtain enough location tags.

[0116] The embodiment of the present application also provides a method for training an AI model. Figure 5 For example: The training data set includes multiple training data, and any training data includes location labels and feature data. The training data in the training data set is input into the AI ​​model, and the AI ​​model obtains the location data based on the feature data in the input training data, and adjusts the parameters of the AI ​​model based on the location data and the location labels in the training data until the training is completed.

[0117] The training data in the training data set is obtained as follows Figure 5 As shown: the terminal obtains measurement data and time data through the wireless communication module and the sensor, see S101 for details, the terminal sends the measurement data and time data to the network device such as LMF, and the network device such as LMF receives the measurement data and time data accordingly. The scene judgment module in the network device such as LMF judges whether the terminal is outdoors, from outdoors to indoors, or indoors at the first time based on the measurement data and time data, and the specific judgment process can be seen in S103. The scene judgment module outputs a scene identifier to the training data acquisition module, and the scene identifier indicates that the terminal is outdoors or from outdoors to indoors or indoors.

[0118] The training data acquisition module obtains the location tag based on the scene identifier and constructs the training data including the location tag. Specifically, the scene identifier indicates that the terminal is outdoors, and the GNSS coordinates corresponding to the first time are used as the location tag to construct the training data. The scene identifier indicates that the terminal moves from outdoor to indoor. Based on the sensor data and its acquisition time, and the last GNSS coordinates acquired outdoors and their acquisition time, the location coordinates of the terminal after moving from outdoor to indoor are deduced. In some implementations, LMF calls the AI ​​PDR model or AI VDR model, and inputs the sensor data and its acquisition time, as well as the last GNSS coordinates acquired outdoors and their acquisition time, into the AI ​​PDR model or AI VDR model to obtain the location tag. For more detailed description, please refer to S105-S106.

[0119] The scene identifier indicates that the terminal is indoors, and the positioning result is obtained by correcting the short-range signal to obtain the first-time location tag, see S107.

[0120] After obtaining the location tags, network devices such as training data acquisition modules construct training data: The training data includes location tags and corresponding feature data, and may also include the credibility of the location tags. Because the derivation of location tags from outdoor to indoor states is based on track derivation algorithms and sensor data acquisition, the credibility of the location tags in this step is determined based on the accuracy of sensor data and the credibility of the track derivation algorithm. The accuracy of sensor data can be obtained from the sensor, and the credibility of the track derivation algorithm is output by the track derivation algorithm. For example, the AI-based PDR algorithm will output the credibility of the location tag while outputting the location tag.

[0121] The feature data in this step includes but is not limited to: at least one of sensor data, short-range signal data, cellular communication data, and GNSS data. In some implementations, after the available data is screened, data that meets the quality requirements is used as feature data.

[0122] The more feature data the training data includes, the higher the quality, and the more conducive it is to improving the accuracy of the AI ​​model. In some implementations, the training data can also be screened based on the credibility of the location tags, and the location tags with high credibility and the corresponding feature data can be used as training data to further improve the accuracy of AI model predictions.

[0123] In this embodiment, based on the different environments in which the terminal is located and the speed of the terminal, such as outdoors, entering indoors from outdoors, or indoors, the location tag of the terminal is obtained based on different data and dead reckoning algorithms, thereby constructing training data with location tags, thereby improving the positioning accuracy of the trained model.

[0124] It is understandable that the above embodiments are based on Figure 3 The scenario shown in FIG. 1 is used as an example to illustrate the present invention. In addition to this scenario, the method provided in the embodiment of the present application is also applicable to other scenarios, such as Figure 3 The path in the opposite direction of the arrow indicates that the terminal moves indoors first and then moves from indoors to outdoors. Figure 4 or Figure 5 The method from outdoor to indoor is similar to that shown. The first outdoor GNSS coordinate after going from indoor to outdoor can be used as the reference coordinate, and the position coordinates from indoor to outdoor and indoors can be derived based on the sensor data and the corresponding time.

[0125] It is understandable that the "entering indoors" in the embodiments of the present application covers both the state of the first position from the outdoors to the indoors and the state of the last indoor position from the indoors to the outdoors. Figure 3 On the path in the opposite direction of travel indicated by the arrow, position 3 is the last indoor position before going from indoors to outdoors, so the state of position 3 is "entering indoors".

[0126] In the above embodiment, the data of the starting coordinates of the derivation algorithm is the GNSS coordinates. It is understandable that an alternative method is to determine the starting coordinates based on at least one of the outdoor satellite positioning coordinates and the cellular communication data.

[0127] In the above embodiments, taking LMF obtaining training data and performing scene judgment and positioning as an example, it can be understood that the function of LMF can also be implemented by the terminal.

[0128] The above LMF is used as the execution subject for example only and is not limited. The above method can also be completed by different network elements in cooperation, such as Figure 6 For example, the operation, administration, and maintenance (OAM) network element determines whether the terminal is outdoors, entering indoors from outdoors, or indoors, and sends the determination result to the LMF. After receiving the determination result, the LMF executes the steps of obtaining the location data of the terminal in the above embodiment.

[0129] It should be understood that Figure 5 The training process shown is based on the example of an AI model built into the LMF, but the present application is not limited to this. For example, the AI ​​model can also be built into the terminal or other network elements. The specific implementation of the AI ​​model training method, such as the data source of the AI ​​model, may be different in different architectures, but should all be within the scope of protection of this application.

[0130] Figure 7is a structural example diagram of a terminal provided in an embodiment of the present application, Figure 7 The system includes: a processor 10, a memory 11 and a wireless communication module 12.

[0131] The wireless communication module 12 includes a short-range communication module, such as Figure 2 The WLAN module, Bluetooth module, and GNSS module shown in the figure have the same functions as described above.

[0132] The processor 10 includes a modem and an application processor. The modem can be used to implement communication functions based on a cellular network, such as Figure 2 The functionality of the cellular module is shown.

[0133] The acquisition of the measurement data in the above-mentioned embodiment may be implemented by a modem, or may be implemented by a modem and an application processor together.

[0134] The memory 11 is used to store program codes, and the processor 10 is used to run the program codes so that the terminal implements the steps executed by the terminal in the above embodiments, or the steps executed by the LMF, or the steps executed by the terminal and the LMF.

[0135] Figure 8 7 is a schematic block diagram of a communication device provided in an embodiment of the present application. The communication device 700 may include a processing module 710 and a communication module 720. The communication module 720 may implement a corresponding communication function, which may be an internal communication function of the communication device 700 or a communication function between the communication device 700 and other devices. Optionally, the communication module 720 may also be referred to as a communication interface or a transceiver module. The processing module 710 may implement a corresponding processing function.

[0136] Optionally, the communication device 700 further includes a storage module, which can be used to store instructions and / or data; the processing module 710 can read the instructions and / or data in the storage module, so that the communication device 700 implements the aforementioned method embodiment.

[0137] In a possible design, the communication device 700 may correspond to the network device in the above method embodiment, or a component (such as a circuit, a chip or a chip system, etc.) configured in the network device. The communication device 700 can be used to execute the steps or processes executed by the network device in any of the above method embodiments.

[0138] For example, the communication module 720 is used to obtain measurement data and time data, the measurement data including sensor data and wireless signal data, the sensor data being obtained through a sensor provided on the terminal, the wireless signal data including at least one of satellite positioning data and cellular communication data, and the time data indicating the time when the measurement data was obtained.

[0139] The processing module 710 is used to obtain the location data of the terminal entering the room based on the sensor data, the acquisition time of the sensor data, the outdoor positioning data, and the acquisition time of the outdoor positioning data. The outdoor positioning data represents the location data of the terminal outdoors, and the outdoor positioning data is obtained based on the wireless signal data.

[0140] The above are only examples, and for detailed steps or processes, please refer to the description of the aforementioned embodiments.

[0141] In a possible design, the communication device 700 may correspond to the terminal in the above method embodiment, or a component configured in the terminal (such as a circuit, a chip or a chip system, etc.). The communication device 700 may be used to execute the steps or processes executed by the terminal in any of the above method embodiments.

[0142] For example, the communication module 720 is used to obtain measurement data and time data, and send the measurement data and time data to the network device, the measurement data includes sensor data and wireless signal data, the sensor data is obtained through a sensor set on the terminal, and the wireless signal data includes at least one of satellite positioning data and cellular communication data.

[0143] It is understandable that the steps or processes executed by the above network devices can also be completed by terminal devices.

[0144] Figure 8 800 is another schematic block diagram of a communication device 800 provided in an embodiment of the present application. The communication device 800 may be a chip, a chip system, or a processor, etc., for implementing the above method in a terminal or a network device. The communication device 800 may be used to implement the method described in the above method embodiment, and the details may refer to the description in the above method embodiment.

[0145] like Figure 8As shown, the communication device 800 may include one or more processors 810, which may also be referred to as a processing unit or a processing module, and may implement certain control functions. The processor 810 may be a general-purpose processor or a dedicated processor, for example, a baseband processor or a central processing unit. The baseband processor may be used to process the communication protocol and the communication data, and the central processing unit may be used to control the communication device 800 (e.g., a base station, a baseband chip, a user, a user chip), execute a software program, and process the data of the software program.

[0146] In an optional design, the processor 810 may also store instructions and / or data, and the instructions and / or data can be executed by the processor 810 so that the communication device 800 executes the method described in the above method embodiment.

[0147] In another optional design, the communication device 800 may include a communication interface 820 for implementing the receiving and sending functions. For example, the communication interface 820 may be a transceiver circuit, an interface, an interface circuit, or a transceiver. The transceiver circuit, interface, interface circuit, or transceiver for implementing the receiving and sending functions may be separate or integrated. The above-mentioned transceiver circuit, interface, interface circuit, or transceiver may be used for reading and writing code / data, or the above-mentioned transceiver circuit, interface, interface circuit, or transceiver may be used for transmitting or delivering signals.

[0148] Optionally, the communication device 800 may include one or more memories 830, on which instructions may be stored, and the instructions may be executed on the processor 810, so that the communication device 800 performs the method described in the above method embodiment. Optionally, data may also be stored in the memory 830. Optionally, instructions and / or data may also be stored in the processor 810. The processor 810 and the memory 830 may be provided separately or integrated together.

[0149] It should be understood that in a possible design, each step in the method embodiment provided by the present application can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software. The steps of the method disclosed in conjunction with the embodiment of the present application can be directly embodied as a hardware processor for execution, or a combination of hardware and software modules in a processor for execution. The software module can be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it is not described in detail here.

[0150] In one implementation, the communication device 800 may correspond to the network device in the above method embodiment, and may be used to execute the various steps and / or processes executed by the network device in the above method embodiment. The processor 810 may be used to execute instructions stored in the memory 830, and when the processor 810 executes the instructions stored in the memory, the processor 810 is used to execute the various steps and / or processes of the above method embodiment corresponding to the network device.

[0151] It should be understood that the above-mentioned processing device may be one or more chips. For example, the processing device may be a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on chip (SoC), a central processor unit (CPU), a network processor (NP), a digital signal processor (DSP), a micro controller unit (MCU), a programmable logic device (PLD) or other integrated chips.

[0152] It can be understood that the memory in the embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0153] An embodiment of the application further provides a computer-readable storage medium having instructions stored thereon, and when the instructions are executed on an electronic device, the electronic device executes the method for acquiring location data described in the above embodiment.

[0154] The embodiment of the application also provides a computer program product having an executable program stored thereon. When the computer program product is run on an electronic device, the electronic device implements the method for obtaining location data described in the above embodiment.

[0155] The embodiment of the present application also provides a chip system, which includes one or more processors for calling and running instructions stored in the memory from the memory, so that the method described in the above embodiment is executed. The chip system can be composed of a chip, or it can include a chip and other discrete devices. Among them, the chip system may include an input circuit or interface for sending information or data, and an output circuit or interface for receiving information or data.

[0156] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware, or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated.

[0157] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as 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 interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0158] It should be understood that in the various embodiments of the present application, the size of the serial number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0159] In short, the above is only a preferred embodiment of the technical solution of this application, and is not intended to limit the protection scope of this application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application should be included in the protection scope of this application.

Claims

1. A method for acquiring position data, characterized in that: Applied to an artificial intelligence (AI) model, the method comprises: Acquire measurement data and time data, the measurement data including sensor data and wireless signal data, the sensor data being acquired through a sensor provided on the terminal, the wireless signal data including at least one of satellite positioning data and cellular communication data, and the time data indicating the acquisition time of the measurement data; Based on the sensor data, the acquisition time of the sensor data, the outdoor positioning data, and the acquisition time of the outdoor positioning data, the location data of the terminal entering the room is acquired. The outdoor positioning data represents the location data of the terminal outdoors. The outdoor positioning data is acquired based on the wireless signal data.

2. The method according to claim 1, characterized in that The acquiring of the location data of the terminal entering the room comprises: Based on a pedestrian dead reckoning algorithm or a vehicle dead reckoning algorithm, the position data of the terminal entering the room is obtained, wherein the pedestrian dead reckoning algorithm is determined based on the terminal being in a low-speed moving state, and the vehicle dead reckoning algorithm is determined based on the terminal being in a high-speed moving state, and whether the terminal is in a low-speed moving state or a high-speed moving state is determined based on acceleration sensor data, or is determined based on navigation data and map data.

3. The method according to claim 1 or 2, characterized in that: The interval between the acquisition time of the outdoor positioning data and the first time satisfies a first condition, and the first time is the time when the terminal enters the room.

4. The method according to claim 1 or 2, characterized in that: The outdoor positioning data is obtained based on the wireless signal data, including: the outdoor positioning data is obtained based on the first positioning data corrected by the geographic location coordinates, the first positioning data is obtained based on the wireless signal data, the geographic location coordinates are the coordinates of the exit or entrance, the terminal goes from indoors to outdoors via the exit, and the terminal goes from outdoors to indoors via the entrance.

5. The method according to claim 4, characterized in that The distance between the position represented by the geographic location coordinates and the position represented by the outdoor positioning data is less than or equal to a distance threshold.

6. The method according to claim 4, characterized in that The geographic location coordinates are determined based on a driving trajectory, and the driving trajectory is obtained based on navigation data of the terminal.

7. The method according to claim 4, characterized in that The first position data does not meet the accuracy condition.

8. The method according to claim 1 or 2, characterized in that: The terminal entering the indoor space is determined based on at least one of a light intensity reduction amount being greater than or equal to a first threshold and a satellite positioning signal quality degradation amount being greater than or equal to a second threshold, the light intensity reduction amount being a reduction amount of the second light intensity compared to the first light intensity, the second light intensity being represented by visible light sensor data corresponding to a third time, the first light intensity being represented by visible light sensor data corresponding to the second time, the satellite positioning signal quality degradation amount being a degradation amount of a second quality parameter compared to a first quality parameter, the second quality parameter being represented by the satellite positioning data corresponding to the third time, the first quality parameter being represented by the satellite positioning data corresponding to the second time, and the second time being earlier than the third time.

9. The method according to claim 1 or 2, characterized in that: Whether the terminal enters the room is determined based on the sensor data, where the sensor data includes at least one of visible light sensor data, gyroscope data, acceleration data, and air pressure data.

10. The method according to claim 1 or 2, characterized in that: The acquiring of the location data of the terminal entering the indoor space based on the sensor data, the acquisition time of the sensor data, the outdoor positioning data, and the acquisition time of the outdoor positioning data includes: Based on at least one of the short-range signal data acquired after the terminal enters the room, the credibility of the sensor data, and the credibility of the outdoor positioning data, as well as the sensor data, the time when the sensor data is acquired, the outdoor positioning data, and the time when the outdoor positioning data is acquired, the location data of the terminal entering the room is acquired.

11. An electronic device, characterized in that: The electronic device comprises: one or more processors and a memory; the memory is used to store program codes; the processor is used to run the program codes, so that the electronic device implements the method according to any one of claims 1 to 10.

12. A computer-readable storage medium, characterized in that: Instructions are stored thereon, and when the instructions are executed on an electronic device, the electronic device executes the method according to any one of claims 1 to 10.

13. A computer program product, characterized in that An execution program is stored thereon, and when the computer program product is executed on an electronic device, the electronic device implements the method according to any one of claims 1 to 10.

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