Method and device for obtaining location data

Abstract

The present application provides a method for obtaining location data and related devices, the method comprising: obtaining measurement data and time data, the measurement data comprising sensor data and wireless signal data, the sensor data being obtained through a sensor provided on a terminal, the time data representing the time of obtaining the measurement data, obtaining the location data of the terminal entering the room based on the sensor data, the time of obtaining the sensor data, the outdoor positioning data, and the time of obtaining the outdoor positioning data, wherein the location of the terminal entering the room is determined based on the relevant information of the outdoor positioning data and the sensor data, thereby avoiding the problem of being unable to transmit information to the network in a timely manner when the communication quality between the terminal and the network deteriorates after the terminal enters the room, and enhancing the timeliness of the terminal positioning. The accuracy of the outdoor positioning data and the sensor data is high, thereby improving the accuracy of the location data of the terminal entering the room. The sensor data has higher stability and can meet the user's positioning needs in a timely manner.

Description

Technical Field

[0001] The present application relates to the field of electronic information technology, and in particular to a method for obtaining location data and related devices. 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, because the environment in which the terminal is located is constantly changing, the positioning performance between the network and the terminal varies with the changing 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 location in a timely manner, resulting in positioning errors and poor positioning timeliness. The positioning accuracy between the network and the terminal needs to be improved. Summary of the Invention

[0004] This application provides a method and related device for obtaining location data to achieve the purpose of obtaining more accurate location data. The disclosed technical solution is as follows:

[0005] In a first aspect, the present application provides a method for acquiring location data, which is applied to an artificial intelligence (AI) model. The method comprises: acquiring measurement data and time data, the measurement data including sensor data and wireless signal data, the sensor data being acquired by sensors provided on a terminal, and the time data indicating the time the measurement data was acquired. Based on the sensor data, the time the sensor data was acquired, outdoor positioning data, and the time the outdoor positioning data was acquired, location data of the terminal entering a room is acquired. In this method, the location of the terminal entering a room is determined based on relevant information from the outdoor positioning data and relevant information from the sensor data. This avoids the problem of being unable to transmit information to the network in a timely manner when communication quality between the terminal and the network deteriorates after entering the room, thereby enhancing the timeliness of terminal positioning. Furthermore, the high accuracy of the outdoor positioning data and sensor data can further improve the accuracy of the location data of the terminal entering a room. Furthermore, the sensor data has a higher stability (for example, wireless signals are difficult to acquire in underground environments, but sensor data is easy to acquire), which can promptly meet the user's positioning needs.

[0006] In some implementations, obtaining the terminal's position data upon entering a room includes obtaining the terminal's position data upon entering the room based on a pedestrian dead deduction algorithm or a vehicle dead deduction algorithm, wherein the pedestrian dead deduction algorithm is determined based on the terminal being in a low-speed movement state, and the vehicle dead deduction algorithm is determined based on the terminal being in a high-speed movement state, wherein the determination of the terminal being in a low-speed movement state or a high-speed movement state is based on acceleration sensor data, or based on navigation data and map data. Selecting a dead deduction algorithm based on the terminal's movement speed facilitates obtaining more accurate position data upon entering the room based on the dead deduction algorithm.

[0007] In some implementations, the interval between the acquisition time of the outdoor positioning data and the first time satisfies the first condition, where the first time is the time when the terminal enters the room. Outdoor positioning data, such as satellite positioning data, has high positioning accuracy. Furthermore, when using outdoor positioning data to derive indoor positioning data, the closer the acquisition time of the outdoor positioning data is to the time when the terminal enters the room from the outdoors, the more accurate the derived indoor positioning data. Therefore, filtering the outdoor positioning data based on the acquisition time helps further improve the accuracy of the indoor positioning data.

[0008] In some implementations, outdoor positioning data is obtained based on wireless signal data, including: outdoor positioning data obtained by correcting first positioning data based on geographic location coordinates, where the first positioning data is obtained based on wireless signal data, and the geographic location coordinates are the coordinates of an exit or entrance, where the terminal goes from indoors to outdoors via an exit, and where the terminal goes from outdoors to indoors via an entrance. Because building exits or entrances are fixed in position, correcting outdoor positioning data based on the coordinates of the exit or entrance helps reduce "drift" in satellite positioning data or cellular communication data caused by outdoor obstructions, thereby improving the accuracy of outdoor positioning data and further improving the accuracy of positioning data collected when the terminal enters a building.

[0009] In some implementations, the distance between the location represented by the geographic coordinates and the location represented by the outdoor positioning data is less than or equal to a distance threshold. If a building has multiple exits or entrances, the locations of the exits or entrances may be filtered based on the outdoor positioning data to more accurately correct the outdoor positioning data.

[0010] In some implementations, the geographic location coordinates are determined based on a driving trajectory, which is obtained based on navigation data from 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.

[0011] In some implementations, the first location data does not meet the accuracy conditions, but the outdoor positioning data (i.e., the first location data) obtained based on the wireless signal data meets the accuracy conditions and does not need to be corrected, which is beneficial for saving computing resources while ensuring the accuracy of the outdoor positioning data.

[0012] 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 conducive to improving the accuracy of the location data of the terminal.

[0013] In some implementations, whether a terminal has entered an indoor space is determined based on at least one of a decrease in light intensity greater than or equal to a first threshold and a degradation in satellite positioning signal quality greater than or equal to a second threshold, the decrease in light intensity being a decrease in 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, and the first light intensity being represented by visible light sensor data corresponding to a second time, the degradation in satellite positioning signal quality being a degradation in the second quality parameter compared to the first quality parameter, the second quality parameter being represented by satellite positioning data corresponding to a third time, and the first quality parameter being represented by satellite positioning data corresponding to a second time, the second time being earlier than the third time. In other words, if a sudden deterioration or even disappearance of GNSS quality is detected and / or a sudden dimming of light is detected by the optical sensor, the terminal is determined to have entered an indoor space from the outdoors. This determination method fully utilizes the differences in wireless signals and sensor data between outdoor and indoor spaces, and has high accuracy and feasibility.

[0014] In some implementations, the determination of a terminal entering indoors is based on sensor data, including at least one of visible light sensor data, gyroscope data, acceleration data, and air pressure data. This determination, combined with the characteristics of wireless signals and sensor data from the terminal entering indoors from outdoors, especially underground, facilitates accurate identification of this scenario.

[0015] In some implementations, obtaining the location data of a terminal entering a room based on sensor data, the time the sensor data was acquired, outdoor positioning data, and the time the outdoor positioning data was acquired includes obtaining the location data of the terminal entering the room based on at least one of the following: short-range signal data acquired after the terminal entered the room, the credibility of the sensor data, and the credibility of the outdoor positioning data, as well as the sensor data, the time the sensor data was acquired, the outdoor positioning data, and the time the outdoor positioning data was acquired. The short-range signal serves as characteristic data of the indoor environment, and its credibility can be used to filter out more credible sensor data and outdoor positioning data. These, along with the sensor data, outdoor positioning data, and their acquisition time, serve as inputs to the AI ​​model, further improving the accuracy of the location data output by the AI ​​model.

[0016] 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.

[0017] A 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 in the first aspect of the present application.

[0018] 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.

[0019] 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 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 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.

[0020] 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.

[0021] 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 the indoor space.

[0022] 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 positioning data corrected 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.

[0023] 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.

[0024] 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.

[0025] In some implementations, the first location data does not satisfy an accuracy condition.

[0026] In some implementations, whether the terminal enters 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 satellite positioning data corresponding to the third time, the first quality parameter being represented by satellite positioning data corresponding to the second time, and the second time being earlier than the third time.

[0027] In some implementations, 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.

[0028] In some implementations, the obtaining of 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 includes: obtaining the location data of the terminal entering the room based on at least one of the short-range signal data obtained 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 acquisition time of the sensor data, the outdoor positioning data, and the acquisition time of the outdoor positioning data.

[0029] A fifth aspect of the present application provides a chip system, comprising one or more processors configured to retrieve and execute instructions stored in a memory, thereby executing the method for acquiring location data provided in the first aspect of the present application. The chip system may be composed of a chip alone, or may include a chip and other discrete components.

[0030] 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 including 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

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

[0032] Figure 1 This is an example diagram of an application scenario of obtaining terminal location data through a network, provided by an embodiment of the present application;

[0033] Figure 2 1 is an exemplary diagram of the architecture of a communication system for implementing a method for acquiring location data provided in an embodiment of the present application;

[0034] Figure 3 This is an example diagram of a scenario where a user carries a terminal from outdoors into a room.

[0035] Figure 4 is a flow chart of a method for obtaining location data provided by an embodiment of the present application;

[0036] Figure 5 This is an example diagram of an architecture for obtaining training data provided by an embodiment of the present application;

[0037] Figure 6 This is an example of an architecture of a communication system for implementing a method for acquiring location data provided in an embodiment of the present application;

[0038] Figure 7 This is a diagram illustrating a structure of a terminal provided in an embodiment of the present application;

[0039] Figure 8 This is a structural example diagram of a communication device provided in an embodiment of the present application;

[0040] Figure 9 This is a structural example diagram of a communication device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] The terms "first", "second" and "third" in the specification, claims and drawings of this application are used to distinguish different objects rather than to limit a specific order.

[0042] In the embodiments of the present application, words such as "in some implementations" or "for example" are used to indicate examples, illustrations or explanations, and should not be interpreted as being more preferred or more advantageous than other embodiments or design solutions.

[0043] 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 will emerge in future communication developments.

[0044] The communication system includes terminals and network equipment. The network equipment includes access network equipment and core network equipment.

[0045] A terminal can be in various forms, such as a mobile phone, a tablet computer, a computer with wireless transceiver capabilities, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal in industrial control, an in-vehicle terminal device, a wireless terminal in self-driving, a wireless terminal in remote medical care, a wireless terminal in smart grids, a wireless terminal in transportation safety, a wireless terminal in smart cities, a wireless terminal in smart homes, a wearable terminal device, etc. A terminal may also be sometimes referred to as a terminal device, user equipment (UE), access terminal device, in-vehicle terminal, industrial control terminal, UE unit, UE station, mobile station, mobile station, remote station, remote terminal device, mobile device, UE terminal device, terminal device, wireless communication device, UE agent, or UE device. A terminal may also be a fixed terminal or a mobile terminal.

[0046] Access network equipment includes base stations. A base station 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 in subsequent 3GPP evolution, an access node in a Wi-Fi system, a wireless relay node, a wireless backhaul node, etc. A base station can be: a macro base station, a micro base station, a pico base station, a small station, a relay station, or a balloon station, etc. A base station can include one or more co-sited or non-co-sited TRPs. A 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. A base station can communicate with a terminal or communicate with the terminal through a relay station.

[0047] The core network equipment and the base station can be independent and different physical devices, or the functions of the core network equipment and the logical functions of the base station can be integrated into the same physical device, or part of the functions of the core network equipment and part of the functions of the base station can be integrated into one physical device. Figure 1 For example, LMF is run in the core network equipment.

[0048] In the following text, core network equipment and access network equipment are collectively referred to as network equipment.

[0049] 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 network (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), which outputs a position estimation result based on the wireless signal data.

[0050] However, because the environment in which the terminal is located is constantly changing, the positioning performance between the network device and the terminal varies with the changing environment. For example, in some scenarios, the communication quality between the network device and the terminal is poor, and the terminal cannot promptly obtain the aforementioned PRS and Bluetooth signals, and may also be unable to promptly feedback wireless signal data. As a result, the network device cannot promptly obtain the terminal's location, resulting in positioning errors and poor positioning timeliness. Therefore, the positioning accuracy between the network device and the terminal needs to be improved.

[0051] In view of this, the present application provides a method and related apparatus for obtaining location data to achieve more accurate location data.

[0052] Figure 2 The present invention is a diagram showing an example of the architecture of a communication system for implementing a method for obtaining location data.

[0053] Combine Figure 2The terminal includes: a global navigation satellite system (GNSS) module, a cellular module, a wireless local area network (WLAN) module, and a Bluetooth module.

[0054] The GNSS module is used to implement GNSS positioning. Specifically, the GNSS module receives signals transmitted by satellites and obtains the GNSS data carried in the signals. GNSS data includes the terminal's location data obtained using a GNSS method and evaluation parameters for the location data. The evaluation parameters indicate the accuracy of the terminal's location data obtained using satellite positioning. Examples of evaluation parameters include at least one of the horizontal dilution of precision (HDOP) and the carrier-to-noise ratio. GNSS data may also include the number of satellites searched. In environments with strong satellite signals, such as open areas outdoors, GNSS positioning provides relatively accurate terminal location data. However, in relatively closed or heavily obstructed environments, such as indoors, the GNSS module may not receive GNSS signals of sufficient quality for positioning. GNSS is an example of satellite positioning and can be replaced by or used in conjunction with other satellite positioning technologies.

[0055] The cellular module implements cellular communication functions. Positioning-related cellular communication data includes but is not limited to PRS, angle-of-arrival (AOA), and timing advance (TA). For example, a terminal receives PRS from access network equipment, such as a base station. PRS assists in positioning services in mobile communications. PRS that meet positioning requirements can be received indoors or outdoors. The terminal can measure the PRS to obtain cellular communication data.

[0056] The WLAN module is used to implement wireless local area network (WLAN) functions such as wireless fidelity (Wi-Fi). WLAN positioning-related functions include, but are not limited to, receiving Wi-Fi signals from access points (APs) and obtaining Wi-Fi data from these signals. 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).

[0057] The Bluetooth module is used to implement Bluetooth functions. Positioning-related Bluetooth functions include, but are not limited to, detecting Bluetooth signals emitted by other electronic devices and acquiring the Bluetooth data carried in those signals. Bluetooth data includes information about the device sending the Bluetooth signal and the strength of the Bluetooth signal.

[0058] 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.

[0059] The terminal also includes sensors. Sensors related to the technical solutions provided in the embodiments of the present application include, but are not limited to, gyroscopes, accelerometers, visible light sensors, and barometers.

[0060] Sensors are used to sense 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 terminal's acceleration data, 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.

[0061] In the embodiments of the present application, wireless signal data and sensor data are collectively referred to as measurement data.

[0062] The LMF includes an artificial intelligence (AI) model for positioning. It also includes a scene determination module, which determines the terminal's location based on at least one of wireless signal data and sensor data, such as indoors, moving from outdoor to indoor, or outdoor. The AI ​​model's positioning function uses different methods and data to obtain the terminal's location data for different scenarios.

[0063] Figure 2 The 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.

[0064] 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.

[0065] 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:

[0066] S101: The terminal obtains measurement data and time data.

[0067] The measurement data includes wireless signal data and sensor data.

[0068] 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.

[0069] 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.

[0070] Combine Figure 3 In the scenario shown, it is understandable that when the terminal is outdoors, it can usually obtain sufficient GNSS data and cellular communication data, but may not be able to obtain sufficient short-range communication data such as Bluetooth data and Wi-Fi data. When the terminal is indoors, it can usually obtain sufficient cellular communication data and short-range communication data, but has difficulty obtaining sufficient GNSS data.

[0071] Sensor data includes but is not limited to: at least one of posture data, acceleration data, visible light intensity data, and air pressure data. Figure 2 The example's sensor gets sensor data.

[0072] In one method for a terminal to acquire data, the terminal acquires data at a preset period. The period for acquiring wireless signal data and the period for acquiring sensor data may be the same or different. In another method for a terminal to acquire data, the terminal acquires data in response to preset trigger conditions, where the conditions for acquiring wireless signal data may be the same or different from the conditions for acquiring sensor data. It will be understood that the acquisition period or trigger conditions for each type of wireless signal data or each type of sensor data may be the same or different.

[0073] Time data indicates the time when the measurement data was acquired. The acquisition time of the measurement data is the time when the terminal acquired the measurement data. Time data can be a moment value or a time interval.

[0074] 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. 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.

[0075] S102: The terminal sends measurement data and time data to the network device. Correspondingly, the network device receives the measurement data and time data.

[0076] In some implementations, the terminal filters the data before sending it to the network device. Data filtering can be understood as removing data that does not meet requirements, including but not limited to at least one of positioning requirements, model training requirements, and data quality requirements. For example, if the Wi-Fi signal strength in a piece of Wi-Fi data does not meet a threshold, the Wi-Fi data will be deleted.

[0077] 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 pre-configured 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.

[0078] The above-mentioned data screening and time data processing may also be performed by the network device instead of the terminal.

[0079] 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 to send from the base station, 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.

[0080] 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.

[0081] 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.

[0082] 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 of data acquisition, and does not necessarily represent the real-time location status of the terminal.

[0083] 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 simply referred to as "entering indoors". The first state after entering indoors from outdoors is outdoor entering indoors. 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, from outdoor to indoor. Positions 3 to 7 are indoor positions.

[0084] It is understood that the embodiments of the present application are not limited to the first position where the terminal enters the room from the outdoors being "outdoors into indoors". For example, the position corresponding to "outdoors into indoors" can be any position indoors. For another example, the position corresponding to "outdoors into indoors" can be a position in the process of moving from the outdoors into the indoors. In other words, the position corresponding to "outdoors into indoors" is not distinguished by the geographical boundary between indoors and outdoors, but can depend on the specific application scenario and needs.

[0085] 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.

[0086] 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.

[0087] One way to determine whether a terminal enters a room from outdoors is to make a determination based on data acquired at different times (eg, adjacent acquisition times) and a comparison result between the data.

[0088] 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 and visible light sensor data with the third acquisition time, 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.

[0089] 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. In descending order of acquisition time, the previous data item of the data with the fourth acquisition time is the data with the third acquisition time. If the visible light sensor data with the fourth acquisition time, compared with the visible light sensor data with the third acquisition time, indicates a decrease in light intensity greater than or equal to a first threshold, i.e., there is a significant decrease in GNSS signal quality, and if the GNSS data with the fourth acquisition time, compared with the GNSS data with the third acquisition time, indicates a deterioration in GNSS signal quality greater than or equal to a second threshold, i.e., there is a significant decrease in light intensity, then it is determined that the terminal has entered indoors from outdoors.

[0090] When the terminal is moving at a low speed outdoors, the changes between the data collected successively are relatively gradual. Therefore, the accuracy of determining whether the terminal has entered indoors based on the data collected successively is relatively high. However, whether the terminal is moving at a low speed is not a prerequisite for the above method of determining whether the terminal has entered indoors from outdoors. In other words, it is not necessary to determine whether the terminal is moving at a low speed before determining whether the terminal has entered indoors from outdoors.

[0091] For another example, the data acquired at the third acquisition time and the data acquired at 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 movement state (e.g., a driving state). Furthermore, based on the posture data and air pressure data acquired at multiple different times, it is determined that the terminal is in a downward movement state. Furthermore, it is determined that the terminal is not outdoors by combining at least one of visible light sensor data and GNSS data, and then it is determined that the terminal is in a state of entering an indoor area, such as an underground parking lot. Similarly, determining that the terminal is in a high-speed movement state is an optional step.

[0092] 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.

[0093] Combine Figure 3For 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.

[0094] Combine Figure 3 , the position from outdoor to indoor refers to the first position after entering the room from outdoor, such as Figure 3 Position 3 in .

[0095] If it is determined that the terminal is outdoors, S104 is executed.

[0096] 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.

[0097] When it is determined that the terminal is already indoors, the indoor position coordinates of the terminal are derived using a correction method for the short-range positioning result, as in S107 .

[0098] 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.

[0099] As mentioned above, GNSS data is satellite positioning data, including the terminal's location coordinates obtained by satellite positioning. Therefore, one example is to use the location coordinates in the GNSS data corresponding to the first time as the terminal's location coordinates.

[0100] 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).

[0101] S105 : The network device determines the starting coordinates based on the GNSS coordinates acquired before the first time.

[0102] In this embodiment, the GNSS coordinates acquired by the terminal outdoors are used as the starting coordinates for deriving the indoor position coordinates.

[0103] Combine Figure 3As shown, both Location 1 and Location 2 are outdoors and can be used as starting coordinates. However, it is understood that the closer the distance to an indoor location is, the more accurate the derivation result may be. Therefore, in this embodiment, Location 2 is used as the derivation starting location. Location 2 is the location represented by the last GNSS data acquired before the terminal enters the indoor location.

[0104] 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 the preset interval threshold, or within the preset range. The first condition can be configured as needed, combined with Figure 3 Assuming that location 3 corresponds to the first time, and the interval between the time at which data was acquired at location 2 and the first time is less than or equal to the interval threshold, the GNSS coordinates acquired at location 2 are used as the starting coordinates. It is understandable that the GNSS coordinates at location 2 may not be accurate enough. In this case, coordinates from another outdoor location, such as the GNSS coordinates at location 1, can be selected. The interval threshold can be preconfigured.

[0105] It is understandable that GNSS coordinates may not be accurate enough, for example, Figure 3 Position 2 in the figure is near a building such as a bridge, which reduces the accuracy of GNSS positioning and causes GNSS coordinate drift. Therefore, to improve the accuracy of GNSS coordinates and 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 is understood that the failure of the GNSS coordinate accuracy to meet the accuracy condition is optional, and correction can be performed directly without determining the accuracy.

[0106] 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 into a room. 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.

[0107] It is understood that the building a terminal enters may have multiple entrances. In this case, one approach is to use the GNSS coordinates as the starting coordinates to select one of the multiple entrance coordinates, for example, selecting the entrance coordinate closest to the GNSS coordinates used as the starting coordinates, and then revising the GNSS coordinates used as the starting coordinates based on the selected entrance coordinates. Another approach is to obtain navigation data from the terminal, obtain the terminal's driving trajectory based on the navigation data, and determine the coordinates of the terminal's entrance to the building based on the driving trajectory. Typically, navigation data includes map data and driving trajectory data.

[0108] 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.

[0109] In some implementations, if the terminal is determined to be in a low-speed movement state, the network device invokes a pedestrian dead reckoning (PDR) algorithm based on sensor data such as the starting coordinates, the acquisition time corresponding to the starting coordinates, posture data from the gyroscope, acceleration data from the accelerometer, and the corresponding acquisition time to obtain the location coordinates at the first time. Alternatively, if the terminal is determined to be in a high-speed movement state, the network device invokes a vehicle dead reckoning (VDR) algorithm to obtain the location coordinates at the first time. It is understood that the location coordinates at the first time are the location coordinates of the terminal when it enters the indoor state from the outdoor state.

[0110] Based on the different states of the terminal: low-speed movement state (such as the user carrying the terminal on foot) or high-speed movement state (such as driving), determining (or selecting) the corresponding algorithm is conducive to obtaining more accurate location coordinates of entering the room.

[0111] In addition to the aforementioned methods, such as determining whether a terminal is in a low-speed or high-speed movement state based on acceleration data, other methods can also be used to determine whether the terminal is in a low-speed or high-speed movement state. For example, based on the movement trajectory obtained from navigation data, combined with the road information and movement trajectory represented by map data, the location data of the entrance from indoor to indoor space is obtained. Based on the type of pre-configured entrance represented by the map data, the walking or driving state is determined. If the entrance type is a garage entrance, the driving state is determined; otherwise, the walking state is determined. For another example, based on the posture data collected by the gyroscope, combined with the acceleration data and the air pressure data collected by the barometer, it can be determined that the terminal is in a downward movement state at a relatively high speed, i.e., a high-speed movement state.

[0112] 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.

[0113] 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, or can be performed before S106 when it is determined that the terminal is in a state of moving from outdoor to indoor.

[0114] 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 input data for 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.

[0115] S107: The network device obtains the indoor position coordinates of the terminal at the first time by correcting the short-range signal positioning result.

[0116] Combine Figure 3 As shown, position 3 is the state of entering indoors from outdoors, and positions 4 to 7 are all indoors. In this step, the coordinates of position 4 are obtained as an example.

[0117] Use short-range signal positioning to obtain indoor location coordinates. Short-range signal positioning methods include but are not limited to obtaining the indoor location coordinates of the terminal through a triangulation positioning algorithm or a fingerprint matching algorithm based on at least one of Wi-Fi data and Bluetooth data. For example, the triangulation positioning algorithm obtains the coordinates of a location based on the Wi-Fi data generated by the signals of at least three access points at a location, as well as the location coordinates of at least three access points. For another example, a fingerprint library for various indoor locations is pre-established. The fingerprint library includes fingerprints of multiple locations, and 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 to find a matching fingerprint. Then, based on the coordinates included in the matching fingerprint, the coordinates of the location to be located are obtained.

[0118] Combine Figure 3In the scenario shown, if the terminal is already at position 4 or later during its travel, it has passed position 3. Therefore, to improve the accuracy of short-range signal positioning results, an offset is used to correct the short-range signal positioning results. That is, based on sensor data (which may also include wireless signal data) and its acquisition time, the position offset from position 3 to position 4 is calculated. This position offset and the short-range signal positioning result are then used to obtain a new short-range signal positioning result. This approach can improve the accuracy of short-range signal positioning results.

[0119] In some implementations, S104-S108 are implemented by a network device calling an AI model.

[0120] 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 indoors, uses different data based on different situations, and calls different algorithms based on different moving speeds to obtain the terminal's location data, which is conducive to improving the accuracy of the obtained location data.

[0121] 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, as well as an algorithm that matches 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.

[0122] Especially for scenarios such as underground parking lots where the quality of short-range signals, cellular communication signals, and satellite positioning signals is 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.

[0123] The above describes in detail the process of interaction between terminals and network devices. It is understandable that the data processing method mentioned above can also be applied to AI model training. The following describes it in detail.

[0124] To ensure that the AI ​​model outputs more accurate location data, it is necessary to train the AI ​​model using labeled data. The following describes the AI ​​model training process in detail.

[0125] The current difficulty in training AI models lies in obtaining sufficient and accurate location tags. For example, in some scenarios, the wireless signal quality is insufficient to support location tag acquisition, such as in underground parking lots. Whether using WLAN, gNB, or Bluetooth, the signal quality is relatively poor, making it impossible to obtain location tags. For another example, in indoor scenarios, current positioning methods based on short-range signals such as WLAN or Bluetooth generally use triangulation or fingerprint positioning. Triangulation positioning generally requires the location data of known access points, while fingerprint positioning requires a large database of fingerprint data, making it difficult to obtain sufficient location tags.

[0126] The embodiment of the present application also provides a method for training an AI model. Figure 5 For example:

[0127] The training dataset includes multiple pieces of training data, each of which includes location tags and feature data. The training data in the training dataset is input into the AI ​​model, which then obtains location data based on the feature data in the input training data. The AI ​​model then adjusts its parameters based on the location data and the location tags in the training data until training is complete.

[0128] The training data in the training dataset is obtained as follows Figure 5 As shown: The terminal obtains measurement data and time data through the wireless communication module and sensors. For details, see S101. The terminal sends the measurement data and time data to a network device such as an LMF, which receives the measurement data and time data accordingly. Based on the measurement data and time data, a scene judgment module in the network device such as the LMF determines whether the terminal is outdoors, moving from outdoors to indoors, or still indoors at the first time. For the specific judgment process, see S103. The scene judgment module outputs a scene identifier to the training data acquisition module. The scene identifier indicates whether the terminal is outdoors, moving from outdoors to indoors, or still indoors.

[0129] The training data acquisition module obtains the location tag based on the scene identifier and constructs 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, 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 deduced. In some implementations, the 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 its 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.

[0130] The scene identifier indicates that the terminal is indoors, and the positioning result of the short-range signal is obtained by correcting it to obtain the first-time location tag, see S107.

[0131] After obtaining the location tags, network devices such as the training data acquisition module construct training data:

[0132] 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 the track derivation algorithm and sensor data acquisition, the credibility of the location tags in this step is determined based on the accuracy of the sensor data and the credibility of the track derivation algorithm. The accuracy of the 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 at the same time as the location tag.

[0133] 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 filtering the available data, data that meets the quality requirements is used as the feature data.

[0134] The more feature data included in the training data, 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 filtered based on the credibility of the location tags, and highly credible location tags and corresponding feature data are used as training data to further improve the accuracy of AI model predictions.

[0135] 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.

[0136] 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. In this scenario, Figure 4 or Figure 5 The method shown in the outdoor to indoor state is similar. 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.

[0137] 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 before going 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".

[0138] In the above embodiment, the data used as the starting coordinates of the derivation algorithm is the GNSS coordinates. It is understandable that an alternative approach is to determine the starting coordinates based on at least one of outdoor satellite positioning coordinates and cellular communication data.

[0139] In the above embodiments, taking LMF obtaining training data and performing scene judgment and positioning as an example, it can be understood that the functions of LMF can also be implemented by the terminal.

[0140] 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 judgment result to the LMF. After receiving the judgment result, the LMF executes the steps of obtaining the location data of the terminal in the above embodiment.

[0141] It should be understood that Figure 5 The training process shown is based on an example where the AI ​​model is built into the LMF, but this 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 vary in different architectures, but all shall be within the scope of protection of this application.

[0142] Figure 7 This is a diagram illustrating a terminal structure according to an embodiment of the present application. Figure 7 The system includes: a processor 10, a memory 11 and a wireless communication module 12.

[0143] 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.

[0144] 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.

[0145] The acquisition of the measurement data in the aforementioned embodiment may be achieved by a modem, or may be achieved jointly by a modem and an application processor.

[0146] 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, or the steps executed by the LMF, or the steps executed by the terminal and the LMF in the above embodiments.

[0147] 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 corresponding communication functions, which may be internal communication functions of the communication device 700 or communication functions 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 corresponding processing functions.

[0148] 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 to enable the communication device 700 to implement the aforementioned method embodiment.

[0149] In one possible design, the communication device 700 may correspond to the network device in the above method embodiments, or a component configured in the network device (such as a circuit, chip, or chip system). 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.

[0150] For example, the communication module 720 is used to obtain measurement data and time data, where 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 time when the measurement data is obtained.

[0151] The processing module 710 is used to obtain 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. 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.

[0152] The above is only an example, and for detailed steps or processes, please refer to the description of the aforementioned embodiments.

[0153] In one possible design, the communication device 700 may correspond to the terminal in the above method embodiments, or a component configured in the terminal (such as a circuit, chip, or chip system). The communication device 700 can be used to execute the steps or processes executed by the terminal in any of the above method embodiments.

[0154] 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 the sensor set on the terminal, and the wireless signal data includes at least one of satellite positioning data and cellular communication data.

[0155] It is understandable that the steps or processes executed by the above network devices can also be completed by terminal devices.

[0156] 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, chip system, or processor, etc., that implements the above-mentioned method in a terminal or network device. The communication device 800 may be used to implement the method described in the above-mentioned method embodiment. For details, please refer to the description of the above-mentioned method embodiment.

[0157] like Figure 8 As shown, the communication device 800 may include one or more processors 810, which may also be referred to as processing units or processing modules, 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 communication protocols and communication data, while the central processing unit may be used to control the communication device 800 (e.g., base station, baseband chip, user, user chip), execute software programs, and process data from the software programs.

[0158] In an optional design, the processor 810 may also store instructions and / or data, which can be executed by the processor 810 to enable the communication device 800 to perform the method described in the above method embodiment.

[0159] In another optional design, the communication device 800 may include a communication interface 820 for implementing receiving and transmitting 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 transmitting functions may be separate or integrated. The transceiver circuit, interface, interface circuit, or transceiver may be used for reading and writing code / data, or the transceiver circuit, interface, interface circuit, or transceiver may be used for transmitting or delivering signals.

[0160] Optionally, the communication device 800 may include one or more memories 830, which may store instructions. The instructions may be executed on the processor 810, causing the communication device 800 to perform the method described in the above method embodiment. Optionally, the memory 830 may also store data. Optionally, the processor 810 may also store instructions and / or data. The processor 810 and memory 830 may be provided separately or integrated together.

[0161] It should be understood that, in one possible design, each step in the method embodiment provided in the present application can be completed by an integrated logic circuit of the hardware in the processor or by instructions in the form of software. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor. The software module can be located in a storage medium mature 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 the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware. To avoid repetition, it will not be described in detail here.

[0162] In one implementation, the communication device 800 may correspond to the network device in the above-mentioned method embodiment, and may be used to execute the various steps and / or processes performed by the network device in the above-mentioned 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-mentioned method embodiment corresponding to the network device.

[0163] It should be understood that the 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 microcontroller unit (MCU), a programmable logic device (PLD), or other integrated chips.

[0164] It is understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. The non-volatile memory may 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 may be a random access memory (RAM), which is used as an external cache. By way of example and 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.

[0165] An embodiment of the application further 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 for obtaining location data described in the above embodiment.

[0166] The embodiments of the application further provide 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 embodiments.

[0167] The present application also provides a chip system including one or more processors configured to call and execute instructions stored in a memory, thereby executing the method described in the above embodiment. The chip system may be composed of a chip, or may include a chip and other discrete devices. 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.

[0168] In the above embodiments, all or part of the embodiments may be implemented using software, hardware, firmware, or any combination thereof. When implemented using 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, the processes or functions described in the embodiments of the present application are generated in whole or in part.

[0169] In the several embodiments provided in this 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 merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. 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.

[0170] 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.

[0171] In short, the above description is only a preferred embodiment of the technical solution of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this application shall be included in the scope of protection of this application.

Claims

1. A method for obtaining location data, characterized in that: Applied to an artificial intelligence (AI) model, the method includes: Acquiring measurement data and time data, the measurement data including sensor data and wireless signal data, the sensor data being acquired by 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 acquired; 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, the outdoor positioning data represents the location data of the terminal outdoors, the outdoor positioning data is obtained based on the wireless signal data, the interval between the acquisition time of the outdoor positioning data and the first time satisfies a first condition, the first time is the time when the terminal enters the room, the first condition is less than or equal to a preset interval threshold, and the terminal entering the room is determined based on the measurement data and time data.

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

4. The method according to claim 3, characterized in that 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.

5. The method according to claim 3, 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.

6. The method according to claim 3, characterized in that The first position data does not meet the accuracy condition.

7. 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 the 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 the degradation amount 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.

8. 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.

9. 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 obtained 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 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.

10. The method according to claim 1 or 2, characterized in that The training method of the AI ​​model includes: Training the AI ​​model using training data, where any piece of training data includes a location label and feature data; The location tag of the terminal entering the indoor space 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. The interval between the acquisition time of the outdoor positioning data and the first time satisfies a first condition. The first time is the time when the terminal enters the indoor space. The first condition is less than or equal to a preset interval threshold. The location tag of the terminal outdoors is obtained based on the satellite positioning data. The location tag of the terminal indoors is obtained by correcting the short-range signal positioning result using a position offset, and the position offset is obtained based on the sensor data. The feature data includes at least one of sensor data, short-range signal data, cellular communication data, and GNSS data.

11. An electronic device, characterized in that: The electronic device 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 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 is caused to execute 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 run on an electronic device, the electronic device implements the method according to any one of claims 1 to 10.

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