A positioning point display method and device, electronic equipment and storage medium

Abstract

Embodiments of the present application provide a positioning point display method and device, electronic equipment and storage medium, which are applied to a smart wearable device and include the following steps: obtaining positioning information of the smart wearable device; acquiring target ionosphere total electron content (TEC) data within a preset range centered on the positioning information within a preset time period starting from a current time; and when the target ionosphere total electron content (TEC) data is greater than a preset TEC threshold value, the smart wearable device does not display the positioning information. By not displaying the positioning result of the positioning point in the active state of the ionosphere, reliable and accurate position information is provided to the user, and the user experience is further improved.

Description

Technical Field

[0001] This application relates to the field of positioning technology, and in particular to a positioning point display method, device, electronic device and storage medium. Background Technology

[0002] In modern mobile devices and smart terminals, Global Navigation Satellite System (GNSS) positioning technology is widely used to provide accurate location services. However, in real-world user scenarios, the lack of ground truth equipment makes it difficult to determine the true location of user devices. This uncertainty poses a significant challenge to upper-layer applications, making it difficult to decide whether the current positioning point should be adopted. Currently, the common industry practice is to directly output all GNSS positioning results to the application for display. Under adverse conditions such as ionospheric activity, this can lead to users seeing incorrect positioning results. Summary of the Invention

[0003] This application provides a positioning point display method, device, electronic device, and storage medium, which can ensure reliable and accurate location information to users by not displaying the positioning results of positioning points in an active ionospheric state, thereby further improving the user experience.

[0004] The first aspect of this application provides a positioning point display method, applied to a smart wearable device, including:

[0005] Obtain the location information of the smart wearable device;

[0006] Acquire the Total Electron Content (TEC) data of the target ionosphere within a preset range centered on the location information, starting from the current time and within a preset time period.

[0007] When the total electron content (TEC) data of the target ionosphere exceeds a preset TEC threshold, the smart wearable device will not display the location information.

[0008] In some possible embodiments, the location information includes the current location information of the smart wearable device, and the acquisition of the total electron content (TEC) data of the target ionosphere within a preset range centered on the location information for a preset time period starting from the current time includes:

[0009] Acquire TEC data corresponding to all grids within a preset range centered on the current location information within a preset time period starting from the current time, wherein each grid is used to indicate the smallest area into which the preset range area centered on the current location information is divided;

[0010] From the TEC data corresponding to all the grids, obtain the target TEC data, which is the maximum value among the TEC data corresponding to all the grids.

[0011] In some possible embodiments, the method further includes:

[0012] When the total electron content (TEC) data of the target ionosphere exceeds a preset TEC threshold, the positioning function is disabled. The positioning function includes at least one of the following: movement trajectory display, navigation, and positioning.

[0013] In some possible embodiments, the method further includes:

[0014] Obtain the positioning error;

[0015] Receive output commands;

[0016] In response to the output command, the positioning error is output.

[0017] In some possible embodiments, obtaining the positioning error includes:

[0018] Obtain the location information of multiple positioning points within a preset range, wherein the location information includes the longitude and latitude of the positioning points;

[0019] Obtain the average longitude and latitude of the multiple positioning points;

[0020] The positioning error is obtained, which is the value with the largest absolute value among the distance differences between the average value and the plurality of positioning points.

[0021] In some possible embodiments, a first elevation angle and a second elevation angle are preset, the first elevation angle being greater than the second elevation angle, wherein the elevation angle is the angle between the satellite and the horizon where the smart wearable device is located. The method for acquiring the total ionospheric electron content (TEC) data of a target within a preset range centered on the positioning information for a preset time period starting from the current moment includes:

[0022] The maximum TEC data within the first elevation angle interval and the second elevation angle interval are obtained respectively, wherein the elevation angle interval is used to indicate the ionospheric region corresponding to the elevation angle centered on the positioning information;

[0023] The number of satellites in the first elevation angle interval and the number of satellites in the first elevation angle interval are obtained respectively;

[0024] If the maximum TEC data in the first elevation angle range is less than the maximum TEC data in the second elevation angle range...

[0025] If the number of satellites in the first elevation angle interval is greater than the number of satellites in the second elevation angle interval, target TEC data is obtained; the target TEC data is the maximum TEC data in the first elevation angle interval.

[0026] The number of satellites in the first elevation angle interval is less than the number of satellites in the second elevation angle interval, and target TEC data is obtained; the target TEC data is the maximum TEC data in the second elevation angle interval.

[0027] In some possible embodiments, the method further includes:

[0028] When the target total electron content (TEC) data of the ionosphere is less than or equal to a preset TEC threshold, the smart wearable device displays the location information.

[0029] A second aspect of this application provides a positioning point display device, applied to a smart wearable device, comprising:

[0030] The receiving module is used to obtain the positioning information of the smart wearable device; and to acquire the total electron content (TEC) data of the target ionosphere within a preset range centered on the positioning information for a preset time period starting from the current time.

[0031] The display module is configured to prevent the smart wearable device from displaying the location information when the total electron content (TEC) data of the target ionosphere exceeds a preset TEC threshold.

[0032] A third aspect of this application provides an electronic device, including:

[0033] processor;

[0034] Memory used to store the processor's executable instructions;

[0035] The processor is configured to execute the instructions to implement a positioning point display method as described in any one of the embodiments of the first aspect of this application.

[0036] A fourth aspect of this application provides a storage medium that, when instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to perform a positioning point display method as described in any one of the first aspects of this application.

[0037] The technical solutions provided in this application have at least the following beneficial effects:

[0038] This application proposes a location point display method for smart wearable devices, comprising: obtaining location information of the smart wearable device; acquiring total electron content (TEC) data of a target ionosphere within a preset range centered on the location information for a preset time period starting from the current time; and when the TEC data of the target ionosphere exceeds a preset TEC threshold, the smart wearable device does not display the location information. By not displaying the location results of the location point in an active ionospheric state, reliable and accurate location information is provided to the user, further improving the user experience. Attached Figure Description

[0039] Figure 1 This is a schematic diagram illustrating an application scenario of a positioning point display method proposed in an embodiment of this application;

[0040] Figure 2 This is a flowchart illustrating a positioning point display method proposed in an embodiment of this application;

[0041] Figure 3 This is a flowchart illustrating yet another positioning point display method proposed in an embodiment of this application;

[0042] Figure 4 This is a flowchart illustrating yet another positioning point display method proposed in an embodiment of this application;

[0043] Figure 5 This is a flowchart illustrating the process of obtaining positioning error in another positioning point display method proposed in an embodiment of this application.

[0044] Figure 6 This is a schematic diagram of the elevation angle in another positioning point display method proposed in the embodiments of this application;

[0045] Figure 7 This is a flowchart illustrating yet another positioning point display method proposed in an embodiment of this application;

[0046] Figure 8 This is a schematic diagram of the structure of a positioning point display device proposed in an embodiment of this application;

[0047] Figure 9 This is a schematic diagram of the structure of another positioning point display device proposed in the embodiments of this application. Detailed Implementation

[0048] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0049] To facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with essentially the same function and effect. For example, "first instruction" and "second instruction" are used to distinguish different user instructions and do not limit their order. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and the terms "first" and "second" are not necessarily different.

[0050] It should be noted that in the embodiments of this application, the words "exemplarily" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplarily" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplarily" or "for example" is intended to present the relevant concepts in a specific manner.

[0051] Furthermore, "at least one" refers to one or more, while "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 mean: 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, and c can mean: a, or b, or c, or a and b, or a and c, or b and c, or a, b, and c, where a, b, and c can be single or multiple.

[0052] It should be noted that, in the embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0053] In modern mobile devices and smart terminals, GNSS positioning technology is widely used to provide precise location services. GNSS is a system that uses satellites to provide positioning, navigation, and timing services. Common GNSS systems include China's BeiDou Navigation Satellite System, the United States' Global Positioning System (GPS), Russia's Global Navigation Satellite System, and the European Union's Galileo. This technology uses a high-precision positioning device, typically composed of a high-performance antenna, a GNSS receiver, and an inertial navigation unit, to provide continuous high-precision positioning point output. It is usually used as standard equipment in the GNSS product development industry to perform high-precision calibration at different locations and trajectories during GNSS product testing to quantitatively evaluate the actual positioning performance of GNSS products. However, in actual user scenarios, due to the lack of a ground truth device, it is difficult to determine the true location and positioning accuracy of user equipment. This uncertainty poses a significant challenge to upper-level applications, as they cannot obtain the accuracy information of each positioning point and find it difficult to decide whether the current positioning point should be used.

[0054] Currently, the common practice is to directly output all GNSS positioning results to the application for display, without reporting accuracy parameters. This means that regardless of the actual positioning error, all positioning points will be displayed on the map or other user interfaces. While this approach simplifies implementation, it also introduces a series of problems:

[0055] When the ionosphere is active, some satellite signals cross the active ionospheric zone, increasing pseudorange errors between the receiver and the satellite. The ionosphere, part of Earth's atmosphere, is located at an altitude of approximately 50 to 1000 kilometers and is filled with ionized gas, affecting radio wave propagation. GNSS satellite signals are affected by the ionosphere, resulting in longer propagation times. Pseudorange refers to the estimated distance from the satellite to the receiver, calculated based on the signal propagation time. Due to the asynchronous clocks of the receiver and satellite, and various delays that may occur during signal propagation, this distance estimate is not the true geometric distance and is therefore called "pseudorange." The more active the ionosphere, the more significant this effect, severely impacting positioning accuracy.

[0056] In addition, directly displaying these location points that are highly affected by the ionosphere can lead to incorrect location results for users, thus impacting the user experience. For example, in navigation applications, users may be guided to the wrong route or location, causing inconvenience or even safety hazards.

[0057] To mitigate these issues, some solutions suggest using ionospheric activity indication services provided by third-party providers to filter out points with poor positioning accuracy. However, this method has the following drawbacks:

[0058] (1) High network overhead: Frequent access to third-party services increases the number of network requests, resulting in additional power consumption and data usage, especially on mobile devices, which can significantly affect battery life and users' data usage budget.

[0059] (2) High service fees: Long-term reliance on third-party service providers not only increases operating costs, but may also be affected by changes in service provider policies, such as service price adjustments and data restrictions, which pose a threat to the sustainability and stability of the product.

[0060] In view of this, this application proposes a location point display method for smart wearable devices, comprising: obtaining location information of the smart wearable device; acquiring target total electron content (TEC) data within a preset range centered on the location information within a preset time period starting from the current time; and when the target total electron content (TEC) data is greater than a preset TEC threshold value, the smart wearable device does not display the location information.

[0061] The ionospheric tectonics (TEC) refers to the total number of electrons along a vertical path from the ground to the top of the ionosphere, usually expressed as electrons per square meter. TEC is an important parameter for assessing the impact of the ionosphere on radio signals and affects the accuracy of navigation systems such as GPS.

[0062] In detail, this application provides a method for displaying positioning points in a smart wearable device. It determines whether to display positioning information by evaluating the total ionospheric TEC data, ensuring high accuracy and reliability. Specifically, the device first obtains the latitude and longitude coordinates of its current location, then retrieves TEC data within a preset range centered on the current location from a third-party service or built-in module, and calculates the target TEC data (i.e., the maximum value). If the target TEC data exceeds a preset threshold, it indicates ionospheric activity, and the device will not display positioning information and will disable related functions (such as movement trajectory, navigation, etc.) to avoid misleading the user; conversely, if the target TEC data is within the threshold, the positioning information is displayed normally. To improve user experience, the device can also calculate and output the positioning error, determining the maximum error by comparing the distance difference between multiple positioning points and the average value. Furthermore, by setting different priority elevation angle ranges, the device more accurately assesses the impact of ionospheric activity on positioning and selects appropriate target TEC data. When ionospheric activity weakens and the TEC data returns to below the threshold, the device re-displays the positioning information and restores previously disabled functions. This method not only improves the accuracy of location information, but also effectively avoids displaying incorrect location points due to ionospheric activity, enhancing the user experience and overall system performance, while reducing power consumption and bandwidth usage, ensuring efficient operation.

[0063] For example, Figure 1 This diagram illustrates an application scenario of the positioning point display method proposed in this application. The scenario includes: a smart wearable device 101 and a server 102. A brief description of each component in the diagram follows:

[0064] In this scenario, the smart wearable device 101 serves as the main terminal device, responsible for obtaining the user's current location information and evaluating the positioning accuracy based on ionospheric TEC data to determine whether to display the positioning information. For example, the smart wearable device can be a smartwatch, smart earphone, smart bracelet, smart glasses, smart clothing, etc., and is not limited in this embodiment.

[0065] Server 102 provides necessary support services to smart wearable device 101, especially the real-time updating and analysis of ionospheric TEC data. The main functions of server 102 include: providing smart wearable device 101 with ionospheric TEC data centered on its current location within a preset range via API or other protocols; monitoring and predicting ionospheric activity globally or regionally, generating a high-precision TEC data grid, and updating it in real-time as needed; managing registered devices and service subscriptions to ensure each smart wearable device 101 receives timely and accurate service responses; and saving historical TEC data and other relevant parameters for subsequent analysis and service performance optimization.

[0066] This design not only improves the accuracy of positioning information, but also effectively avoids displaying incorrect positioning points due to ionospheric activity, enhancing the user experience and overall system performance, while reducing power consumption and bandwidth consumption to ensure efficient operation.

[0067] The following details the execution steps of the positioning point display method proposed in the embodiments of this application.

[0068] For example, such as Figure 2 As shown, the steps for applying this technology to smart wearable devices are as follows:

[0069] Step 201: Obtain the location information of the smart wearable device;

[0070] The positioning information includes: location information, which includes: longitude and latitude information of the positioning point.

[0071] The smart wearable device performs local GNSS positioning to obtain the device's location.

[0072] For example, the positioning latitude and longitude information of the positioning device is calculated using conventional GNSS multi-constellation pseudorange positioning.

[0073] Calculating the latitude and longitude information of a positioning device using conventional GNSS multi-constellation pseudorange positioning is a complex but highly accurate process. First, the positioning device can receive satellite signals from multiple GNSS constellations, each consisting of several operational satellites, ensuring broad global coverage. Simultaneously, the receiver can receive signals from different frequency bands such as L1, L2, and L5 to improve positioning accuracy and reliability.

[0074] Next, for each received satellite signal, the positioning device measures the time delay of the signal's propagation from the satellite to the receiver and converts it into pseudorange. Pseudorange is an estimated distance between the satellite and the receiver, but it includes errors caused by factors such as receiver clock skew. Using multi-band signals can reduce the impact of ionospheric delay and further improve positioning accuracy.

[0075] Then, using pseudorange data from at least four satellites, combined with known satellite position information (determined by ephemeris data broadcast by the satellites), the receiver's three-dimensional coordinates (latitude, longitude, and altitude) and the error of the receiver's internal clock are calculated using the least squares method. The least squares method finds the optimal solution by minimizing the sum of the squared errors between all measured values ​​and theoretical values. In dynamic environments, Kalman filters or other recursive filtering algorithms can also be used to update the position estimate in real time, improving the continuity and stability of positioning.

[0076] By using multi-constellation GNSS, the number of visible satellites can be significantly increased, especially in urban canyons or multipath environments, which helps improve positioning accuracy and reliability. More satellites mean more observation data, which can be used for cross-validation and error detection, thereby improving the overall system robustness. As the receiver continuously receives new satellite signals, the above process is periodically repeated, enabling real-time updates to the positioning device's location and dynamically adjusting algorithm parameters to optimize performance based on environmental changes (such as satellite visibility, ionospheric activity, etc.).

[0077] To further improve positioning accuracy, positioning equipment can also incorporate other auxiliary data for correction. For example, it can correct for ionospheric delay using global or regional ionospheric models (such as the Klobuchar model and the NeQuick model); correct for tropospheric delay using standard atmospheric models (such as the Saastamoinnen model); and improve positioning accuracy through differential corrections provided by ground reference stations. Pseudorange measurement estimates distance by measuring the time it takes for satellite signals to reach the receiver, but this distance estimation includes time errors due to the asynchrony between the receiver and satellite clocks. The geometric distribution of satellites has a significant impact on positioning accuracy. The Diminishing Probability (DOP) is a commonly used indicator; a lower DOP value indicates a better satellite geometric distribution, thereby improving positioning accuracy.

[0078] Using conventional GNSS multi-constellation pseudorange positioning, positioning devices can accurately calculate their own latitude and longitude information. This process relies not only on the rich satellite signals provided by multiple GNSS constellations but also combines various mathematical algorithms and technical means to ensure high-precision positioning results in various environments. This method is widely used in fields such as car navigation, smartphones, and drones, providing users with reliable geolocation services.

[0079] For example, using the latitude and longitude of this positioning point as a reference, the latitude is ±20° north and south, and the longitude is ±16° east and west (extending 20 degrees north and south from the positioning point, so the total latitude span is 40 degrees). Extending 16 degrees east and west from the specified positioning point, so the total longitude span is 32 degrees.

[0080] Step 202: Obtain the Total Electron Content (TEC) data of the target ionosphere within a preset range centered on the positioning information, starting from the current time and within a preset time period;

[0081] Ionospheric data can be obtained through various means, such as third-party service providers or smart terminal devices that integrate ionospheric data acquisition modules.

[0082] For example, ionospheric TEC data can be received through third-party services, such as via networks (4G, 5G, WIFI, etc.). Typically, this data represents the ionospheric TEC data of the global ionospheric region divided into grids for the next 4 hours. The global ionospheric region is divided into grids, with each grid point representing a TEC value at a specific geographical location.

[0083] Ionospheric TEC data refers to the number density distribution of free electrons in the ionosphere within a specific time and space range. TEC values ​​are usually expressed in TECU (Total Electron Content Unit), where 1 TECU equals 10-1 16 One electron per square meter.

[0084] This data can be obtained through various means, including but not limited to:

[0085] For example, third-party services: obtaining data from service providers that specialize in providing ionospheric monitoring data, such as the International GNSS Service, the European Meteorological Satellite Development Organization, etc.

[0086] For example, sensors or computing modules integrated within a smart wearable device can estimate the TEC value based on the received GNSS signal.

[0087] The preset area is divided into multiple small grids, each corresponding to a specific geographic TEC value. By collecting data from these grid points, a complete TEC distribution map is formed.

[0088] Ionospheric TEC data can be obtained through the following steps:

[0089] The device sends a request to the server via the communication interface, specifying the required preset duration and preset range. The server returns the corresponding TEC data based on the request.

[0090] The received data may include TEC values ​​from multiple time points and multiple geographical locations. Smart wearable devices need to process this data, such as calculating maximum values, average values, or other statistics, to ultimately determine the "target TEC data".

[0091] The processed target TEC data is stored in the device's memory and used for subsequent positioning accuracy assessment and decision-making logic.

[0092] After acquiring ionospheric TEC data, target ionospheric TEC data is acquired, which is the ionospheric TEC data that is the largest within a preset range used in the final embodiment of this application to compare with the TEC threshold to determine the level of ionospheric activity.

[0093] The acquisition of Total Electron Content (TEC) data of the target ionosphere within a preset range centered on the positioning information, starting from the current time and within a preset time period, is as follows: Figure 3 As shown, the detailed steps are as follows:

[0094] Step 301: Obtain TEC data for all grids within a preset range centered on the current location information within a preset time period starting from the current time;

[0095] Each of the grids is used to indicate the smallest area into which a preset range centered on the current location information is divided;

[0096] Step 302: Obtain the target TEC data from the TEC data corresponding to all grids. The target TEC data is the maximum value among the TEC data corresponding to all grids.

[0097] In detail, the preset range includes multiple grids. The TEC values ​​of different grid points may be the same or different, depending on the actual ionization distribution at that time. The maximum value of TEC within multiple grids is calculated.

[0098] Step 203: When the total electron content (TEC) data of the target ionosphere is greater than the preset TEC threshold, the smart wearable device does not display the location information.

[0099] The target ionospheric total electron content (TEC) data is the maximum TEC value across multiple grids. The target ionospheric TEC data is compared to a pre-set TEC threshold value at a pre-defined judgment frequency. This judgment frequency can be adjusted according to different situations. The pre-set TEC threshold value is derived through a combination of methods and considerations to ensure that smart wearable devices can provide reliable and accurate positioning services even under abnormal ionospheric activity conditions. By analyzing historical ionospheric activity data, typical characteristics and extreme situations of ionospheric activity in different regions and time periods can be identified. To this end, long-term historical TEC data is obtained from global or regional ionospheric monitoring stations, and the average TEC value and standard deviation for different seasons and times within a specific region are calculated to identify abnormally high TEC values. Based on these statistical results, a reasonable threshold value is selected, which should be higher than the normal range but lower than the maximum value under extreme abnormal conditions to ensure that positioning accuracy is not affected in most cases.

[0100] To further evaluate the impact of different TECs on GNSS signals, reasonable threshold values ​​will be determined through simulation and experimental verification. Different ionospheric activity conditions will be simulated in a controlled environment to record the impact of TEC changes on GNSS receiver performance. Simultaneously, tests will be conducted in real-world environments, particularly in areas with known high ionospheric activity (such as near the equator or polar regions), to observe equipment performance. Based on the test results, the threshold values ​​will be continuously adjusted and optimized to ensure they effectively filter out abnormal conditions without being overly sensitive and causing false triggers. Furthermore, guidelines and standards published by international organizations will be followed to ensure that the threshold values ​​comply with industry specifications.

[0101] Considering the varying user needs and specific application scenarios, it is crucial to flexibly adjust the TEC threshold to meet the positioning accuracy requirements of different users. Understanding the differences in needs among different user types (such as ordinary consumers, professional outdoor adventurers, and military applications) and setting corresponding TEC thresholds based on different application scenarios (such as urban navigation, mountain hiking, and maritime navigation) is essential. Simultaneously, it is important to ensure that the threshold settings do not excessively impact the user experience, being neither too conservative nor too aggressive.

[0102] Furthermore, considering the spatiotemporal variability of ionospheric activity, it is essential to establish a dynamic adjustment mechanism to update the TEC threshold value in real time. This involves continuously monitoring ionospheric activity levels using real-time data from a global ionospheric monitoring network; developing adaptive algorithms to automatically adjust the TEC threshold value based on real-time data to ensure it remains optimal; and collecting user feedback and suggestions to further optimize the threshold setting.

[0103] In summary, the preset TEC threshold value is derived through a combination of methods, including historical data analysis, simulation and experimental verification, expert experience and industry standards, user needs and application scenarios, and dynamic adjustment mechanisms. These methods ensure that the TEC threshold value can effectively filter out abnormal situations while maintaining flexibility and accuracy, thereby providing users with reliable positioning services.

[0104] For example, the smart wearable device compares the target TEC data with a pre-set TEC threshold. If the target TEC data is greater than the threshold, it is considered that the ionospheric activity is too strong and may significantly interfere with the GNSS signal, resulting in a decrease in positioning accuracy.

[0105] When the target ionospheric total electron content (TEC) data exceeds a preset TEC threshold, the positioning function is disabled. The positioning function includes at least one of the following: movement trajectory display, navigation, and positioning. This step aims to avoid providing users with incorrect or unreliable location data and ensure that the information obtained by the user is as accurate and reliable as possible.

[0106] For example, on the user interface, smart wearable devices no longer display the current latitude and longitude coordinates, map markers, or other forms of location information.

[0107] In addition to not displaying location information, the device can also selectively disable features that rely on precise location, such as movement trajectory display and navigation, to prevent misleading users.

[0108] For example, the target user is an outdoor adventure enthusiast who frequently hikes in remote mountainous areas and relies on a smart bracelet for navigation and emergency rescue services. One day at noon, when the user encounters unusually strong ionospheric activity, the target TEC data detected by the smart wearable device significantly exceeds a preset threshold. To ensure the accuracy of the location information, the smart bracelet immediately stops displaying the current latitude and longitude coordinates and map markers. The map interface that was originally used to display the current location is replaced with a prompt: "Due to abnormal ionospheric activity, the current location information is temporarily unavailable. Please be careful." To prevent misleading the user, the smart bracelet automatically disables the navigation function but retains the emergency SOS button and other non-location-related functions. The user can choose to manually enter known landmarks or use other methods to continue. Although unable to rely on the smart bracelet for real-time navigation, Xiao Zhang can continue based on previous route planning and the surrounding environment. The prompt on the screen reminds him that the current location information is unreliable, prompting him to be more cautious and ensure his safety.

[0109] In some possible embodiments, the smart wearable device displays the location information when the total electron content (TEC) data of the target ionosphere is less than or equal to a preset TEC threshold value.

[0110] For example, when the target ionospheric TEC data exceeds a preset threshold, the smart wearable device does not display location information by default to avoid misleading the user. However, the user can choose to force the display of location points. In this case, the location points on the movement trajectory will be displayed as dashed dots, indicating that the positioning accuracy of these points is low and may be unreliable. The use of dashed dots reminds the user that the current location information may have a large error.

[0111] Conversely, when the target TEC data is less than or equal to a preset threshold, the smart wearable device displays the location information normally. In this case, the location points appear as solid dots on the movement trajectory, indicating high positioning accuracy. The movement trajectory is presented by connecting the individual solid location points into a continuous line, clearly reflecting the spatiotemporal information such as the time sequence of the user's movement and changes in position.

[0112] For example, if a user selects to enable positioning points with large errors, these points will appear as virtual points on the movement trajectory and will not connect with other points, forming a broken trajectory. This approach not only alerts the user to which positioning points may have large errors but also avoids including unreliable positioning points in the continuous trajectory, thereby maintaining the accuracy and reliability of the overall trajectory.

[0113] This approach not only improves the user experience but also enhances the system's flexibility and reliability, ensuring users can operate under different ionospheric conditions.

[0114] All can obtain the most accurate location information and trajectory display.

[0115] In some possible implementations, the user can choose to enable the display of positioning results, which include the latitude and longitude information of the positioning point and the positioning error, such as... Figure 4 As shown, the method further includes:

[0116] Step 401: Obtain the positioning error;

[0117] For example, when the target ionospheric TEC data exceeds a preset threshold, the user can display not only the location of the point on the map but also the positioning error of that point. The calculation steps for the positioning error are as follows: Figure 5 As shown:

[0118] Step 501: Obtain the location information of multiple positioning points within a preset range;

[0119] The location information includes the longitude and latitude of the positioning point, and the ionosphere within a preset range around the positioning point can be used to locate the longitude and latitude of multiple other positioning points.

[0120] Step 502: Obtain the average longitude and latitude of the multiple positioning points;

[0121] For example, a smart wearable device sets a preset range centered on the target user's current location (longitude and latitude). Within this range, the smart wearable device acquires the latitude and longitude information of multiple positioning points via a GNSS receiver. For instance, it might record the coordinates of 10 different locations distributed in various directions around the target user.

[0122] Due to abnormal ionospheric activity, there may be significant errors in the distance between smart wearable devices and their original positioning points. Therefore, the average latitude and longitude of these positioning points are further calculated.

[0123] Step 503: Obtain the positioning error, which is the largest absolute value among the distance differences between the average value and the plurality of positioning points.

[0124] Based on step 502, the differences between these positioning points and the average latitude and longitude are calculated, and the largest distance difference is selected as the positioning error. This processing method not only improves the accuracy of positioning information but also provides users with a reliable reference indicator, helping target users better understand the reliability of the current positioning information.

[0125] Step 402: Receive output command;

[0126] For example, step 402 involves the smart wearable device receiving an output command from the user. This function is typically triggered by the user clicking the "Show Location Results" button on the device. To gain a more comprehensive understanding of this process, its working principle and user experience design can be analyzed in detail from the device's perspective.

[0127] In step 402, the smart wearable device is in a waiting state, ready to receive user input commands. These commands are typically user-initiated operations aimed at requesting the device to display current location information or perform other related functions. To simplify the operation process and improve the user experience, the device interface usually features an intuitive interface element, such as a button or icon, for the user to click.

[0128] When users want to view the current location results, they can issue a command by touching the screen or pressing a physical button. For example, the device's main interface may have a prominent "Show Location" button. Users can simply tap this button to trigger subsequent processing, such as calculating location errors and updating the map display. Once the user's output command is received, the device immediately starts the corresponding processing procedure. This includes checking the current ionospheric activity (such as whether the target TEC data exceeds a threshold), obtaining the latest location information, calculating the location error, and finally presenting the results to the user. If abnormal ionospheric activity is detected, the device will decide whether to display the location point or show it as a dotted dot according to predefined rules, and provide additional prompts.

[0129] From a user experience design perspective, the device ensures that the buttons are simple and clear, allowing users to quickly find and operate them. The button colors, shapes, and labels are optimized to highlight their importance and function. When a user clicks a button, the device immediately provides visual or tactile feedback, such as a color change or slight vibration, to let the user know that the action has been successfully received. Considering different user habits, the device supports multiple input methods, including touchscreens and physical buttons. For devices without touchscreens, similar functions can be achieved through long presses and double-clicks. Furthermore, the smart wearable device provides a brief tutorial or displays on-screen prompts upon first use to help users better understand how to operate it.

[0130] Step 403: In response to the output command, output the positioning error.

[0131] When the user clicks, the positioning error is displayed on the screen of the smart wearable device.

[0132] For example, the longitude and latitude of the device's location point can also be displayed.

[0133] For example, in step 403, after receiving the user's output command, the smart wearable device responds to the command and outputs the positioning error in various ways to ensure that the user can intuitively and accurately understand the reliability of the current positioning information. First, the device can directly display the specific value of the positioning error on the screen, such as "Current positioning error: ±5 meters." This method is concise and clear, allowing the user to immediately understand the error range. Simultaneously, graphical representations, such as using circles or ellipses to display the positioning error range, with the center of the circle representing the current location and the circumference representing the maximum radius of the error, make the information more intuitive, especially suitable for visual map interfaces. Furthermore, color coding is also an effective method, using different colors (such as green indicating a smaller error and red indicating a larger error) to help users quickly determine the positioning accuracy.

[0134] For example, in situations where it's inconvenient to view the screen, the device can provide voice prompts to the user regarding the positioning error, such as "The current positioning error is 5 meters." This output method is particularly suitable for sports or driving scenarios, allowing users to obtain information without looking at the screen. When the positioning error exceeds a preset threshold, the device can also alert the user with a slight vibration. Combined with other output methods (such as screen display or voice prompts), the vibration feedback serves as a double confirmation, ensuring that the user does not miss important information.

[0135] For example, a dedicated status icon can be added to the interface to indicate the positioning error. This could include a signal strength bar displaying error levels from low to high, or an exclamation mark indicating a larger positioning error. Historical trajectories are displayed using a comparison of solid and dashed points. Solid points represent high-precision positioning points, while dashed points represent points with potentially larger errors. This allows users to visually see which locations are more reliable. If the errors at certain positioning points are too large, these points can be left disconnected to create a broken trajectory, preventing user confusion and maintaining the overall accuracy of the trajectory.

[0136] To provide more detailed analysis, the device can, for example, generate a complete positioning error report, including timestamps, latitude and longitude coordinates, and error values. Users can view this report at any time to understand the specifics of each positioning. Finally, the device can also synchronize positioning error information to the user's smartphone application, allowing users to view and analyze the data in more detail on a larger screen. This approach is particularly suitable for professional users who require precise positioning. Through these diverse output methods, smart wearable devices not only improve the user experience but also enhance the system's flexibility and reliability, ensuring users obtain more accurate positioning information in various environments.

[0137] In some possible embodiments, a first elevation angle and a second elevation angle are preset, wherein the first elevation angle is greater than the second elevation angle, and the elevation angle α is as follows: Figure 6 As shown, the elevation angle is the angle between the satellite and the horizon where the smart wearable device is located, and point P is the position of the smart wearable device. The method for obtaining the target ionospheric total electron content (TEC) data mentioned in step 202, which involves acquiring the TEC data within a preset range centered on the positioning information for a preset time period starting from the current moment, includes the following steps: Figure 7 As shown:

[0138] Step 701: Obtain the maximum TEC data in the first elevation angle interval and the second elevation angle interval respectively;

[0139] The elevation angle range is used to indicate the ionospheric region corresponding to the elevation angle centered on the positioning information.

[0140] For example, during high-precision positioning by smart wearable devices, ionospheric TEC has a significant impact on the propagation of GNSS signals. To optimize positioning accuracy, the device needs to assess ionospheric activity in different elevation angle ranges and select the most suitable TEC data as the target TEC data based on this information.

[0141] First, in step 701, the device needs to obtain the first elevation angle and the maximum TEC data within that elevation angle range. Specifically, the device first determines a specific elevation angle (referred to as the "first elevation angle"), and then obtains the maximum TEC data within the first elevation angle range corresponding to that elevation angle. The elevation angle refers to the angle between the line of sight from the receiver to the satellite and the horizontal plane, while the elevation angle range is used to indicate the ionospheric region within a specific elevation angle range, such as the first elevation angle range being 30° to 60°, the second elevation angle range being 60° to 90°, etc.

[0142] For each elevation angle interval, the equipment calculates or receives TEC data for all available satellites within that interval and identifies the maximum value. This is because the intensity of ionospheric activity can vary across different elevation angle intervals, and the maximum TEC data reflects the highest level of ionospheric activity within that interval. The impact of ionospheric activity on GNSS signals depends on the thickness of the ionosphere and the path length the signal passes through; typically, signals at lower elevation angles have longer paths, traversing more ionospheric regions, and are therefore more susceptible to the effects of ionospheric activity. By analyzing the maximum TEC data across different elevation angle intervals, the equipment can better assess the impact of ionospheric activity on positioning accuracy.

[0143] Step 702: Obtain the number of satellites within the first elevation angle interval and the number of satellites within the first elevation angle interval, respectively;

[0144] Next, in step 702, the device counts the number of visible satellites in the first elevation angle interval and the second elevation angle interval, respectively. These two elevation angle intervals can be adjacent or non-adjacent, depending on the application scenario and device settings. For each elevation angle interval, the device counts the number of currently visible satellites. This step is to evaluate the amount of observation data in each elevation angle interval, thereby determining which interval's TEC data is more reliable.

[0145] If the maximum TEC data in the first elevation angle range is less than the maximum TEC data in the second elevation angle range...

[0146] Step 703: The number of satellites in the first elevation angle interval is greater than the number of satellites in the second elevation angle interval, and the target TEC data is obtained; the target TEC data is the maximum TEC data in the first elevation angle interval;

[0147] Step 704: The number of satellites in the first elevation angle interval is less than the number of satellites in the second elevation angle interval, and the target TEC data is obtained; the target TEC data is the maximum TEC data in the second elevation angle interval.

[0148] If the maximum TEC data in the first elevation angle interval is less than the maximum TEC data in the second elevation angle interval, then a further comparison of the number of satellites in the two intervals is needed to determine the target TEC data. Specifically:

[0149] If the number of satellites in the first elevation angle interval is greater than the number of satellites in the second elevation angle interval, even if the maximum TEC data in the first elevation angle interval is smaller, the device will select the maximum TEC data in the first elevation angle interval as the target TEC data because more satellites provide observation data.

[0150] Conversely, if there are more satellites in the second elevation angle range, the device will select the largest TEC data in the second elevation angle range as the target TEC data.

[0151] When selecting target TEC data, the equipment needs to consider not only the size of the TEC data but also the richness of the observation data. More satellites mean more observation data, which can improve positioning accuracy and reliability. Therefore, if the maximum TEC data in two elevation angle intervals are inconsistent, the equipment will prioritize the maximum TEC data in the interval with more satellites as the target TEC data.

[0152] By comprehensively considering TEC data and the number of satellites, the device can make optimal decisions in complex environments, providing users with more reliable positioning services.

[0153] For example, there are many factors that affect ionospheric TEC data, and in actual operation, more situations may need to be considered. This application will not provide examples of each of these factors in the embodiments.

[0154] It should be understood that, although Figure 2-5 and Figure 7 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 2-5 and Figure 7 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0155] In some embodiments, such as Figure 8 As shown, a positioning point display device 800 is provided, including: a receiving module 801 and a display module 802, wherein:

[0156] The receiving module 801 is used to obtain the positioning information of the smart wearable device; and to acquire the total electron content (TEC) data of the target ionosphere within a preset range centered on the positioning information for a preset time period starting from the current time.

[0157] The display module 802 is configured to prevent the smart wearable device from displaying the location information when the total electron content (TEC) data of the target ionosphere is greater than a preset TEC threshold value.

[0158] Further limitations regarding the positioning point display device can be found in the limitations of the positioning point display method above, and will not be repeated here. Each module in the aforementioned device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in hardware or independently of the processor in the terminal device, or stored in software in the memory of the terminal device, so that the processor can call and execute the corresponding operations of each module.

[0159] Another embodiment provides a storage medium for storing a computer program. This computer program contains instructions for implementing the methods described in the embodiments of this application. By installing this computer program on a computer, the computer can execute the corresponding methods.

[0160] Another embodiment provides a computer program product that includes computer program code. When this computer program code is run on a computer, it causes the computer to implement the methods proposed in the embodiments of this application. Thus, a user can implement the methods of the embodiments of this application by using this computer program product.

[0161] For example, Figure 9 This is a schematic block diagram of another positioning point display device provided in the embodiments of this application.

[0162] Figure 9 The positioning point display device 900 shown consists of four main parts: a processor 901, a memory 902, a communication interface 903, and a bus 904. Each part has its specific function and role, and these components and their functions in the embodiments of this application will be explained in detail below.

[0163] The processor 901 is the core control unit of the positioning point display device, responsible for performing various calculations and processing tasks, including but not limited to acquiring the user's current location information, evaluating the total electron content (TEC) data of the ionosphere, determining the ionospheric activity state, and calculating positioning errors. Specifically, the processor 901 processes satellite signals from the GNSS receiver module to calculate precise geographical location information; acquires TEC data within a preset range from the server or built-in module and calculates the maximum value of the target TEC data; based on the comparison result between the target TEC data and a preset threshold value, it decides whether to display positioning information and controls the enabling or disabling of related functions; and calculates and outputs the positioning error to improve the user experience.

[0164] The memory 902 is used to store various types of data and program code required for the operation of the device, ensuring the normal operation and efficient processing of the system. It stores operating system and application code, user configuration parameters and historical records, acquired TEC data, positioning information and calculated positioning errors, as well as pre-set TEC threshold values ​​and other constant parameters.

[0165] Communication interface 903 is responsible for data interaction with external devices and services, ensuring that the device can obtain necessary support data and upload key information in real time. It communicates with the server through API interfaces or other protocols to obtain the latest ionospheric TEC data and uploads the calculated positioning error and other feedback information to the server. It also supports connections with other smart devices, such as mobile devices and smart home systems, enabling a wider range of application scenarios.

[0166] Bus 904 serves as an internal communication channel, connecting processor 901, memory 902, and communication interface 903 to ensure efficient data and instruction transmission between components. Bus 904 implements data read and write operations between processor 901 and memory 902, coordinates data exchange between processor 901 and communication interface 903, ensures smooth external communication, and provides a stable and efficient internal communication platform that supports multi-task concurrent processing, thereby improving overall system performance.

[0167] This design effectively avoids displaying incorrect positioning points due to ionospheric activity, improving the user experience and overall system performance, while reducing power consumption and bandwidth usage, ensuring efficient operation.

[0168] It should be understood that, in the embodiments of this application, the processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0169] In implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software. The steps of the method disclosed in the embodiments of this application can be directly manifested as execution by a hardware processor, or as a combination of hardware and software modules within the processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor executes the instructions in the memory, combining them with its hardware to complete the steps of the above method. To avoid repetition, detailed descriptions are omitted here.

[0170] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this application.

[0171] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0172] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0173] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0174] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0175] If the aforementioned function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application embodiment, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0176] The above description is merely a specific implementation of the embodiments of this application, but the protection scope of the embodiments of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the embodiments of this application should be included within the protection scope of the embodiments of this application. Therefore, the protection scope of the embodiments of this application should be determined by the protection scope of the claims.

Claims

1. A method for displaying positioning points, characterized in that, Applications in smart wearable devices, including: Obtain the location information of the smart wearable device; Acquire the Total Electron Content (TEC) data of the target ionosphere within a preset range centered on the location information, starting from the current time and within a preset time period. When the total electron content (TEC) data of the target ionosphere exceeds a preset TEC threshold, the smart wearable device will not display the location information.

2. The method according to claim 1, characterized in that, The location information includes the current location information of the smart wearable device. The acquisition of Total Electron Content (TEC) data of the target ionosphere within a preset range centered on the location information for a preset time period starting from the current moment includes: Acquire TEC data corresponding to all grids within a preset range centered on the current location information within a preset time period starting from the current time, wherein each grid is used to indicate the smallest area into which the preset range area centered on the current location information is divided; From the TEC data corresponding to all the grids, the target TEC data is obtained, which is the maximum value among the TEC data corresponding to all the grids.

3. The method according to claim 1, characterized in that, The method further includes: When the total electron content (TEC) data of the target ionosphere exceeds a preset TEC threshold, the positioning function is disabled. The positioning function includes at least one of the following: movement trajectory display, navigation, and positioning.

4. The method according to any one of claims 1-3, characterized in that, The method further includes: Obtain the positioning error; Receive output commands; In response to the output command, the positioning error is output.

5. The method according to claim 4, characterized in that, The obtained positioning error includes: Obtain the location information of multiple positioning points within a preset range, wherein the location information includes the longitude and latitude of the positioning points; Obtain the average longitude and latitude of the multiple positioning points; The positioning error is obtained, which is the value with the largest absolute value among the distance differences between the average value and the plurality of positioning points.

6. The method according to claim 1, characterized in that, A first elevation angle and a second elevation angle are preset, wherein the first elevation angle is greater than the second elevation angle, and the elevation angle is the angle between the satellite and the horizon where the smart wearable device is located. The method for acquiring the total ionospheric electron content (TEC) data of a target within a preset range centered on the positioning information within a preset time period starting from the current time includes: The maximum TEC data within the first elevation angle interval and the second elevation angle interval are obtained respectively, wherein the elevation angle interval is used to indicate the ionospheric region corresponding to the elevation angle centered on the positioning information; The number of satellites in the first elevation angle interval and the number of satellites in the first elevation angle interval are obtained respectively; If the maximum TEC data in the first elevation angle range is less than the maximum TEC data in the second elevation angle range... If the number of satellites in the first elevation angle interval is greater than the number of satellites in the second elevation angle interval, target TEC data is obtained; the target TEC data is the maximum TEC data in the first elevation angle interval. The number of satellites in the first elevation angle interval is less than the number of satellites in the second elevation angle interval, and target TEC data is obtained; the target TEC data is the maximum TEC data in the second elevation angle interval.

7. The method according to claim 1, characterized in that, The method further includes: When the target total electron content (TEC) data of the ionosphere is less than or equal to a preset TEC threshold, the smart wearable device displays the location information.

8. A positioning point display device, characterized in that, Applications in smart wearable devices, including: The receiving module is used to obtain the positioning information of the smart wearable device; and to acquire the total electron content (TEC) data of the target ionosphere within a preset range centered on the positioning information for a preset time period starting from the current time. The display module is configured to prevent the smart wearable device from displaying the location information when the total electron content (TEC) data of the target ionosphere exceeds a preset TEC threshold.

9. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement a positioning point display method as described in any one of claims 1-7.

10. A storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device is able to perform a positioning point display method as described in any one of claims 1-7.

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