Positioning method and device

Abstract

The embodiment of the invention provides a positioning method and device, and the method comprises the steps that a network device obtains first data and second data, the first data comprises the data of at least one mobile device, and the second data comprises the data of at least one reference station; wherein the mobile equipment meets a first condition, the first condition comprises one or more of the static state of the mobile equipment and the effective carrier phase of the mobile equipment, the data of each mobile equipment comprises the original observation data of the mobile equipment, and the data of each reference station comprises the original observation data of the reference station; and determining target observation data for assisting the user equipment in positioning based on the first data and the second data. According to the method, more (massive) GNSS static data can be effectively obtained with lower cost, and the observation data with higher precision can be obtained through processing and provided for the to-be-positioned equipment, so that the positioning precision of the to-be-positioned equipment can be improved.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a positioning method and apparatus. Background Technology

[0002] Global Navigation Satellite System (GNSS) is an important method for providing absolute position. A GNSS system typically consists of a space constellation, a ground monitoring component, and user equipment components, and features all-weather operation, high efficiency, and wide coverage. To obtain high-precision GNSS differential positioning results, traditional GNSS differential service providers establish a small number of continuously operating GNSS reference stations and send GNSS observation data to a cloud server. The cloud data processing center processes the GNSS observation data and then distributes the generated differential data to mobile users, thereby improving GNSS positioning accuracy.

[0003] However, current positioning schemes require higher accuracy in the GNSS observation data provided by GNSS reference stations, leading to extremely stringent requirements for the construction and configuration of GNSS base stations. For example, the connection between the GNSS reference station and the ground foundation must be physically reinforced to prevent settlement and displacement; the reference station must be equipped with a high-precision, full-mode, full-frequency GNSS receiver to obtain the most comprehensive GNSS observation information; choke coil antennas must be installed to suppress the effects of multipath delay; and high-reliability, low-latency data transmission equipment such as fiber optic cables must be used. Therefore, according to the current positioning scheme, approximately 2,000 to 3,000 high-quality GNSS reference stations would be needed to achieve a nationwide network, resulting in a long construction period and high construction and maintenance costs.

[0004] Therefore, how to obtain high-precision observation data from the Global Positioning and Navigation Satellite System at a relatively low cost to improve the positioning accuracy of user equipment is one of the urgent problems to be solved. Summary of the Invention

[0005] This application provides a positioning method and apparatus. The method can obtain high-precision observation data from a global satellite navigation system at a relatively low cost, which can be provided to a device to be positioned, thereby improving the positioning accuracy of the device.

[0006] Firstly, this application provides a positioning method that can be applied to network devices (e.g., cloud servers), components of network devices (e.g., processors, chips, or chip systems), logical nodes, logical modules, or software capable of implementing all or part of the functions of network devices, or devices used in conjunction with network devices. Taking the application of this method to a network device as an example, the method includes: the network device acquiring first data and second data, the first data including data from at least one mobile device, and the second data including data from at least one base station; wherein the mobile device meets a first condition, the first condition including one or more of the following: the mobile device is in a static state, and the carrier phase of the mobile device is valid; the data from each mobile device includes the original observation data of the mobile device, and the data from each base station includes the original observation data of the base station; then, the network device determines target observation data based on the first data and the second data, and the target observation data is used to assist the user equipment in positioning.

[0007] In this embodiment, the raw observation data may include at least one of the following: pseudorange, carrier phase, carrier phase lock-in identifier information, Doppler information, carrier-to-noise density ratio (C / N0), and carrier phase continuous lock-in time. C / N0 can characterize signal strength, i.e., the quality of satellite signal tracking.

[0008] In the above, the data of each mobile device also includes the local data of the mobile device, and the data of each base station also includes the local data of the base station; the local data may include, but is not limited to, at least one of the following: approximate location information and GNSS module information (e.g., GNSS chip information).

[0009] In this application, not only can the base station report its own data (including satellite observation data) to the network device, but mobile devices can also report their own data (including satellite observation data) to the network device when they are stationary and the carrier phase is valid. As a result, the network device can effectively obtain a large amount of GNSS static data at a low cost, and then process it to obtain high-precision target observation data (also known as GNSS observation data), which is then provided to the device to be positioned to assist in positioning, thereby improving positioning accuracy.

[0010] In one possible implementation, the network device determines the target observation data based on the first data and the second data, including the following steps:

[0011] Step 1: Determine the first region. The first region can refer to a geographical area with a defined size. For example, using a grid system, the city can be divided into grids of size d (in kilometers) * d (in kilometers), which is the first region with an area of ​​d * d, where the symbol "*" represents multiplication.

[0012] Step 2: Based on the first data and the second data, determine at least one valid reference station within the first region; wherein a valid reference station meets one or more of the following conditions:

[0013] (1) The number of effective carrier phases is greater than a first threshold; (2) The number of effective carrier phases is greater than the number of effective carrier phases of a preset number of devices, wherein the preset number of devices is at least one mobile device and a device in the at least one base station; (3) The distance between the device and the adjacent base station is greater than a second threshold; (4) The device is in a static continuous operation state.

[0014] Step 3: Based on the data from at least one valid reference station, determine the target observation data.

[0015] Regarding step two above, in one possible implementation, the network device determines at least one valid base station within the first area based on the first data and the second data, which may include the following:

[0016] When there is no scene change in the first area, the at least one valid base station is determined based on the first data and the second data;

[0017] When there is a scene change in the first area, the at least one valid reference station is determined based on the scene change information and the first and second data;

[0018] The scenario change includes one or more of the following:

[0019] Scenario 1: At least one first mobile device has disappeared within the first area;

[0020] Scenario 2: At least one first reference station has disappeared within the first region;

[0021] Scenario 3: At least one new second mobile device exists within the first area;

[0022] Scenario 4: At least one new second base station exists in the first region.

[0023] In one possible implementation, the network device determines the at least one valid base station based on scene change information and first and second data, including: updating the first and / or second data based on scene change information to obtain third and / or fourth data; and then determining the at least one valid base station based on the third and / or fourth data.

[0024] When scene change information is used to indicate the presence of at least one missing first mobile device and / or at least one first base station within a first area; the network device updates the first data and / or the second data to obtain the third data and / or the fourth data, which may include:

[0025] Delete the data of at least one first mobile device from the first data to obtain the third data; and / or

[0026] The data from at least one first base station is deleted from the second data to obtain the fourth data.

[0027] When scene change information is used to indicate the presence of at least one new second mobile device and / or at least one second base station in the first area; the network device updates the first data and / or the second data to obtain the third data and / or the fourth data, which may include: acquiring the data of the at least one second mobile device and using the first data and the data of the at least one second mobile device as the third data; and / or acquiring the data of the at least one second base station and using the second data and the data of the at least one second base station as the fourth data.

[0028] Through the above implementation method, in the event of equipment changes within the target area, the collected data of the base station and / or mobile equipment can be updated in a timely manner, thereby ensuring the correctness and reliability of the subsequently determined valid base stations.

[0029] Regarding step three above, in one possible implementation, the network device determines the target observation data based on the data from the at least one valid reference station, which may include the following sub-steps:

[0030] Step 1: Determine the location information of at least one valid reference station; Step 2: Based on the location information of at least one valid reference station, determine at least one target reference station from among the at least one valid reference station; Step 3: Based on the location information of at least one target reference station and the data of at least one target reference station, determine the target observation data.

[0031] Regarding step 1 above, in one possible implementation, the network device determines the location information of the at least one valid reference station, which may include: acquiring data from at least one reference station in a first area; and then performing joint positioning calculation based on the data from the at least one reference station and the data from the at least one valid reference station to obtain the location information of the at least one valid reference station.

[0032] Regarding step 2 above, in one possible implementation, the network device determines at least one target base station from the at least one valid base station based on the location information of the at least one valid base station, which may include:

[0033] Based on the location information of at least one valid reference station, the triangulation adjustment method is used to process the information and determine the location error value of the at least one valid reference station. Then, based on the location error value of the at least one valid reference station, at least one valid reference station with a location error value less than a preset error value is selected and used as the at least one target reference station.

[0034] Regarding step 3 above, in one possible implementation, the network device determines target observation data based on the location information of the at least one target reference station and the data of the at least one target reference station, including the following: when it is determined based on the location information of the at least one valid reference station that the at least one valid reference station meets a first condition, the original observation data of the at least one valid reference station is used as target observation data; wherein, the first condition includes the density between the at least one valid reference station being less than a preset value; when it is determined based on the location information of the at least one valid reference station that the at least one valid reference station does not meet the first condition, the target observation data is determined based on the original observation data of the at least one valid reference station.

[0035] In one possible implementation, when the density between the at least one effective reference station is not less than a preset value, the network device can determine target observation data based on the raw observation data of the at least one effective reference station. This can include: determining the ionospheric residual and the tropospheric layer residual in the baseline direction based on the raw observation data of the at least one target reference station; then determining the ionospheric residual and tropospheric residual between the virtual reference station and the third reference station based on the ionospheric residual and the tropospheric layer residual in the baseline direction; wherein the virtual reference station is the central station in the first area, and the third reference station is the reference station closest to the virtual reference station among the at least one reference station; further, based on the ionospheric residual and tropospheric residual between the virtual reference station and the third reference station, and the raw observation data of the third reference station, the virtual observation data of the virtual reference station is determined and used as the target observation data. Through this implementation, virtual observation data from the virtual reference station provided to the device to be located can be effectively obtained to assist the user equipment in achieving positioning.

[0036] In one possible implementation, the method may further include: the network device sending the location information of the at least one target reference station to the device to be located within a first area. This implementation also allows the location information of available reference stations within the first area to be provided to the device to be located for positioning.

[0037] Secondly, this application provides a positioning method that can be applied to a mobile device, or a component of the mobile device (e.g., a processor, chip, or chip system), or a logical node, logical module, or software that can implement all or part of the functions of the mobile device, or a device used in conjunction with the mobile device. Taking the application of this method to a mobile device as an example, the method includes: the mobile device receiving satellite signals and generating raw observation data based on the satellite signals; when the mobile device meets a second condition, sending the data of the mobile device to a network device, wherein the data of the mobile device includes the raw observation data; wherein the second condition includes one or more of the following: the mobile device is in a static state, or the carrier phase of the mobile device is valid.

[0038] In this embodiment, the raw observation data may include at least one of the following: pseudorange, carrier phase, carrier phase lock-in identifier information, Doppler information, carrier-to-noise density ratio (C / N0), and carrier phase continuous lock-in time. C / N0 can characterize signal strength, which is an important indicator of the quality of satellite signal tracking.

[0039] In addition, the data from the mobile device also includes the mobile device’s local data, which may include, but is not limited to, at least one of the following: approximate location information and GNSS module information (such as GNSS chip information).

[0040] In this application, even when the mobile device is stationary and the carrier phase is valid, it can still report its own data (including satellite observation data) to the network device. This allows the network device to effectively obtain a large amount of GNSS static data at a low cost, and then process it to obtain high-precision observation data, which is then provided to the device to be positioned to assist in positioning, thereby improving the positioning accuracy.

[0041] In one possible implementation, the method may further include: the mobile device determining its current state as a stationary state based on one or more of the following data:

[0042] (1) The residual of at least one satellite Doppler observation data in the original observation data; (2) The chassis wheel speedometer data of the mobile device; (3) The inertial measurement unit (IMU) data of the mobile device; (4) The visual data of the mobile device.

[0043] This implementation method allows mobile devices to effectively determine whether they are currently stationary.

[0044] In one possible implementation, the aforementioned raw observation data includes carrier phase observation data; the method may further include: determining that the carrier phase observation data is valid when one or more of the following conditions are met:

[0045] (1) The continuous lock time of the carrier phase is positive; (2) The number of valid carrier phase observations is greater than a preset value, for example, the preset value is 4. The continuous lock time of the carrier phase and the number of valid carrier phase observations can be obtained based on the carrier phase observation data.

[0046] This implementation method enables mobile devices to effectively determine whether their carrier phase is valid.

[0047] Thirdly, this application also provides a communication device, which is a network device or a chip corresponding to a network device. This communication device has the functions to implement the first aspect and any of the possible implementations described above. The communication device can be implemented in hardware or by hardware executing corresponding software. The hardware or software includes one or more units or modules corresponding to the above functions.

[0048] In one possible design, the communication device includes a processor configured to support the communication device in performing corresponding functions of the network device described above. The communication device may also include a memory coupled to the processor, which stores necessary program instructions and data for the communication device. Optionally, the communication device further includes interface circuitry for supporting communication between the communication device and other communication devices, such as the transmission and reception of data or signals. Exemplarily, the communication interface may be a transceiver, circuit, bus, module, or other type of communication interface.

[0049] In one possible design, the communication device includes corresponding functional modules, each used to implement the steps in the above method. The functions can be implemented in hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the functions described above.

[0050] In one possible design, the communication device includes a processing unit and a communication unit, which can perform the corresponding functions in the above method examples, as described in the method provided in the first aspect, and will not be repeated here.

[0051] Fourthly, this application also provides a communication device, which is a mobile device or a chip corresponding to a mobile device. This communication device has the functions to implement the second aspect described above and any of the possible embodiments therein. The communication device can be implemented in hardware or by hardware executing corresponding software. The hardware or software includes one or more units or modules corresponding to the above functions.

[0052] In one possible design, the communication device includes a processor configured to support the communication device in performing corresponding functions of the mobile device described above. The communication device may also include a memory coupled to the processor, which stores necessary program instructions and data for the communication device. Optionally, the communication device further includes interface circuitry for supporting communication between the communication device and other communication devices, such as the transmission and reception of data or signals. Exemplarily, the communication interface may be a transceiver, circuit, bus, module, or other type of communication interface.

[0053] In one possible design, the communication device includes corresponding functional modules, each used to implement the steps in the above method. The functions can be implemented in hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the functions described above.

[0054] In one possible design, the communication device includes a processing unit and a communication unit, which can perform the corresponding functions in the above method examples, as described in the method provided in the second aspect, and will not be repeated here.

[0055] Fifthly, a communication device is provided, including a processor and an interface circuit. The interface circuit is used to receive signals from other communication devices outside the communication device and transmit them to the processor, or to send signals from the processor to other communication devices outside the communication device. The processor is used to implement the methods of the first aspect and any possible implementation thereof through logic circuits or execution code instructions.

[0056] In a sixth aspect, a communication device is provided, including a processor and an interface circuit. The interface circuit is used to receive signals from other communication devices outside the communication device and transmit them to the processor, or to send signals from the processor to other communication devices outside the communication device. The processor is used to implement the methods in the second aspect and any of the possible implementations thereof through logic circuits or execution code instructions.

[0057] In a seventh aspect, a computer-readable storage medium is provided, which stores a computer program or instructions that, when executed by a processor, implement the methods of any one of the first and second aspects and any possible implementation thereof.

[0058] Eighthly, a computer program product storing instructions is provided, which, when executed by a processor, implement the methods of the first and second aspects and any possible implementation thereof.

[0059] A ninth aspect provides a chip system including a processor and potentially a memory for implementing the methods of the first and second aspects and any possible implementation thereof. The chip system may be composed of chips or may include chips and other discrete devices.

[0060] In a tenth aspect, a communication system is provided, the communication system comprising the terminal equipment described in the first aspect and the network equipment described in the second aspect.

[0061] It should be noted that the technical effects that can be achieved by any of the third to tenth aspects or any of the third to tenth aspects can be referred to the description of the technical effects that can be achieved by any of the first and second aspects or any of the first and second aspects, which will not be repeated here. Attached Figure Description

[0062] Figure 1 This application provides a schematic diagram of a positioning scenario.

[0063] Figure 2 This is a schematic diagram of a network RTK.

[0064] Figure 3A , Figure 3B This is a schematic diagram of two positioning systems that can be applied to the embodiments of this application;

[0065] Figure 4 A flowchart illustrating a positioning method provided in an embodiment of this application;

[0066] Figure 5 This is a schematic diagram of the method flow of Embodiment 1 of this application;

[0067] Figure 6A A schematic diagram illustrating the process of determining terminal device shutdown and carrier phase validity in an embodiment of this application;

[0068] Figure 6B A schematic diagram illustrating another process for determining terminal device shutdown and carrier phase validity, provided for an embodiment of this application;

[0069] Figure 7A This is a schematic diagram of the method flow of Embodiment 2 of this application;

[0070] Figure 7B This is a flowchart illustrating the execution of Embodiment 2 of this application;

[0071] Figure 8A This is a schematic diagram of the method flow of Embodiment 3 of this application;

[0072] Figure 8BThis is a flowchart illustrating the execution of Embodiment 3 of this application;

[0073] Figure 9 This is a schematic diagram of the structure of a communication device provided in an embodiment of this application;

[0074] Figure 10 This is a schematic diagram of another communication device provided in an embodiment of this application;

[0075] Figure 11 This is a schematic diagram of a chip device structure provided in an embodiment of this application. Detailed Implementation

[0076] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the embodiments of this application will be further described in detail below with reference to the accompanying drawings.

[0077] The terms, terminology, and features used in the embodiments of this application will be explained below. It should be noted that these explanations are intended to make the embodiments of this application easier to understand and should not be regarded as limiting the scope of protection claimed by this application.

[0078] 1) Pseudorange: This refers to the approximate distance between the receiver and the satellite. Taking the pseudorange of a base station as an example, assuming that the clock of the base station and the clock of the satellite are strictly synchronized, the propagation time of the satellite signal can be obtained by calculating the time when the satellite transmits the signal and the time when the base station receives the signal. Multiplying this by the propagation speed gives the distance between the satellite and the base station. However, there is an unavoidable clock difference between the base station's clock and the satellite's clock, and the satellite signal is also affected by factors such as atmospheric refraction during propagation. Therefore, the distance directly measured by this method is not equal to the true distance between the satellite and the base station, hence the term pseudorange.

[0079] 2) Carrier phase: This refers to the phase difference between the satellite signal received by the receiver and the receiver's local oscillator reference signal. In other words, it's the measured value of the phase of the satellite signal received by the reference station at the same receiving time relative to the phase of the carrier signal generated by the receiver. It boasts high precision and stability, achieving centimeter-level accuracy, and is unaffected by receiver clock differences. However, carrier phase measurements contain unknown periodicity ambiguity, making absolute positioning impossible. But combining it with pseudorange can achieve even better positioning results.

[0080] Pseudorange and carrier phase are two fundamental distance measurements in GPS receivers, and they play different roles in positioning technology.

[0081] The main differences between carrier phase and pseudorange lie in their measurement accuracy, whether they contain ambiguity, and whether they can achieve absolute positioning. Carrier phase has higher accuracy and stability, but it requires solving the problem of periodic ambiguity to achieve single-point absolute positioning; while pseudorange, although less accurate, can achieve absolute positioning and is not affected by periodic ambiguity.

[0082] 3) Receiving frequency: This refers to the frequency at which the receiver receives the satellite signal. For example, satellite signals may include three carrier frequency bands: L1, L2, and L5. The frequency f1 of the L1 carrier band is 1575.42MHz, the frequency f2 of the L2 carrier band is 1227.6MHz, and the frequency f5 of the L5 carrier band is 1176.45MHz. It's understandable that from the satellite's perspective, the receiving frequency can be replaced by the transmitting frequency.

[0083] It should be noted that the data types contained in the raw observations acquired by different devices may be the same or different, and this application does not impose any restrictions. Furthermore, for the same data type, the specific observation values ​​acquired by different devices may be the same or different, depending on the device's location and the processing capability of its GNSS chip. For example, the pseudorange value in the first raw telemetry measurement may be different from the pseudorange value in the second raw observation measurement.

[0084] 4) Virtual Reference Stations: In practical applications, the base stations providing positioning assistance information for vehicles have distance requirements (e.g., the distance between the base station and the vehicle must be less than 10km). This places extremely high demands on the number of base stations, which is impossible to achieve in many areas. Furthermore, the actual location of the base stations is confidential information, and service providers cannot disclose it to users of positioning devices. To address these issues, virtual reference stations (VRS) technology was introduced. VRS is a type of network RTK. Its basic principle is as follows: a certain number of base stations are set up within a specific area. The base stations receive satellite signals and transmit the obtained raw observations to network equipment. The network equipment then "virtually" creates a reference station near these base stations (e.g., three adjacent base stations). Like base stations, virtual reference stations have definite location information and corresponding raw observations. However, the difference is that the location of a virtual reference station is determined based on the location of the base stations, and the raw observations of a virtual reference station are simulated and calculated based on the raw observations of the base stations. The raw observations of the virtual reference station can be the same as those of the base station and can be broadcast as positioning assistance information to the device to be positioned.

[0085] Understandably, when network devices calculate the raw observations of a virtual reference station, they also need to consider the impact of ionospheric error on the raw observations of the virtual reference station, and therefore need to estimate the ionospheric error of the virtual reference station.

[0086] It should be noted that in the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0087] Furthermore, unless otherwise stated, the ordinal numbers such as "first," "second," or "1," "2," etc. (except in special cases where they represent numerical values) mentioned in the embodiments of this application are used to distinguish multiple objects and are not used to limit the size, content, order, timing, priority, or importance of the multiple objects. For example, "first information" and "second information" are only used to distinguish different phase information and do not indicate a difference in the size, priority, or importance of these two pieces of information.

[0088] It should be noted that, in this application, the terms "exemplary" or "for example" are used to indicate that something is being described as an example, illustration, or illustration. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0089] The terms "comprising" and "having," and any variations thereof, used in the following description of embodiments of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices. Furthermore, the term "for indicating" used in the description of embodiments of this application can include both direct and indirect indication. When describing an indication message for indicating A, it may include whether the indication message directly indicates A or indirectly indicates A, but does not necessarily mean that the indication message carries A.

[0090] The preceding text introduced some of the terms / terms used in the embodiments of this application. The following text introduces the technical background of the embodiments of this application.

[0091] In Global Navigation Satellite System (GNSS) positioning technology, such as Figure 1 As shown, the satellite operates at an altitude of approximately 20,000 kilometers above the Earth's surface. During transmission from the satellite to the ground, the satellite signal must pass through the ionosphere (thousands of kilometers above the ground) and the troposphere (60 kilometers above the ground). When the satellite signal passes through the ionosphere, the ionosphere interferes with its propagation, resulting in ionospheric errors in the signal reaching the ground. These ionospheric errors can be represented by the total ionospheric electron content (TEC). However, in practical applications, ionospheric errors can be represented in other ways, and this application does not impose any limitations on this representation.

[0092] Ionospheric interference is frequency-dependent on satellite signals. An ionospheric error model can be constructed based on dual-frequency signals (e.g., L1, L2, or L1, L5) to minimize this interference, significantly improving positioning accuracy. However, when the ionosphere is highly active due to solar influence, the dual-frequency signal-based error model cannot eliminate higher-order residuals, leading to larger positioning errors. In such cases, a more complex model using three-frequency signals (e.g., L1, L2, L5) can be constructed to eliminate higher-order effects.

[0093] Typically, information such as pseudorange, carrier phase, and receiver frequency (or satellite transmission frequency) is of significant value for ionospheric error estimation. In practical applications, this information can be used as positioning aids for positioning calculations.

[0094] Furthermore, to eliminate ionospheric errors, network RTK, also known as base station RTK, is a new technology built upon conventional RTK and the Global Navigation Satellite System (GNSS). Network RTK typically involves establishing multiple (usually three or more) base stations within a region to form a mesh coverage. Using one or more of these base stations as a reference, positioning assistance information (such as pseudorange, carrier phase, and receiving frequency) is calculated and broadcast to provide real-time corrections for the positioning information of users within the region. This method is also called multi-base station RTK.

[0095] Figure 2A schematic diagram of network RTK is shown. Network devices (such as a cloud service platform of a positioning service provider, or a data processing center) can acquire raw observations from one or more base stations, then determine ionospheric errors based on these raw observations, and determine positioning assistance information based on the ionospheric errors. This positioning assistance information is then distributed to the device to be positioned (such as a vehicle) via a roadside unit (RSU). When performing high-precision positioning, a vehicle can combine the positioning assistance information with its own raw observations and navigation messages acquired through a GNSS module, and calculate its own position information using algorithms such as real-time kinematic (RTK) and dead reckoning (DR).

[0096] As described above, Global Positioning and Navigation Satellite System (GNSS) is an important method for providing absolute position. A GNSS system generally consists of a space constellation, a ground monitoring component, and user equipment components, and features all-weather operation, high efficiency, and wide coverage. To obtain high-precision GNSS differential positioning results, traditional GNSS differential service providers establish a small number of continuously operating GNSS reference stations and send GNSS observation data to a cloud server. The cloud data processing center processes the GNSS observation data and then distributes the generated differential data to mobile users, thereby improving GNSS positioning accuracy.

[0097] However, current positioning schemes require higher accuracy in the GNSS observation data provided by GNSS reference stations, leading to extremely stringent requirements for the construction and configuration of GNSS base stations. For example, the connection between the GNSS reference station and the ground foundation must be physically reinforced to prevent settlement and displacement; the reference station must be equipped with a high-precision, full-mode, full-frequency GNSS receiver to obtain the most comprehensive GNSS observation information; a choke coil antenna must be installed to suppress the effects of multipath delay; and high-reliability, low-latency data transmission equipment such as fiber optic cables must be used. Therefore, according to the current positioning scheme, approximately 2,000 to 3,000 high-quality GNSS reference stations would be needed to achieve a nationwide network. Clearly, this not only results in a long construction period but also high construction and maintenance costs.

[0098] To address the aforementioned problems, this application provides a positioning method and apparatus. This method can obtain high-precision observation data from a global satellite navigation system at a relatively low cost, which can be provided to a device to be positioned, thereby improving the positioning accuracy of the device. The method and apparatus are based on the same inventive concept. Since the principles by which the method and apparatus solve the problems are similar, their implementations can be mutually referenced, and repeated details will not be elaborated further.

[0099] The technical solutions provided in this application are applicable to scenarios including, but not limited to, automated driving (AD), assisted driving, or manual driving scenarios. In these scenarios, the vehicle can receive satellite signals from satellites and perform positioning based on these signals. For example, as... Figures 1-2 The scene shown.

[0100] It should be noted that, Figures 1-2 The scenario shown is merely an example. Besides vehicles, the technical solutions provided in this application can be applied to any other terminal or mobile device with satellite positioning capabilities. For example, the terminal / mobile device can be a smart device with satellite positioning capabilities, including but not limited to: smart home devices such as televisions, robot vacuums, and video surveillance systems; smart transportation equipment such as cars, ships, drones, trains, freight cars, and trucks; and smart manufacturing equipment such as robots, industrial equipment, smart logistics, and smart factories. Alternatively, the terminal / mobile device can also be a portable electronic device with satellite positioning capabilities, such as mobile phones, tablets, PDAs, headphones, speakers, wearable devices (such as smartwatches), in-vehicle devices, virtual reality devices, and augmented reality devices.

[0101] Figures 3A-3B Several positioning system architecture diagrams applicable to embodiments of this application are shown.

[0102] like Figure 3A As shown, the system may include satellites, base stations, network equipment, and mobile devices.

[0103] Among them, satellites include, but are not limited to, GPS satellites and BeiDou satellites, which can transmit GNSS satellite signals.

[0104] Mobile devices: These can be called mobile GNSS device terminals. Mobile GNSS devices include GNSS radio frequency antennas, GNSS baseband processing chips, microcontroller units (MCUs) and other data processing units, and data transmission units using fourth-generation (4G) or fifth-generation (5G) communication technologies or future communication technologies.

[0105] Mobile devices can be used to receive satellite signals and obtain corresponding raw observations; they can also provide the raw observations they obtain to network devices. The number of mobile devices can be one or more, and this application does not limit this.

[0106] In this embodiment of the application, the mobile device may also be a user device or a terminal device.

[0107] Base station: Also known as GNSS static base station equipment, it includes GNSS radio frequency antenna, GNSS baseband processing chip, MCU and other data processing units, 4G / 5G / fiber and other network data transmission units, etc.

[0108] A base station can be used to receive satellite signals and obtain corresponding raw observations, and can also provide the raw observations it obtains to network equipment (or cloud servers). The number of base stations can be one or more, and this application does not limit this.

[0109] As is understood, the raw observations mentioned in this article can also be referred to as raw observation data, satellite observation data, etc.; raw observations are observation data obtained by a receiver (such as a base station and / or mobile device) from observations of certain satellites in a global satellite navigation system (such as GPS), and can be obtained by processing satellite signals by the receiver's GNSS chip (or GNSS board). In the embodiments of this application, the data types in the raw observations include, but are not limited to, pseudorange, carrier phase, and receiving frequency.

[0110] Network equipment can be a cloud-based data processing unit, requiring the ability to process massive amounts of data and transmit / receive network data. For example, network equipment can be a cloud service platform (or cloud server) for a location service provider. The cloud-based data processing unit can use communication devices such as 4G / 5G to send virtual GNSS satellite observation data to mobile terminals / devices, providing differential services for mobile GNSS terminals / devices.

[0111] also, Figure 3A The system shown may also include a device to be located and a roadside unit (RSU). The device to be located can receive satellite signals and obtain corresponding raw observations, such as third raw observations (understandably, when the aforementioned mobile device is the device to be located, the third raw observation is also called the first raw observation). The device to be located can perform positioning calculations based on its own raw observations and positioning assistance information sent by network devices.

[0112] The RSU can be any device capable of communicating with the device to be located or network devices, such as a base station or user equipment. This application does not impose specific limitations on this. The RSU can receive positioning assistance information from the network device and forward it to the device to be located. Furthermore, the RSU can also act as a relay station for signals transmitted by other devices; for example, a base station can transmit raw observations to network devices via the RSU, and this application does not impose any limitations.

[0113] In one possible design, the device to be located can be a mobile device; in other words, the device to be located can provide the raw observations it obtains to the network device.

[0114] In practical applications, if the mobile device and the device to be located are different devices, the mobile device and / or the device to be located can provide the network device with raw observations, and this application does not impose any restrictions.

[0115] like Figure 3B As shown, this is a schematic diagram of another positioning system provided in an embodiment of this application, which differs from the one described above. Figure 3A The system shown allows the device to be located (mobile device) to provide its raw observation data to the network device.

[0116] Understandably, in practical applications, when the mobile device and the device to be located are different devices, only the mobile device or the device to be located may provide raw observation data to the network device, or both the mobile device and the device to be located may provide raw observation data to the network device simultaneously. This application does not impose any restrictions on this.

[0117] Understandably, the above Figures 3A-3B The devices in the positioning system shown (such as satellites, base stations, network devices, mobile devices, devices to be located, and RSUs) are merely examples. In actual applications, the system may also include other devices, such as network devices for providing navigation maps and other applications. Furthermore, this application does not specify the number of each device in the above system.

[0118] The positioning system architecture or network architecture and business scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of communication systems or network architectures and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application can also be applied to similar technical problems.

[0119] In this application, "send" and "receive" refer to the direction of information / data / signal transmission. For example, "send information to XX" can be understood as the destination of the information being XX, and "send information" can include direct transmission or indirect transmission through other units or modules. "Receive information from YY" can be understood as the source of the information being YY, and "receive information" can include receiving directly from YY or receiving indirectly from YY through other units or modules. Furthermore, "send" can also be understood as the "output" of a chip interface, and "receive" can be understood as the "input" of a chip interface. In other words, "send" or "receive" can occur between devices, such as a base station and a terminal transmitting or receiving data via an air interface. "Send" or "receive" can also occur within a device, such as transmitting or receiving data between components, modules, chips, software modules, or hardware modules within a device via a bus, wiring, or interface.

[0120] It should be understood that the names of the messages (or information) in the following processes in this application are merely examples. As communication technology evolves, the names of the messages (or information, etc.) in the following processes may change. However, regardless of how the names change, as long as their meaning is the same as the function or meaning of the messages (or information, etc.) in this application, they all fall within the protection scope of this application. For example, "raw observation data" can be replaced with "satellite observation data," "GNSS observation data," etc.

[0121] The solutions of the embodiments of this application will be described below.

[0122] This application provides a positioning method, which can be applied to, but is not limited to, positioning methods. Figures 3A-3B The system architecture shown is illustrated. This method can be executed by a network device (or mobile device), a module of the network device (or mobile device) (e.g., a processor, chip, or chip system), or a logical node, logical module, or software capable of implementing all or part of the functions of the network device (or mobile device). Furthermore, this application does not specifically limit the specific structure of the execution subject (network device, mobile device) or the number of each execution subject of the method provided in the embodiments of this application, as long as communication can be performed according to the method provided in the embodiments of this application by running a program that records the code of the method provided in the embodiments of this application.

[0123] For ease of description, the following description uses the interaction between a network device and a mobile device as an example. The order of the steps in the following processes is merely illustrative; in actual applications, the execution order of the steps in each process can be adjusted, and all or some of the steps described below can be executed adaptively.

[0124] See Figure 4 As shown, the method provided in this application embodiment may include the following:

[0125] S401: Satellite signals received by mobile devices and the generation of raw observation data.

[0126] In this embodiment, the raw observation data may include at least one of the following: pseudorange, carrier phase, carrier phase lock-in identifier information, Doppler information, carrier noise density ratio (C / N0), and carrier phase continuous lock-in time. C / N0 can characterize signal strength, i.e., the quality of satellite signal tracking.

[0127] Raw observation data from mobile devices can also be referred to as satellite observation data from mobile devices. The satellites mentioned in this application can refer to satellites capable of transmitting GNSS satellite signals, such as GPS satellites and BeiDou satellites.

[0128] S402: When the mobile device meets the first condition, the mobile device sends data to the network device, the data including raw observation data. For example, the network device may be, but is not limited to, a cloud server.

[0129] The first condition mentioned above may include one or more of the following conditions:

[0130] (1) The mobile device is in a static state; (2) The carrier phase of the mobile device is valid.

[0131] In addition, the data from the mobile device also includes the mobile device’s local data, which may include, but is not limited to, at least one of the following: approximate location information and GNSS module information (such as GNSS chip information).

[0132] Regarding the above condition (1), in one possible implementation, the method may further include: the mobile device can determine its current state as a stationary state based on one or more of the following data:

[0133] (1) The residual of at least one satellite Doppler observation data in the original observation data; (2) The chassis wheel speedometer data of the mobile device; (3) The inertial measurement unit (IMU) data of the mobile device; (4) The visual data of the mobile device.

[0134] Regarding condition (2) above, in one possible implementation, the original observation data includes carrier phase observation data; the method may further include: when one or more of the following conditions are met, the mobile device can determine that the carrier phase observation data is valid:

[0135] (1) The continuous lock time of the carrier phase is positive; (2) The number of valid carrier phase observations is greater than a preset value, for example, the preset value is 4. The continuous lock time of the carrier phase and the number of valid carrier phase observations can be obtained based on the carrier phase observation data.

[0136] The above S401-S402 describes how a mobile device reports data to a network device (e.g., a cloud server) using a single mobile device as an example. In practical applications, there may be one mobile device or multiple (or a massive number) mobile devices. These mobile devices can refer to the methods shown in S401-S402 to determine whether they meet the conditions for reporting data to the network device (such as the second condition mentioned above), and then report the data if the conditions are met. Accordingly, the network device obtains / receives data from at least one mobile device (hereinafter collectively referred to as the first data).

[0137] S403: The base station receives satellite signals and generates raw observation data.

[0138] Similarly, in this application, the raw observation data of the reference station may include at least one of the following: pseudorange, carrier phase, carrier phase lock identification information, Doppler information, carrier noise density ratio (C / N0), and carrier phase continuous lock time.

[0139] The raw observation data of the base station can also be referred to as the satellite observation data of the base station. The satellite mentioned in this application can refer to a satellite capable of transmitting GNSS satellite signals, such as GPS satellites, BeiDou satellites, etc.

[0140] S404: The base station sends its data to the network device, which includes the base station's raw observation data.

[0141] In addition, the data from the base station also includes local data from mobile devices, which may include, but is not limited to, at least one of the following: approximate location information and GNSS module information (such as GNSS chip information).

[0142] The above S403-S404 uses a single base station as an example to illustrate how it reports data to a network device (such as a cloud server). In practical applications, there may be one base station or multiple (or a massive number) base stations. These base stations can all report their own data to the network device in the manner shown in S403-S404. Accordingly, the network device will receive data from at least one base station (hereinafter referred to as the second data).

[0143] Furthermore, the data reported by the mobile device to the network device (S401-S402 above) and the data reported by the base station to the network device (S403-S404 above) can be executed synchronously or asynchronously, and there is no limitation on the order of execution.

[0144] S405: The network device determines the target observation data based on the first data and the second data; the target observation data is used to assist the device to be located in positioning.

[0145] In one possible implementation, when a network device (e.g., a cloud server) executes S405 (determining target observation data based on first and second data), it may include the following steps:

[0146] Step 1: Determine the first area.

[0147] The first region can refer to a geographical area with a defined area. For example, using a grid system, a city can be divided into grids of size d (in kilometers) * d (in kilometers), which is the first region with an area of ​​d * d.

[0148] Step 2: Based on the first data and the second data, determine at least one valid reference station within the first region; wherein a valid reference station may satisfy one or more of the following conditions:

[0149] (1) The number of effective carrier phases is greater than a first threshold; (2) The number of effective carrier phases is greater than the number of effective carrier phases of a preset number of devices, wherein the preset number of devices is at least one mobile device and a device in the at least one base station; (3) The distance between the device and the adjacent base station is greater than a second threshold; (4) The device is in a static continuous operation state.

[0150] Step 3: Based on the data from at least one valid reference station, determine the target observation data.

[0151] Regarding step two above, in one possible implementation, the network device determines at least one valid base station in the first area based on the first data and the second data. This may include: when there is no scene change in the first area, determining the at least one valid base station based on the first data and the second data; when there is a scene change in the first area, determining the at least one valid base station based on the scene change information and the first data and the second data.

[0152] In this application embodiment, the scene change may include, but is not limited to, one or more of the following situations:

[0153] Scenario 1: At least one first mobile device has disappeared within the first area;

[0154] Scenario 2: At least one first reference station has disappeared within the first region;

[0155] Scenario 3: At least one new second mobile device exists within the first area;

[0156] Scenario 4: At least one new second base station exists in the first region.

[0157] In one possible implementation, when a scene change occurs in the first area, the network device determines the at least one valid base station based on the scene change information and the first and second data, including: first updating the first and / or second data based on the scene change information to obtain the third and / or fourth data; and then determining the at least one valid base station based on the third and / or fourth data.

[0158] When scene change information is used to indicate that at least one first mobile device and / or at least one first base station has disappeared in the first area; the network device updates the first data and / or the second data to obtain the third data and / or the fourth data, which may include: deleting the data of the at least one first mobile device from the first data to obtain the third data; and / or deleting the data of the at least one first base station from the second data to obtain the fourth data.

[0159] When scene change information is used to indicate the presence of at least one new second mobile device and / or at least one second base station in the first area; the network device updates the first data and / or the second data to obtain the third data and / or the fourth data, which may include: acquiring the data of the at least one second mobile device and using the first data and the data of the at least one second mobile device as the third data; and / or acquiring the data of the at least one second base station and using the second data and the data of the at least one second base station as the fourth data.

[0160] Regarding step three above, one possible implementation involves the network device (e.g., a cloud server) determining the target observation data based on data from at least one valid reference station, which may include the following steps:

[0161] Step 1: The network device determines the location information of the at least one valid reference station;

[0162] Regarding step 1 above, in one possible implementation, the network device determines the location information of the at least one valid reference station, which may include: acquiring data from at least one reference station in a first area; and then performing joint positioning calculation based on the data from the at least one reference station and the data from the at least one valid reference station to obtain the location information of the at least one valid reference station.

[0163] The data from the reference station mentioned above includes the location information of the reference station.

[0164] Step 2: Based on the location information of the at least one valid reference station, the network device determines at least one target reference station from the at least one valid reference station.

[0165] Regarding step 2 above, in one possible implementation, the network device determines at least one target reference station from the at least one valid reference station based on the location information of the at least one valid reference station. This may include: processing the location information of the at least one valid reference station using a triangulation adjustment method to determine the location error value of the at least one valid reference station; and then, based on the location error value of the at least one valid reference station, selecting at least one valid reference station whose location error value is less than a preset error value, and using it as the at least one target reference station.

[0166] Step 3: The network device determines the target observation data based on the location information of the at least one target reference station and the data of the at least one target reference station.

[0167] Regarding step 3 above, in one possible implementation, the network device determines target observation data based on the location information of the at least one target reference station and the data of the at least one target reference station, including: when it is determined based on the location information of the at least one valid reference station that the at least one valid reference station meets a second condition, the original observation data of the at least one valid reference station is used as target observation data; wherein, the second condition includes the density between the at least one valid reference station being less than a preset value; when it is determined based on the location information of the at least one valid reference station that the at least one valid reference station does not meet the above second condition, the target observation data is determined based on the original observation data of the at least one valid reference station.

[0168] When the second condition is not met between at least one valid reference station, in one possible implementation, the network device determines the target observation data based on the raw observation data of the at least one valid reference station. This may include: determining the ionospheric residual and the tropospheric layer residual in the baseline direction based on the raw observation data of the at least one target reference station; then determining the ionospheric residual and the tropospheric residual between the virtual reference station and the third reference station based on the ionospheric residual and the tropospheric layer residual in the baseline direction; wherein the virtual reference station is the central station in the first region, and the third reference station is the reference station closest to the virtual reference station among the at least one reference station; further, determining the virtual observation data of the virtual reference station based on the ionospheric residual and the tropospheric residual between the virtual reference station and the third reference station, as well as the raw observation data of the third reference station, and using this as the target observation data.

[0169] In one possible implementation, the method may further include: the network device sending the location information of the at least one target base station to a terminal device in the first area.

[0170] In summary, this application provides a positioning method, which includes: a network device acquiring first data and second data, wherein the first data includes data from at least one mobile device, and the second data includes data from at least one base station; wherein the mobile device meets a first condition, the first condition including one or more of the following: the mobile device is in a static state, and the carrier phase of the mobile device is valid; the data of each mobile device includes the original observation data of the mobile device, and the data of each base station includes the original observation data of the base station; and then, based on the first data and the second data, target observation data is determined, which is used to assist the user equipment in positioning. In this application's method, not only can the base station report its own data (including satellite observation data) to the network device, but the mobile device, when it is in a static state and the carrier phase is valid, can also report its own data (including satellite observation data) to the network device. This allows the network device to effectively obtain a large amount of GNSS static data at a lower cost, thereby processing it to obtain higher-precision observation data, which is then provided to the device to be positioned, thus improving the positioning accuracy of the device (the positioning accuracy can reach the decimeter (dm) or centimeter (cm) level).

[0171] The above will be explained through several specific implementation methods. Figure 4 The proposed solution will be described in detail.

[0172] Implementation Method 1:

[0173] In implementation method one, based on the above... Figure 4 The scheme shown will be described in detail in steps S402 to S404, namely the end-side device (hereinafter referred to as the terminal device, i.e. the above-mentioned) Figure 4 (Example of a mobile device in the illustrated scheme) meets the preset conditions (as described above) Figure 4 When the first condition in the illustrated scheme is met, data can also be sent to the cloud server (as described above). Figure 4 The example network device in the scheme shown reports its own data in a specific way, so that the cloud server can not only obtain GNSS data from the base station (as mentioned above) Figure 4 The original observation data from the base station in the illustrated scheme can also be obtained through end-side equipment (the aforementioned...). Figure 4 The original observation data of the mobile device in the scheme shown is used as the data of the base station, that is, the data reported by the end device is used as the data of the base station.

[0174] See Figure 5 As shown, the method of Implementation Method 1 includes the following steps:

[0175] S501: The terminal equipment receives satellite signals and generates satellite observation data (as described above). Figure 4Example of raw observation data from the mobile device in the illustrated scheme).

[0176] In this application embodiment, the satellite observation data obtained by the terminal device (i.e., the above-mentioned) Figure 5 The raw observation data of the mobile device in the scheme shown may include: pseudorange, pseudorange valid identifier, carrier phase, carrier phase lock identifier, Doppler, carrier noise density ratio (C / N0), carrier phase continuous lock time, etc.

[0177] In this application, "satellite" can refer to a satellite capable of transmitting GNSS satellite signals, such as GPS satellites, BeiDou satellites, etc., and the number of satellites is not limited.

[0178] S502: Based on the satellite observation data, the terminal equipment determines whether it is in a static state and whether the carrier phase is valid.

[0179] In this application embodiment, the terminal device can determine whether it is currently in a static state in one or more of the following ways, but is not limited to:

[0180] Method a, using Doppler data for stopping (determining stop):

[0181] Satellite Doppler observations in the satellite observation data of the terminal equipment can conform to the following formula:

[0182]

[0183] Assuming the terminal equipment is stationary, the Doppler residuals for each satellite can be obtained according to the following formula:

[0184]

[0185] In the above, These are the Doppler residual values. For Doppler observations, r is the identifier / number of the mobile device, s is the identifier / number of the satellite, and v is the value of the satellite. s The velocity v represents the speed at which the satellite moves. s It can be obtained from ephemeris information, v r Here, c represents the speed of the terminal device / receiver, e represents the direction vector from the satellite to the receiver, df represents the receiving frequency correction term caused by receiver clock instability (which needs to be estimated), and ε represents Doppler measurement noise; the symbol "*" represents the multiplication sign.

[0186] When a terminal device determines that a certain number (preset number) of satellite Doppler residuals are distributed in a zero-mean white noise pattern, it can confirm that it is currently stationary; otherwise, it can confirm that it is currently non-stationary (i.e., it may be moving).

[0187] Method b: Stopping method based on wheel speed data:

[0188] If the terminal device has wheel speed meter data of the vehicle chassis (for example, the terminal device is a vehicle), the terminal device can determine whether the value of the wheel speed meter is less than a preset threshold (small value) based on the wheel speed meter data. If the value of the wheel speed meter is less than the preset value (small value), it can confirm that it is currently stationary; otherwise, it can confirm that it is currently non-stationary (i.e., it may be moving).

[0189] Method c: Stop (determine stop) method using inertial measurement unit (IMU) data:

[0190] If the terminal device has inertial measurement unit (IMU) data, the terminal device can determine whether the IMU data output is in a white noise state and whether the standard deviation is less than a preset threshold. If the terminal device's IMU data output is in a white noise state and the standard deviation is less than the preset threshold, it can confirm that it is currently stationary; otherwise, it can confirm that it is currently in a non-stationary state (i.e., it may be moving).

[0191] Method d: Using visual data for stopping (judging stop):

[0192] If a terminal device (such as a mobile phone) has a camera and can obtain its visual data, the terminal device can obtain the data of the previous and next frames of the camera. Based on the data of the previous and next frames of the camera, it can determine whether the frame difference between the previous and next frames is less than a set threshold. If the frame difference between the previous and next frames is less than the set threshold, it can be confirmed that it is currently in a stationary state; otherwise, it can be confirmed that it is currently in a non-stationary state (i.e., it may be moving).

[0193] In this application embodiment, the terminal device determines whether its own carrier phase is valid, which can be achieved in ways including but not limited to the following:

[0194] Typically, each carrier phase observation value for a satellite is accompanied by a validity flag and a continuous lock time. Therefore, the terminal device can determine that the continuous lock time is positive and the number of valid carrier phase observation values ​​is greater than 4 (i.e., the carrier phase observation values ​​of 4 satellites are valid) based on the carrier phase observation values ​​in its own satellite observation data. If so, the terminal device can confirm that its own carrier phase observation data or carrier phase is valid; otherwise, the terminal device confirms that its own carrier phase is invalid.

[0195] In S502, the terminal device can first determine whether it is stationary based on the Doppler data in the satellite observation data using the Doppler method. If it is stationary, the terminal device then determines whether its carrier phase is valid. If valid, it can upload its satellite observation data (such as pseudorange, pseudorange validity indicator, carrier phase, carrier phase lock indicator, Doppler, C / N0, carrier phase continuous lock time, etc.) and local data to the cloud server. The local data of the terminal device can include the approximate location coordinates of the terminal device (a rough or possible location coordinate of the terminal device in the area) and the GNSS chip information of the terminal device (such as manufacturer and firmware version information).

[0196] S503: When the terminal device is in a static state and the carrier phase is valid, the terminal device will report its own data to the cloud server.

[0197] If the terminal device meets the above two conditions (i.e., it is in a stationary state and the carrier phase is valid), the terminal device can report its current satellite observation data and local data to the cloud server.

[0198] If the terminal device does not meet the above two conditions (i.e., the terminal device is in a non-stationary state and / or the carrier phase is invalid), it may not report satellite observation data and local data to the cloud server.

[0199] In S501 to S503 above, terminal equipment refers to terminal equipment including a GNSS module, and the number of such terminal equipment is not limited; it can be one or more (or a large number). Furthermore, each terminal equipment can execute the steps shown in S501 to S503 above. That is, after generating satellite observation data, if the static state is met and the carrier phase is valid, the terminal equipment can report its own satellite observation data to the cloud server. In addition, these terminal equipment can also report local data, such as the approximate location coordinates of the terminal equipment and GNSS chip information (e.g., manufacturer, firmware version information), to the cloud server.

[0200] For example, regarding steps S502 to S503 above, the embodiments of this application provide the following schematic diagrams of determination processes:

[0201] Example 1: Figure 6AThe document illustrates a determination process where, if the terminal device does not have sensors other than GNSS, it can use Doppler data to determine whether it is stationary. This involves using Doppler observation data from satellite observations to determine if the device is stationary. If stationary, the document further determines if the carrier phase is valid. If the carrier phase is valid, the device reports its satellite observation data and local data (such as approximate coordinates and GNSS chip information) to the cloud server.

[0202] Example 2: Figure 6B Another determination process is shown. If the terminal device has sensors other than GNSS, it can use one or more of the following methods to determine whether it is stationary: Doppler data determination method, visual data determination method, wheel speed data determination method, and IMU data determination method. If it is confirmed that it is stationary, it further determines whether its carrier phase is valid. If the carrier phase is valid, it reports its satellite observation data and local data (such as approximate coordinates, GNSS chip information, etc.) to the cloud server.

[0203] S504: The base station generates satellite observation data based on the received satellite signals (as described above). Figure 4 (Example of raw observation data from the base station in the illustrated scheme).

[0204] S505: The base station reports its own data to the cloud server.

[0205] In S504 and S505 above, a reference station refers to a reference station that includes a GNSS module. The number of such reference stations is not limited; there can be one or more (or a large number). Each reference station can follow the steps shown in S504 and S505, that is, after generating satellite observation data, the reference station reports it to the cloud server. In addition, each reference station can also report local data, such as the approximate location coordinates of the reference station and GNSS chip information (manufacturer, firmware version information), to the cloud server.

[0206] In the embodiments of this application, the terminal device (i.e., S501 to 503) reporting data to the cloud server and the base station (i.e., S504 to S505) reporting data to the cloud server can be performed synchronously or asynchronously, and the order of execution is not specifically limited.

[0207] In the first embodiment of this application, not only can the base station report its own data (including satellite observation data and local data) to the cloud server, but the end-side equipment (i.e., the terminal equipment) can also report its own data (including satellite observation data and local data) to the cloud server when it is stationary and the carrier phase is valid. This allows the cloud server to obtain or collect a large amount of GNSS static data. Therefore, in the method of this application, the cloud server can collect static GNSS data from the terminal equipment through crowdsourcing to serve as data for the GNSS base station. Furthermore, the cloud server can use the GNSS data from the terminal equipment to determine its own motion state without relying on other external sensors, thus obtaining a large amount of GNSS base station data at a lower cost.

[0208] Implementation Method Two:

[0209] In the second implementation method, the main focus is on Figure 4 The steps in S405 of the scheme are described in detail, namely, the cloud server collects massive amounts of GNSS static data from the base station and the end-side equipment. The GNSS static data includes data reported by the terminal equipment. Figure 4 Example of the first data in the scheme shown) and data reported by the base station ( Figure 4 After the example of the second data in the scheme shown, the collected GNSS static data is preprocessed, and then the processed GNSS static data can be used to obtain an optimized (dense, uniformly distributed reference stations, and uniform quality distribution of observations in each reference station network) GNSS static observation network.

[0210] See Figure 7A As shown, the method flow of Implementation Method Two includes the following steps:

[0211] S701A: The cloud server determines the target area (i.e., the above). Figure 4 (Example of step one in S405 of the scheme shown).

[0212] For example, if a cloud server forms a network based on the massive amount of collected GNSS static data, it can divide the area where the devices from which this massive amount of GNSS static data originates into a grid area of ​​d*d (square kilometers) according to a preset geometric distance d (in kilometers), and use this d*d grid area as the target area. Figure 4 (Example of the first region in the scheme shown).

[0213] S702A: The cloud server is based on collected GNSS static data (as mentioned above). Figure 4Using the first and second data in the scheme shown, determine the M effective reference stations within the target area (a d*d grid area) and the data of these M effective reference stations, where M is a positive integer. (That is, the above...) Figure 4 (Example of step two in S405 of the scheme shown).

[0214] In one possible implementation, the cloud server determines the device with the most effective carrier phases based on the carrier phase data of each device in the collected GNSS static data, and uses it as the effective reference station in the target area (d*d grid area).

[0215] For example, the cloud server determines the device with the most valid carrier phases based on the carrier phase data of each device in the collected GNSS static data, and uses this as the effective reference station in the target area. This can include the following steps:

[0216] Step 1: The cloud server selects satellite observation data (N is a positive integer) reported by N devices within the target area (d*d grid area) from the collected GNSS static data; these N devices include terminal devices and base stations.

[0217] Step 2: The cloud server obtains the carrier phase data of these N devices from the satellite observation data of these N devices.

[0218] Step 3: Based on the carrier phase data of these N devices, the cloud server can determine the number of effective carrier phases corresponding to each of the N devices.

[0219] Whether the carrier phase is valid can be determined in accordance with the method shown in S502 above, that is, the continuous lock time is positive and the effective value of the carrier phase observation is greater than 4 (that is, the carrier phase observation values ​​of 4 satellites are valid).

[0220] Step 4: The cloud server can sort the number of effective carrier phases corresponding to these N devices in ascending order (or descending order).

[0221] Step 5: The cloud server can select the M devices with the most effective carrier phases from the N devices and use these M devices as effective reference stations in the target area (d*d grid area); M is a positive integer less than or equal to N.

[0222] Alternatively, the cloud server can select M devices from the N devices, where the number of effective carrier phases is greater than a set threshold, and use these M devices as effective reference stations within the target area (a d*d grid area).

[0223] For example, the number of effective carrier phases corresponding to device 1 is A1, the number of effective carrier phases corresponding to device 2 is A2, the number of effective carrier phases corresponding to device 3 is A3, ..., and the number of effective carrier phases corresponding to device N is A N .

[0224] Let A1, A2, A3...A N Sort in ascending order, resulting in: A N …A1 <A3<A2。

[0225] From these N devices, select the three devices with the most effective carrier phases, namely A1, A3, and A2, as the effective reference stations within the target area; or

[0226] From these N devices, select 3 devices with a number of effective carrier phases greater than a preset value, such as A1, A3, and A2, which will be used as effective reference stations in the target area.

[0227] If there are one or more statically continuously operating reference stations within the target area (d*d grid area), then these one or more statically continuously operating reference stations can be used as valid reference stations within the target area (d*d grid area).

[0228] In the following steps, the cloud server selects data from the collected GNSS static data to use the data from these M valid reference stations for network formation.

[0229] S703A: The cloud server, based on the distance between M valid base stations in the target area (d*d grid area), deletes the closer base stations from the M valid base stations, and obtains M1 adjacent valid base stations with greater distance and the data of these M1 valid base stations; M1 is a positive integer less than or equal to M.

[0230] In one possible implementation, among the M valid reference stations in the target area (d*d grid area), if the distance between two adjacent reference stations is less than a preset threshold, one or both of these adjacent reference stations can be deleted.

[0231] For example, from M effective base stations in the target area (a grid area of ​​d*d), M1 effective reference stations are selected. These M1 effective reference stations should meet the following condition: the distance between adjacent reference stations exceeds a set threshold (including the set threshold).

[0232] In the following steps, the cloud server selects data from the collected GNSS static data to use the data from these M1 valid reference stations for network formation.

[0233] In S703A, the selected M1 valid reference stations include actual reference stations and / or terminal equipment.

[0234] S704A: The cloud server performs change detection to determine whether there are any device changes (such as adding or removing devices) within the target area (d*d grid area).

[0235] For example, within the target area (a d*d grid area), if one or more of the following conditions exist, it can be confirmed that a device change exists within the target area (a d*d grid area):

[0236] Case 1: Within the target area (d*d grid area), there are base stations that have been removed or withdrawn;

[0237] Scenario 2: A new base station exists within the target area (a d*d grid area);

[0238] Scenario 3: Within the target area (a d*d grid area), there are terminal devices that have been removed or withdrawn;

[0239] Scenario 4: A new terminal device exists within the target area (a d*d grid area).

[0240] S705A: When there is a device change in the target area (d*d grid area), update the M1 valid reference stations and their data to obtain the M2 valid reference stations and their data; where M2 may be an integer value greater than M1, a positive integer less than M1, or equal to M1.

[0241] In one possible implementation, if there are no changing devices within the target area (d*d grid area), the steps of S702A-S703A can be followed to select valid reference stations, and then delete the nearest valid reference stations.

[0242] For example, if there are missing / removed reference stations in the target area (d*d grid area), if the removed / removed reference station belongs to the M1 valid reference stations, then the data of the missing / removed reference station can be deleted from the data of the M1 valid reference stations. If it does not belong to the M1 valid reference stations, then no update will be performed on the data of the M1 valid reference stations.

[0243] If there are newly added reference stations in the target area (d*d grid area), then the effective reference stations can be selected from them in accordance with the method shown in S702A, and then the effective reference stations that are close to the adjacent reference stations can be deleted in accordance with the method shown in S703A.

[0244] If there are removed / withdrawn terminal devices in the target area (d*d grid area), and if these terminal devices belong to the M1 valid base stations, then the data of the removed / withdrawn terminal devices can be deleted from the data of the M1 valid base stations.

[0245] If there are newly added terminal devices in the target area (d*d grid area), then the effective terminal devices can be selected as effective base stations as shown in S702A, and then the effective base stations that are close to the adjacent base stations can be deleted as shown in S703A.

[0246] If a device change occurs within the target area (a d*d grid area), in S705A, the cloud server can update the M1 valid base stations selected in S704A and their data, resulting in M2 valid base stations after change detection. Compared to the M1 valid base stations selected in S703A, the number of M2 valid base stations obtained in step S705A after change detection may be more or less, meaning M2 is greater than M. ′ M1 is an integer, or M2 is a positive integer less than or equal to M1.

[0247] Subsequently, the cloud server can use the updated data from the M2 valid base stations (i.e., crowdsourced base station data) obtained from the S705A to form a network.

[0248] However, in this embodiment, if there is no equipment change in the target area (d*d grid area), S705A can be omitted. Subsequently, the cloud server can use the data of M1 valid base stations (i.e. crowdsourced base station data) obtained in S703A to form a network.

[0249] Figure 7B A schematic diagram illustrating the execution of the process in Implementation Method Two is shown below. Figure 7BAs shown, step 1 involves performing regional gridding, i.e., determining the target area (d*d grid) after gridding; step 2 involves selecting effective reference stations within the target area, i.e., determining the effective reference stations within the target area based on the collected GNSS data; step 3 involves updating / refreshing effective reference stations according to distance intervals, i.e., deleting reference stations that are closer to each other based on the distance between adjacent reference stations; step 4 involves performing change detection within the target area, i.e., detecting whether there are any equipment changes within the target area. If there are equipment changes, the process returns to step 2 to select effective reference stations, then to step 3 to update effective reference stations according to distance intervals, and further to step 4 to perform change detection within the target area. When it is confirmed that there are no equipment changes within the target area, the final effective reference stations and their data are output. The data from the final effective reference stations are used to form a network, thereby obtaining a dense GNSS static observation network with evenly distributed effective reference stations.

[0250] In the second implementation method, the cloud server can filter and network the collected crowdsourced GNSS data, that is, establish a grid-based target area. It can perform change detection on the GNSS reference stations in the target area, support the removal and / or addition of crowdsourced reference stations (reference stations, terminal devices), and then process the GNSS data obtained by low-cost equipment, thereby obtaining high-precision measurement data that meets the requirements of the reference station. Compared with traditional methods, the method of this application can greatly reduce the requirements for GNSS reference station equipment.

[0251] Implementation Method 3:

[0252] In the third implementation method, further... Figure 4 Step 3 of the scheme is described in detail, which is how to use the data of M2 effective reference stations (i.e. crowdsourced base stations) obtained in Implementation Method 2 to determine the precise location coordinates of each effective reference station (with an accuracy of decimeter (dm) or centimeter (cm) level) and generate virtual observation data to send / provide to user equipment in the network to assist them in achieving high-precision positioning (the positioning accuracy can reach the decimeter (dm) or centimeter (cm) level).

[0253] See Figure 8A As shown, the method flow of Implementation Method 3 includes the following:

[0254] S801A: The cloud server determines the precise location coordinates of each effective base station based on data from M2 effective base stations and data from at least one external reference station.

[0255] In one possible implementation, the cloud server can also acquire data from at least one reference station within the target area (including satellite observation data and local data, such as approximate location coordinates, GNSS chip information, etc.).

[0256] Then, the cloud server combines the position coordinates of M2 effective reference stations with the position coordinates of at least one external reference station to perform dynamic real-time kinematic (RTK) online differential calculation to obtain the precise position coordinates of each effective reference station.

[0257] S802A: The cloud server will work with the crowdsourcing benchmark stations to process the data, removing / eliminating the crowdsourcing benchmark stations with excessive errors from the M2 valid benchmark stations, resulting in M3 benchmark stations, where M3 is a positive integer less than or equal to M2.

[0258] For example, the cloud server uses the triangulation adjustment method to measure the position coordinates of these M2 effective reference stations; then, based on the precise position coordinates of these M2 effective reference stations, the position error values ​​of these M2 reference stations are determined; further, from these M2 reference stations, reference stations with larger position error values ​​are removed (for example, reference stations with position error values ​​greater than a preset error value are removed), thereby obtaining M3 reference stations.

[0259] S803A: The cloud server determines whether the density between M3 base stations is greater than a set threshold.

[0260] If the value exceeds the set threshold, then the following steps S804A-S805A can be executed.

[0261] If the value is not greater than the set threshold, after executing S802A, the cloud server can broadcast the data and precise coordinates of these base stations within the target area (d*d grid) to the user equipment according to the principle of proximity, in order to assist the user equipment in achieving accurate positioning.

[0262] For example, the cloud server can determine that the density of the M3 base stations is low if the distance between any adjacent base stations is less than a set threshold, or if the overall distance between adjacent base stations is less than a set threshold, or if there are a large number of base stations that meet the aforementioned conditions (i.e., the distance to adjacent base stations is less than a set threshold). In this case, the cloud server can broadcast / send the satellite observation data and precise location coordinates of the M3 base stations to the target area (d*d grid area) to the positioning device, terminal device, or user device, etc.

[0263] S804A: When the density between M3 base stations is greater than a set threshold, the cloud server calculates the ionospheric residual in the baseline direction based on the data from the M3 base stations, and obtains the tropospheric residual in the baseline direction according to the double-difference observation equation.

[0264] The data from the M3 reference stations includes satellite observation data from the M3 reference stations. The satellite observation data from each reference station includes GNSS satellite pseudorange, pseudorange standard deviation, carrier phase, carrier phase standard deviation, cycle slip identifier, CN0, etc.

[0265] For example, taking two of the M3 base stations as examples, hereinafter referred to as base station A and base station B, the ionospheric residual in the baseline direction between these two base stations can be calculated according to the following formula three:

[0266]

[0267] The double-difference observation equation can conform to the following formula four:

[0268]

[0269] Based on Formula 4 above, the tropospheric residual along the baseline direction can be obtained according to Formula 5 below:

[0270]

[0271] In the above, i and j are the identifiers / numbers of the two satellites, A and B represent the two reference stations (also called stations), 1 and 2 are the subscripts of the frequency points, f1 is the electromagnetic wave frequency of frequency point 1, and f2 is the electromagnetic wave frequency of frequency point 2. This is the double-difference operator, where N is the integer ambiguity, I is the ionospheric error, T is the tropospheric error, and ρ is the geometric distance from the satellite to the receiver. This is the differential Doppler phase.

[0272] S805A: The cloud server determines the ionospheric residual and tropospheric residual between the grid center site and the nearest adjacent site.

[0273] After obtaining the residual delay component in S804, the cloud server establishes a local low-order surface model and uses least-squares surface fitting to obtain the low-order surface parameters. The grid center point is selected as the virtual observation generation site V, and the base station closest to site V (assumed to be site A) is selected. Referring to formulas three and five above, the ionospheric residual between site V and site A is obtained through interpolation. and the tropospheric residuals between station V and station A

[0274] S806A: The cloud server generates virtual observation data for site V. All observations that conform to the following relationship can be used as correct virtual observations.

[0275] The relative values ​​of the Doppler phase (carrier phase observations) of satellite i and satellite j at station V conform to the following formula six:

[0276]

[0277] The relative values ​​of the pseudoranges of satellites i and j at station V conform to the following formula seven:

[0278]

[0279]

[0280] From formulas six and seven above, we can obtain...

[0281] The carrier phase observation value of reference satellite i can be calculated using the distance between the satellite and the ground (i.e., reference satellite i and station V). and pseudorange Furthermore, according to Carrier observations of reference satellite i The carrier phase observation value of satellite j can be obtained. according to pseudorange of reference satellite i The pseudorange of satellite j can be obtained. This allows us to obtain carrier phase observations from all other satellites. Pseudodistance P.

[0282] Through the above S804-S805, the cloud server can determine the distance between the location information of each valid reference station (i.e., crowdsourced reference station, including actual reference stations and mobile devices) and the virtual reference station based on the location information of each valid reference station. It discards satellite observation data of valid reference stations whose distance from the virtual reference station is not less than a preset distance, and only uses satellite observation data of valid reference stations whose distance from the virtual reference station is within the preset distance range.

[0283] S807A: The cloud server broadcasts the generated virtual observation data to the device to be located.

[0284] In this embodiment of the application, the virtual observation data broadcast by the cloud server includes GNSS satellite pseudorange, pseudorange standard deviation, carrier phase, carrier phase standard deviation, cycle slip identifier, carrier noise density ratio (C / N0), etc.

[0285] For example, Figure 8B A schematic diagram of a process structure for Embodiment 3 is shown. See also Figure 8BAs shown, in step 1, the coordinates of the reference station are calculated (see S801A above); in step 2, the reference station with gross errors is eliminated through joint adjustment (see S802A above); in step 3, it is determined whether the density of the current reference station is greater than the threshold. If so, step 4 is executed, that is, the baseline double-difference ionospheric and tropospheric errors are calculated (see S804A above). If not, the satellite observation data and position coordinates of the current reference station are broadcast to the device to be positioned; after step 4, step 5 is executed to fit the ionosphere and laminar residuals of the center of the target area (see S805A above); in step 6, virtual observation data is generated (see S806A above) and then broadcast to the device to be positioned.

[0286] In Implementation Method 3, a joint adjustment method is used to perform quality control on the crowdsourced GNSS reference stations, thereby achieving optimal selection of reference station data. The GNSS reference stations established through crowdsourcing can operate as a standalone network and support access to continuously operating reference stations. They can also be operated as encrypted stations in the existing continuously operating reference stations (CORS) network, effectively solving the problem of reduced service availability of traditional continuously operating reference stations (CORS) networks due to excessive atmospheric propagation delay errors.

[0287] In addition, crowdsourced GNSS data can be used to calculate ionospheric and tropospheric errors and combined with the main reference station in the network to generate virtual GNSS observation data, which can be broadcast to other GNSS terminals in the network for positioning. This can effectively improve the positioning accuracy, enabling the positioning accuracy to reach the decimeter (dm) or centimeter (cm) level.

[0288] Regarding the above-described embodiments one to three, it should be noted that:

[0289] (1) The above-described embodiments one to three can be implemented in part or in whole, or they can be implemented separately, without any specific limitation.

[0290] (2) The above focuses on describing the differences between implementation methods one to three. Except for the differences, implementation methods one to three can be referred to each other.

[0291] (3) The step numbers of the flowcharts described in Embodiments 1 to 3 above are only examples of the execution flow and do not constitute a restriction on the order of execution of the steps. There are no time dependencies between the steps in the various implementations of this application, and there is no strict execution order between them. In addition, not all the steps shown in the flowcharts are mandatory steps. Some steps can be added or deleted based on the actual needs of each flowchart.

[0292] In the embodiments provided above, the methods provided by the embodiments of this application have been described from the perspective of interaction between various devices. To implement the functions of the methods provided in the embodiments or implementations of this application, network devices or mobile devices may include hardware structures and / or software modules, implementing the above functions in the form of hardware structures, software modules, or a combination of hardware structures and software modules. Whether a particular function is executed in the form of hardware structures, software modules, or a combination of hardware structures and software modules depends on the specific application and design constraints of the technical solution.

[0293] The module division in this embodiment is illustrative and represents only one logical functional division; in actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments or implementations of this application can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0294] Similar to the above concept, such as Figure 9 As shown, this application embodiment also provides a communication device 900 for implementing the functions of the network device or mobile device in the above method. For example, the communication device 900 can be a software module or a chip system. In this application embodiment, the chip system can be composed of chips or can include chips and other discrete devices. The communication device 900 may include: a communication unit 901 and a processing unit 902.

[0295] In this embodiment, the communication unit 901, also referred to as the transceiver unit, may include a sending unit and / or a receiving unit, respectively used to perform the sending and receiving steps of the network device or mobile device in the above method embodiments. The processing unit 902 may be used to read instructions and / or data from the storage module so that the communication device 900 implements the aforementioned method embodiments.

[0296] Optionally, the communication device 900 may further include a storage unit 903, which is equivalent to a storage module and can be used to store instructions and / or data.

[0297] The following, combined with Figures 9 to 10 This application provides a detailed description of the communication device provided in its embodiments. It should be understood that the descriptions of the device embodiments correspond to the descriptions of the method embodiments; therefore, any content not described in detail can be found above. Figure 4 and Figure 5 as well as Figures 7A-8A The method shown is used to achieve this, and for the sake of simplicity, it will not be described in detail here.

[0298] The communication unit 901 can also be called a transceiver, transceiver, or transceiver device. The processing unit can also be called a processor, processing board, processing module, or processing device. Optionally, the device in the communication unit 901 used to implement the receiving function can be considered a receiving unit, and the device in the communication unit 901 used to implement the transmitting function can be considered a transmitting unit; that is, the communication unit 901 includes both a receiving unit and a transmitting unit. The communication unit can sometimes also be called a transceiver, transceiver circuit, or transceiver unit. The receiving unit can sometimes be called a receiver, receiver, or receiving circuit. The transmitting unit can sometimes be called a transmitter, transmitter, or transmitting circuit.

[0299] When the communication device 900 performs the above embodiment Figure 4 When referring to network devices in the process shown:

[0300] The communication unit 901 is used to acquire first data and second data. The first data includes data from at least one mobile device, and the second data includes data from at least one base station. Each mobile device's data includes its raw observation data, and each base station's data includes its raw observation data. When the mobile device meets a first condition, the first condition includes one or more of the following: the mobile device is in a static state, and the carrier phase of the mobile device is valid.

[0301] The processing unit 902 is used to determine target observation data based on the first data and the second data, and the target observation data is used to assist the user equipment in positioning.

[0302] When the communication device 900 performs the above embodiment Figure 4 When the mobile device is in the process shown:

[0303] The communication unit 901 is used to receive satellite signals and generate raw observation data through the processing unit 902.

[0304] The communication unit 901 is further configured to send data from the mobile device when the mobile device meets a first condition, wherein the data from the mobile device includes the original observation data; the first condition includes one or more of the following:

[0305] The mobile device is in a static state and the carrier phase of the mobile device is valid.

[0306] The above is just an example. Processing unit 902 and communication unit 901 can also perform other functions. For a more detailed description, please refer to [link / reference needed]. Figure 4 and Figure 5 as well as Figures 7A-8A The relevant descriptions in the method embodiments shown are not repeated here.

[0307] like Figure 10 The image shown is a communication device 1000 provided in an embodiment of this application. Figure 10 The communication device shown can be Figure 9 The diagram illustrates one hardware circuit implementation of the communication device 1000. This communication device 1000 can be applied to the flowcharts shown above, performing the functions of the network device or mobile device in the method embodiments described above. For ease of explanation, Figure 10 Only the main components of the communication device are shown.

[0308] like Figure 10 As shown, the communication device 1000 includes a communication interface 1001 and a processor 1002. The communication interface 1001 and the processor 1002 are coupled to each other. It is understood that the communication interface 1001 can be a transceiver or an input / output interface, or an interface circuit such as a transceiver circuit. Optionally, the communication device 1000 may further include a memory 1003 for storing instructions executed by the processor 1002, or storing input data required by the processor 1002 to execute instructions, or storing data generated after the processor 1002 executes instructions.

[0309] When the communication device 1000 is used to implement Figure 4 and Figure 5 as well as Figures 7A-8A In the method shown, the communication interface 1001 is used to implement the functions of the communication unit 901, and the processor 1002 is used to implement the functions of the processing unit 902.

[0310] This application embodiment does not limit the specific connection medium between the communication interface 1001, processor 1002, and memory 1003. This application embodiment... Figure 10 The memory 1003, processor 1002, and communication interface 1001 are connected via a communication bus 1004. The communication bus 1004 is in... Figure 10 The connections between other components are shown in bold lines only and are not intended to be limiting. The communication bus 1004 can be divided into address bus, data bus, control bus, etc. For ease of illustration, Figure 10 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0311] When the aforementioned communication device is a chip. Figure 11 A simplified schematic diagram of a chip device structure is shown. The chip 1100 includes interface circuitry 1101 and one or more processors 1102. Optionally, the chip 1100 may also include a bus. Wherein:

[0312] Processor 1102 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the method for determining the service node information described above can be completed by the integrated logic circuitry in the hardware of processor 1102 or by instructions in software form. The processor 1102 may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods and steps disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor.

[0313] The interface circuit 1101 can be used to send or receive data, instructions or information. The processor 1102 can use the data, instructions or other information received by the interface circuit 1101 to process the data, instructions or other information, and can send the processed information out through the interface circuit 1101.

[0314] Optionally, chip 1100 also includes memory 1103, which may include read-only memory and random access memory, and provides operation instructions and data to the processor. A portion of memory 1103 may also include non-volatile random access memory (NVRAM).

[0315] Optionally, the memory stores executable software modules or data structures, and the processor can execute corresponding operations by calling the operation instructions stored in the memory (which may be stored in the operating system).

[0316] Optionally, the chip can be used in the network device or mobile device involved in the embodiments of this application. Optionally, the interface circuit 1101 can be used to output the execution result of the processor 1102. For the positioning methods provided by one or more embodiments of this application, please refer to the foregoing embodiments, which will not be repeated here.

[0317] It should be noted that the functions of the interface circuit 1101 and the processor 1102 can be implemented through hardware design, software design, or a combination of hardware and software; no restrictions are imposed here.

[0318] This application also provides a computer-readable storage medium storing computer instructions for implementing the methods executed by a network device or a mobile device in the above method embodiments.

[0319] For example, when the computer program is executed by a computer, it enables the computer to implement the methods executed by the network device or mobile device in the above method embodiments.

[0320] This application also provides a computer program product containing instructions that, when executed by a computer, cause the computer to perform the method described in the above method embodiments, which is executed by a network device or a mobile device.

[0321] This application also provides a chip, including a processor, for calling computer programs or computer instructions stored in the memory, so that the processor executes the above-mentioned... Figure 4 and Figure 5 as well as Figures 7A-8A The location method of the implementation shown.

[0322] In one possible implementation, the chip's input corresponds to the above... Figure 4 and Figure 5 as well as Figures 7A-8A The receiving operation shown in the implementation corresponds to the output of the chip described above. Figure 4 and Figure 5 as well as Figures 7A-8A The sending operation in the implementation shown.

[0323] Optionally, the processor is coupled to the memory via an interface.

[0324] Optionally, the chip also includes a memory that stores computer programs or computer instructions.

[0325] The processor mentioned above can be a general-purpose central processing unit, a microprocessor, an application-specific integrated circuit (ASIC), or one or more devices used to control the above. Figure 4 and Figure 5 as well as Figures 7A-8A The illustrated embodiment / implementation describes a program execution integrated circuit for a positioning method. The memory mentioned above can be read-only memory (ROM) or other types of static storage devices capable of storing static information and instructions, such as random access memory (RAM).

[0326] It should be noted that, for the sake of convenience and brevity, the explanations and beneficial effects of the relevant content in any of the communication devices provided above can be referred to the corresponding service node information determination method embodiments provided above, and will not be repeated here.

[0327] In this application, the communication devices may further include a hardware layer, an operating system layer running on top of the hardware layer, and an application layer running on the operating system layer. The hardware layer may include hardware such as a central processing unit (CPU), a memory management unit (MMU), and memory (also known as main memory). The operating system layer may be any one or more computer operating systems that implement business processing through processes, such as Linux, Unix, Android, iOS, or Windows. The application layer may include applications such as browsers, address books, word processing software, and instant messaging software.

[0328] The module division in this embodiment is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in each embodiment of this application can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0329] Through the above description of the embodiments, those skilled in the art will clearly understand that the embodiments of this application can be implemented in hardware, firmware, or a combination thereof. When implemented in software, the above functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transfer of a computer program from one place to another. Storage media can be any available medium accessible to a computer. For example, but not limited to, computer-readable media can include RAM, ROM, electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage media, or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible to a computer. Furthermore, any connection can suitably be a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of the medium. As used in embodiments of this application, disks and discs include compact discs (CDs), laser discs, optical discs, digital video discs (DVDs), floppy disks, and Blu-ray discs, wherein disks typically magnetically copy data, while discs optically copy data using lasers. The combinations above should also be included within the scope of protection for computer-readable media.

[0330] In summary, the above descriptions are merely embodiments of this application and are not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made based on the disclosure of this application should be included within the scope of protection of this application.

Claims

1. A positioning method, characterized in that, include: Acquire first data and second data, wherein the first data includes data from at least one mobile device and the second data includes data from at least one base station; wherein the data from each mobile device includes the raw observation data of the mobile device and the data from each base station includes the raw observation data of the base station; when the mobile device meets a first condition, the first condition includes one or more of the following: the mobile device is in a static state and the carrier phase of the mobile device is valid; Based on the first data and the second data, target observation data is determined, which is used to assist user equipment in positioning.

2. The method as described in claim 1, characterized in that, The determination of target observation data based on the first data and the second data includes: Determine the first region; Based on the first data and the second data, at least one valid reference station within the first area is determined; The target observation data are determined based on the data from the at least one valid reference station; The effective reference station meets one or more of the following criteria: The number of valid carrier phases is greater than the first threshold; The number of effective carrier phases is greater than the number of effective carrier phases of a preset number of devices, wherein the preset number of devices are the at least one mobile device and the devices in the at least one base station; The distance between the station and the adjacent reference station is greater than the second threshold. It is in a static continuous operation state.

3. The method as described in claim 2, characterized in that, The step of determining at least one valid reference station within the first area based on the first data and the second data includes: When there is no scene change in the first area, the at least one valid base station is determined based on the first data and the second data; When there is a scene change in the first area, the at least one valid base station is determined based on the scene change information, the first data, and the second data; The scene change includes one or more of the following: At least one first mobile device has disappeared within the first area; At least one first reference station has disappeared within the first region; At least one new second mobile device exists within the first area; There is at least one newly added second reference station in the first region.

4. The method as described in claim 3, characterized in that, The determination of the at least one valid base station based on scene change information and the first and second data includes: Based on the scene change information, update the first data and / or the second data to obtain the third data and / or the fourth data; Based on the third and / or fourth data, the at least one valid reference station is determined.

5. The method as described in claim 4, characterized in that, When the scene change information is used to indicate that at least one first mobile device and / or at least one first base station has disappeared in the first area; The step of updating the first data and / or the second data to obtain the third data and / or the fourth data includes: The data of the at least one first mobile device is deleted from the first data to obtain the third data; and / or The fourth data is obtained by deleting the data from at least one first reference station from the second data.

6. The method as described in claim 4, characterized in that, When the scene change information is used to indicate that there is at least one new second mobile device and / or at least one new second base station in the first area; The step of updating the first data and / or the second data to obtain the third data and / or the fourth data includes: Acquire data from the at least one second mobile device, and use the first data and the data from the at least one second mobile device as the third data; and / or Data from the at least one second reference station is acquired, and the second data and the data from the at least one second reference station are used as the fourth data.

7. The method according to any one of claims 2 to 6, characterized in that, The determination of the target observation data based on the data from the at least one valid reference station includes: Determine the location information of the at least one valid reference station; Based on the location information of the at least one valid reference station, at least one target reference station is determined from the at least one valid reference station; The target observation data is determined based on the location information of the at least one target reference station and the data from the at least one target reference station.

8. The method as described in claim 7, characterized in that, Determining the location information of the at least one valid reference station includes: Acquire data from at least one reference station within the first region; The location information of the at least one effective reference station is obtained by performing joint positioning calculation based on the data from the at least one reference station and the data from the at least one effective reference station.

9. The method as described in claim 7, characterized in that, The step of determining at least one target reference station from the at least one valid reference station based on the location information of the at least one valid reference station includes: Based on the location information of the at least one valid reference station, the triangulation adjustment method is used to process the data and determine the location error value of the at least one valid reference station. Based on the position error value of the at least one valid reference station, at least one valid reference station with a position error value less than a preset error value is selected and used as the at least one target reference station.

10. The method as described in claim 7, characterized in that, The determination of the target observation data based on the location information of the at least one target reference station and the data from the at least one target reference station includes: When it is determined, based on the location information of the at least one valid reference station, that the at least one valid reference station meets the second condition, the original observation data of the at least one valid reference station is used as the target observation data; When it is determined, based on the location information of the at least one valid reference station, that the at least one valid reference station does not meet the second condition, the target observation data is determined based on the original observation data of the at least one valid reference station; The second condition includes that the density between the at least one valid reference station is less than a preset value.

11. The method as described in claim 10, characterized in that, The determination of the target observation data based on the raw observation data from the at least one valid reference station includes: Based on the raw observation data from the at least one target reference station, determine the ionospheric residual in the baseline direction and the tropospheric residual in the baseline direction; Based on the ionospheric residual and the tropospheric residual in the baseline direction, the ionospheric residual and the tropospheric residual between the virtual reference station and the third reference station are determined; wherein, the virtual reference station is the central station in the first region, and the third reference station is the reference station closest to the virtual reference station among the at least one reference station; Based on the ionospheric residual and tropospheric residual between the virtual reference station and the third reference station, as well as the original observation data of the third reference station, the virtual observation data of the virtual reference station is determined and used as the target observation data.

12. The method according to any one of claims 7 to 11, characterized in that, The method further includes: Send the location information of the at least one target base station.

13. The method according to any one of claims 1 to 12, characterized in that, The data for each mobile device also includes the local data of the mobile device, and the data for the base station also includes the local data of the base station; The local data includes at least one of the following: Approximate location information and GNSS module information.

14. The method according to any one of claims 1 to 13, characterized in that, The raw observation data includes at least one of the following: Pseudorange, carrier phase, carrier phase lock-in information, Doppler information, carrier noise density ratio CN0, and carrier phase continuous lock-in time.

15. A positioning method, characterized in that, Chips used in or corresponding to mobile devices include: Receive satellite signals and generate raw observation data based on the satellite signals; When the mobile device meets the first condition, it transmits data from the mobile device, including the original observation data; the first condition includes one or more of the following: The mobile device is in a static state and the carrier phase of the mobile device is valid.

16. The method as described in claim 15, characterized in that, The method further includes: The current state of the mobile device is determined to be stationary based on one or more of the following data: The residual of at least one satellite Doppler observation data in the original observation data; The chassis wheel speed meter data of the mobile device; The inertial measurement unit (IMU) data in the mobile device; The visual data of the mobile device.

17. The method as described in claim 15 or 16, characterized in that, The raw observation data includes carrier phase observation data; the method further includes: The observed data for the carrier phase is deemed valid when one or more of the following conditions are met: The continuous lock time of the carrier phase is positive, and the number of valid carrier phase observation values ​​is greater than a preset value; The continuous lock time of the carrier phase and the number of valid carrier phase observation values ​​are obtained based on the carrier phase observation data.

18. The method according to any one of claims 15 to 17, characterized in that, The data from the mobile device also includes local data from the mobile device, which includes at least one of the following: Approximate location information and GNSS module information.

19. The method according to any one of claims 15 to 18, characterized in that, The raw observation data includes at least one of the following: Pseudorange, carrier phase, carrier phase lock-in information, Doppler information, carrier noise density ratio CN0, and carrier phase continuous lock-in time.

20. A communication device, characterized in that, It includes units or modules for performing the method as described in any one of claims 1 to 14, or units or modules for performing the method as described in any one of claims 15 to 19.

21. A communication device, characterized in that, include: At least one processor and interface circuitry; The interface circuit is used to receive signals from other devices outside the device and transmit them to the processor, or to send signals from the processor to other devices outside the device. The processor is used to implement the method as described in any one of claims 1 to 14 or the method as described in any one of claims 15 to 19 through logic circuits or execution code instructions.

22. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer-readable program or instructions that, when executed on a communication device, cause the method as described in any one of claims 1 to 14 to be performed, or cause the method as described in any one of claims 15 to 19 to be performed.

23. A computer program product, characterized in that, The computer program product includes a computer program or instructions that, when executed on a computer, cause the computer to perform the method as claimed in any one of claims 1 to 14, or cause the computer to perform the method as claimed in any one of claims 15 to 19.

24. A chip, characterized in that, The chip is configured to read and execute computer programs or instructions in a memory to implement the method as described in any one of claims 11-14, or to implement the method as described in any one of claims 15 to 19.

25. A communication system, characterized in that, include: Network equipment, mobile devices, base stations; The network device is configured to perform the method as described in any one of claims 1 to 14; The mobile device is configured to perform the method as described in any one of claims 15 to 19; The base station is used to send data from the base station to the network device.

Images