Base station positioning dynamic deviation correction method based on base point

Abstract

The invention discloses a base-point-based base station positioning dynamic deviation correction method, relates to the technical field of terminal positioning, and solves the problems that terminal equipment mostly depends on fixed base station signals, cannot effectively cope with dynamic changes and interference, lacks effective automatic error correction and real-time adaptive capacity, and is inconvenient to use. And a high-reliability positioning result is difficult to provide in a rapidly changing environment. The dynamic deviation correction method comprises the following steps: acquiring and processing longitude and latitude data transmitted by terminal equipment as a current positioning point of the terminal equipment; measuring and correcting the distance deviation between the current positioning point and the last positioning point; judging the distance deviation according to a preset distance threshold value, and selecting an effective positioning point in combination with a preset positioning point selection mechanism; performing deviation correction calculation on the effective positioning points according to a time variable deviation correction mechanism to obtain final positioning points; updating and optimizing the base point according to the final positioning point in combination with a base point updating mechanism; and by dynamically updating the base point and introducing a time-distance coupling deviation correction mechanism, the positioning precision is optimized, and the error rate is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of terminal positioning, and particularly to a dynamic deviation correction method for base station positioning based on reference points. Background Art

[0002] With the popularization of the Internet of Things, smart cities, and location-based services (LBS), the traditional base station positioning technology has exposed significant defects due to problems such as environmental interference and signal attenuation. For example, in complex urban environments, multipath effects, non-line-of-sight propagation (NLOS), and uneven base station distribution can lead to positioning errors reaching the order of hundreds of meters, making it difficult to meet the requirements of high-precision scenarios (such as emergency rescue and autonomous driving). In addition, the static base station positioning model cannot adapt to dynamic environmental changes, such as sudden weather changes, temporary obstacles, or base station failures, further exacerbating the positioning drift problem.

[0003] Early base station positioning relied on single parameters such as received signal strength indication (RSSI) or time difference of arrival (TDOA), lacking a dynamic feedback mechanism for real-time environmental parameters. With the deployment of 5G networks and the improvement of edge computing capabilities, the fusion of multi-source data (such as base station signals, inertial sensors, and map information) has become possible, providing a technical basis for dynamic deviation correction. At the same time, the industry's requirements for positioning accuracy have shifted from "meter-level" to "sub-meter-level". For example, centimeter-level positioning is required for logistics tracking to optimize route planning, which is difficult to achieve with traditional methods.

[0004] The regulatory requirements for the positioning accuracy of emergency calls in the public safety field have promoted the development of deviation correction technologies. In addition, commercial scenarios such as indoor navigation and shared economy device management also urgently need low-cost and highly robust positioning solutions. The dynamic deviation correction method based on reference points effectively balances accuracy and computational cost by introducing a reference point network, combining real-time environmental modeling, and adaptive algorithms, becoming the key path to solve the above contradictions.

[0005] Patent No. CN202410584991.6 discloses a method for LBS positioning deviation correction, including the following steps: S1, obtaining the WGS84 longitude and latitude positioning coordinates where the LBS positioning terminal is located, and obtaining n (n≥3) consecutive positioning coordinates; S2, calculating the spherical distance between every two adjacent positioning coordinate points among the n consecutive positioning coordinates obtained in step S1, and putting them into set D; S3, dividing set D into set and set, and determining the deviation value in set D; S4, calculating the average value of set ; S5, calculating the deviation correction angle of the deviation value, and obtaining the corrected new coordinates according to the deviation correction angle and ; S6, deleting the corrected deviation value from set, repeating step S5, and traversing each deviation value in set until set is an empty set; S7, taking the coordinates after updating set as the final positioning coordinates where the LBS positioning terminal is located. The above invention adopts a pure algorithm verification scheme independent of traditional positioning devices, which can effectively identify and correct abnormal coordinate points that deviate significantly from the normal distribution range.

[0006] Patent number CN202311523555.X discloses a location correction method and device based on heterogeneous data of base station communication. According to the generation timing of communication data of the identification code to be corrected, base station data associated before and after the timing is extracted; the communication data of the identification code to be corrected is read and the communication data is saved in chronological order; the base station data associated in chronological order is read, and the base station coupling data that meets specific conditions is retained, the base station coupling relationship is mined to form a base station coupling library; based on the time and space attributes of the communication data of the identification code, the DBSCAN algorithm is used to divide the communication data, and the initial position of the identification code to be corrected is calculated; combined with the base station coupling data and the list of base stations and connection durations connected to the initial position of the identification code to be corrected, the initial position of the identification code to be corrected is further corrected using the base station coupling correction algorithm, and the corrected position of the identification code to be corrected is generated. Compared with the original residence position calculated only by weighted average of base station positions, the accuracy of the above invention has been significantly improved.

[0007] Although the above patent can complete the positioning correction of terminal devices, terminal devices mostly rely on fixed base station signals, cannot effectively cope with dynamic changes and interference, lack effective automatic error correction and real-time adaptation capabilities, and it is difficult to provide highly reliable positioning results in a rapidly changing environment. Summary of the Invention

[0008] The purpose of the present invention is to provide a dynamic correction method for base station positioning based on reference points, which can optimize the positioning accuracy, reduce the error rate, and have strong adaptability by dynamically updating the reference points and introducing a time variable correction mechanism.

[0009] The present invention uses the following technical solutions: A dynamic correction method for base station positioning based on reference points, which successively includes the following steps; S1: Obtain and process the longitude and latitude data transmitted by the terminal device and use it as the current positioning point of the terminal device; S2: Measure and correct the distance deviation between the current positioning point and the previous positioning point; S3: Judge the distance deviation according to a preset distance threshold and select an effective positioning point in combination with a preset positioning point selection mechanism; S4: Perform correction calculation on the effective positioning point according to the time variable correction mechanism to obtain the final positioning point; S5: Update and optimize the reference point according to the final positioning point in combination with the reference point update mechanism.

[0010] Preferably, step S1 includes the following steps: S11: The terminal device transmits terminal original data using the HTTP / HTTPS protocol or the MQTT protocol; S12: Convert the original terminal data to the standard GPS coordinate system to obtain the initial longitude and latitude data; S13: Use a sliding window to detect and verify the initial longitude and latitude data; S14: If the longitude and latitude in the initial longitude and latitude data are not within the preset range, determine that the current initial longitude and latitude data is illegal and abnormal data, and temporarily remove and mark the illegal and abnormal data using a Bloom filter; if the longitude and latitude in the initial longitude and latitude data are within the preset range, determine that the current initial longitude and latitude data is normal and qualified data, and cache the normal and qualified data in real time; S15: Add a timestamp and a device serial number to the normal and qualified data, and then use it as the current positioning point of the terminal device.

[0011] Preferably, step S2 includes the following steps: S21: Calculate the distance difference between the current positioning point and the previous positioning point based on the radius of curvature of the earth using the haversine function or the ellipsoid model function; S22: Add an error weight coefficient to the distance difference according to the terminal type to obtain a weighted distance difference; S23: Correct the weighted distance difference using a signal reflection attenuation model according to the terminal usage scenario to obtain a distance deviation.

[0012] Preferably, step S3 includes the following steps: S31: Automatically generate a distance threshold according to the theoretical accuracy of the terminal device; S32: Compare and judge the distance threshold with the distance deviation; S33: If the distance deviation is less than or equal to the distance threshold, mark the current positioning point as a valid positioning point in combination with the positioning point selection mechanism; If the distance deviation is greater than the distance threshold, mark the current positioning point as a suspected drift point in combination with the positioning point selection mechanism, store it in the device log, and at the same time detect the movement trend of the previous N valid positioning points; S34: If the movement trend is continuously deviated, determine that the current positioning point is a valid movement and mark it as a valid positioning point; if the movement trend is jump deviated, mark the previous positioning point as a valid positioning point.

[0013] Preferably, step S4 includes the following steps: S41: Use a dynamic sliding window to statistically judge the cumulative value of the moving distance of the valid positioning points according to the terminal device status; S42: If the cumulative value of the moving distance is greater than or equal to the physical threshold, determine that the cumulative value of the moving distance is invalid data; if the cumulative value of the moving distance is less than the physical threshold, determine that the cumulative value of the moving distance is valid data, and at the same time perform deviation correction calculation on the valid positioning points; S43: Denoise the effective positioning points by using the Kalman filtering algorithm in combination with the particle filtering algorithm to obtain noise-free positioning points; S44: Perform exponentially weighted averaging on the noise-free positioning points according to the time variable deviation correction mechanism to obtain the final positioning points.

[0014] Preferably, step S5 includes the following steps: S51: Judge the effectiveness and movement trend of M consecutive final positioning points; S52: If they are all effective positioning points and the movement trends are consistent, determine the current final positioning point as the base point; if they are all effective positioning points but the movement trends are opposite, keep the base point unchanged and record it in the time series database; S53: Adaptively optimize the physical threshold in combination with the deviation correction calculation times of the effective positioning points; S54: If the deviation correction calculation times are greater than or equal to the set value, the terminal device automatically switches the positioning source and automatically marks the positioning error points; if the deviation correction calculation times are less than the set value, the terminal device keeps the positioning source unchanged.

[0015] Through judging the distance deviation between two points and introducing the time deviation correction mechanism, the present invention makes the positioning result more stable, reduces the accumulation of errors; can dynamically adapt in complex environments, avoids frequent failures or large deviations of traditional positioning systems; reduces the system calculation amount and improves the processing efficiency by intelligently screening and correcting the positioning data, ensuring the reliability of the system in high-speed movement or changing environments; enables the positioning system to continuously optimize under changing environments through the dynamic adjustment mechanism, meeting the requirements of accuracy and real-time performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0017] Figure 1 It is the principle block diagram of the base station positioning dynamic deviation correction method; Figure 2 It is the flow chart of the dynamic deviation correction method. DETAILED DESCRIPTION OF THE INVENTION

[0018] The following will make a detailed description of the present invention in combination with the drawings and embodiments: As Figure 1 - Figure 2 shown, a base station positioning dynamic deviation correction method based on a base point according to the present invention sequentially includes the following steps; S1: Acquire and process the longitude and latitude data transmitted by the terminal device and use it as the current positioning point of the terminal device; S2: Calculate and correct the distance deviation between the current positioning point and the last positioning point; S3: judging the distance deviation according to the preset distance threshold, and selecting a valid positioning point in combination with the preset positioning point selection mechanism; S4: Correction calculation is performed on the effective positioning point according to the time variable correction mechanism to obtain the final positioning point; S5: Update and optimize the base point according to the final positioning point combined with the base point update mechanism.

[0019] In the present invention, step S1 includes the following steps: S11: The terminal device transmits the original terminal data using HTTP / HTTPS protocol or MQTT protocol; In this embodiment, the terminal devices include mobile phones, vehicle-mounted devices, and IoT sensors; S12: Convert the original data of the terminal into the standard GPS coordinate system to obtain the initial longitude and latitude data; In this embodiment, the standard GPS coordinate system is the WGS-84 coordinate system; S13: Using a sliding window to detect and verify the initial longitude and latitude data; S14: If the longitude and latitude in the initial longitude and latitude data are not within the preset range, the current initial longitude and latitude data is determined to be illegal abnormal data, and the illegal abnormal data is temporarily removed and marked using the Bloom filter; if the longitude and latitude in the initial longitude and latitude data are within the preset range, the current initial longitude and latitude data is determined to be normal qualified data, and the normal qualified data is cached in real time; S15: Add a timestamp and a device serial code to the normal qualified data, and use them as the current positioning point of the terminal device.

[0020] In the present invention, step S2 includes the following steps: S21: Calculate the distance difference between the current positioning point and the last positioning point using a haversine function or an ellipsoid model function based on the radius of curvature of the earth; S22: adding an error weight coefficient to the distance difference according to the terminal type to obtain a weighted distance difference; S23: Correct the weighted distance difference using a signal reflection attenuation model according to the terminal usage scenario to obtain a distance deviation.

[0021] In this embodiment, the terminal usage scenarios include urban canyon and indoor scenarios; In the present invention, step S3 includes the following steps: S31: automatically generating a distance threshold according to the theoretical accuracy of the terminal device; S32: Compare and determine the distance threshold with the distance deviation; S33: If the distance deviation is less than or equal to the distance threshold, mark the current positioning point as a valid positioning point in combination with the positioning point selection mechanism; If the distance deviation is greater than the distance threshold, mark the current positioning point as a suspected drift point in combination with the positioning point selection mechanism, store it in the device log, and at the same time detect the movement trend of the previous N valid positioning points; S34: If the movement trend is a continuous deviation, determine that the current positioning point is a valid movement and mark it as a valid positioning point; if the movement trend is a jump deviation, mark the previous positioning point as a valid positioning point.

[0022] In the present invention, step S4 includes the following steps: S41: Use a dynamic sliding window according to the terminal device status to statistically determine the cumulative value of the moving distance of the valid positioning points; In this embodiment, the terminal device status includes network disconnection, movement, and stillness; S42: If the cumulative value of the moving distance is greater than or equal to the physical threshold, determine that the cumulative value of the moving distance is invalid data; if the cumulative value of the moving distance is less than the physical threshold, determine that the cumulative value of the moving distance is valid data, and at the same time perform deviation correction calculation on the valid positioning points; S43: Use the Kalman filter algorithm in combination with the particle filter algorithm to denoise the valid positioning points to obtain noise-free positioning points; S44: Perform exponential weighted averaging on the noise-free positioning points according to the time variable deviation correction mechanism to obtain the final positioning point.

[0023] In the present invention, step S5 includes the following steps: Step S5 includes the following steps: S51: Judge the validity and movement trend of M consecutive final positioning points; S52: If they are all valid positioning points and the movement trends are the same, determine that the current final positioning point is the base point; if they are all valid positioning points but the movement trends are opposite, keep the base point unchanged and record it in the time series database; S53: Adaptively optimize the physical threshold in combination with the deviation correction calculation times of the valid positioning points; S54: If the deviation correction calculation times are greater than or equal to the set value, the terminal device automatically switches the positioning source and automatically marks the positioning error points; if the deviation correction calculation times are less than the set value, the terminal device keeps the positioning source unchanged.

[0024] Embodiment 1: Mobile phones, in-vehicle devices, IoT sensors, etc. use the HTTP / HTTPS protocol or the MQTT protocol to transmit the original terminal data, convert the original terminal data to the standard GPS coordinate system, obtain the initial longitude and latitude data, and use a sliding window to detect and verify the initial longitude and latitude data: If the longitude and latitude in the initial longitude and latitude data are not within the preset range, it is determined that the current initial longitude and latitude data is illegal and abnormal data, and the Bloom filter is used to temporarily eliminate and mark the illegal and abnormal data; If the longitude and latitude in the initial longitude and latitude data are within the preset range, it is determined that the current initial longitude and latitude data is normal and qualified data, and the normal and qualified data is cached in real time; Add a timestamp and a device serial number to the normal and qualified data, and then use it as the current positioning point of the terminal device.

[0025] Based on the radius of curvature of the earth, use the haversine function or the ellipsoid model function to calculate the distance difference between the current positioning point and the previous positioning point, add an error weight coefficient to the distance difference according to the terminal type to obtain the weighted distance difference, and use the signal reflection attenuation model to correct the weighted distance difference according to the terminal usage scenario to obtain the distance deviation; According to the theoretical accuracy of the terminal device, automatically generate a distance threshold; Compare and judge the distance threshold with the distance deviation: If the distance deviation is less than or equal to the distance threshold, mark the current positioning point as a valid positioning point in combination with the positioning point selection mechanism; If the distance deviation is greater than the distance threshold, mark the current positioning point as a suspected drift point in combination with the positioning point selection mechanism, store it in the device log, and at the same time detect the movement trend of the previous N valid positioning points: If the movement trend is continuously deviated, it is determined that the current positioning point is a valid movement and marked as a valid positioning point; If the movement trend is a jump deviation, mark the previous positioning point as a valid positioning point; According to the terminal device status, use a dynamic sliding window to statistically judge the cumulative value of the moving distance of the valid positioning points: If the cumulative value of the moving distance is greater than or equal to the physical threshold, it is determined that the cumulative value of the moving distance is invalid data; If the cumulative value of the moving distance is less than the physical threshold, it is determined that the cumulative value of the moving distance is valid data, and at the same time perform deviation correction calculation on the valid positioning points; Use the Kalman filter algorithm combined with the particle filter algorithm to denoise the valid positioning points to obtain the noise-free positioning points; Perform exponential weighted averaging on the noise-free positioning points according to the time variable deviation correction mechanism to obtain the final positioning point.

[0026] Judge the validity and movement trend of consecutive M final positioning points: If they are all valid positioning points and have the same movement trend, then determine the current final positioning point as the base point; if they are all valid positioning points but have opposite movement trends, keep the base point unchanged and record it in the time series database; combine the deviation correction calculation times of the valid positioning points to adaptively optimize the physical threshold; if the deviation correction calculation times are greater than or equal to the set value, the terminal device automatically switches the positioning source and automatically marks the positioning error points; if the deviation correction calculation times are less than the set value, the terminal device keeps the positioning source unchanged.

[0027] Embodiment 2: Receive the latitude and longitude data uploaded by the terminal; calculate the distance deviation between the current positioning point and the previous positioning point; judge whether the distance exceeds the threshold and select the positioning point. If the calculated distance deviation between the two points exceeds the predetermined threshold, the system will select the previous valid positioning point as the current position. If the distance deviation is within the acceptable range, the current positioning point is considered valid and the current positioning point is selected as the position.

[0028] Introduce a time variable for deviation correction calculation. To further improve the positioning accuracy, the system introduces a time variable for deviation correction calculation. By comparing the time interval and position difference between positioning points, if the distance between positioning points exceeds the preset value within the specified time window, the current positioning point is considered invalid and the previous valid positioning point is continued to be used.

[0029] When the current positioning point is considered valid, the system updates the positioning data and uses it as the new base point. Subsequently, the system continues to receive new positioning data and repeats the above steps for subsequent processing to ensure continuous optimization of the positioning accuracy.

[0030] First, by introducing dynamic base point update and distance deviation judgment, the errors caused by signal fluctuations and environmental interference are effectively avoided, and the positioning accuracy is improved. In traditional base station positioning, signal attenuation and reflection will cause unstable accuracy, while the present invention makes the positioning result more stable and reduces the accumulation of errors by judging the distance deviation between two points and introducing a time deviation correction mechanism. Secondly, the present invention can dynamically adapt in complex environments and avoids the problems of frequent failure or large deviation of traditional positioning systems. By intelligently screening and correcting the positioning data, the system calculation amount is reduced, the processing efficiency is improved, and the reliability of the system in high-speed movement or changing environments is ensured. In addition, the dynamic adjustment mechanism of the present invention enables the positioning system to continuously optimize in a changing environment and meet the requirements of accuracy and real-time performance.

Claims

1. A base station positioning dynamic deviation correction method based on base points, characterized in that: The method comprises the following steps in sequence; S1: Acquire and process the longitude and latitude data transmitted by the terminal device and use it as the current positioning point of the terminal device; S2: Calculate and correct the distance deviation between the current positioning point and the last positioning point; S3: judging the distance deviation according to the preset distance threshold, and selecting a valid positioning point in combination with the preset positioning point selection mechanism; S4: Correction calculation is performed on the effective positioning point according to the time variable correction mechanism to obtain the final positioning point; S5: Update and optimize the base point according to the final positioning point combined with the base point update mechanism.

2. The base station positioning dynamic deviation correction method based on base points according to claim 1, characterized in that: The step S1 includes the following steps: S11: The terminal device transmits the original terminal data using HTTP / HTTPS protocol or MQTT protocol; S12: Convert the original data of the terminal into the standard GPS coordinate system to obtain the initial longitude and latitude data; S13: Using a sliding window to detect and verify the initial longitude and latitude data; S14: If the longitude and latitude in the initial longitude and latitude data are not within the preset range, the current initial longitude and latitude data is determined to be illegal abnormal data, and the illegal abnormal data is temporarily removed and marked using the Bloom filter; if the longitude and latitude in the initial longitude and latitude data are within the preset range, the current initial longitude and latitude data is determined to be normal qualified data, and the normal qualified data is cached in real time; S15: Add a timestamp and a device serial code to the normal qualified data, and use them as the current positioning point of the terminal device.

3. The base station positioning dynamic deviation correction method based on base points according to claim 1, characterized in that: The step S2 comprises the following steps: S21: Calculate the distance difference between the current positioning point and the last positioning point using a haversine function or an ellipsoid model function based on the radius of curvature of the earth; S22: adding an error weight coefficient to the distance difference according to the terminal type to obtain a weighted distance difference; S23: Correct the weighted distance difference using a signal reflection attenuation model according to the terminal usage scenario to obtain a distance deviation.

4. The base station positioning dynamic deviation correction method based on base points according to claim 1, characterized in that: The step S3 comprises the following steps: S31: automatically generating a distance threshold according to the theoretical accuracy of the terminal device; S32: Compare and judge the distance threshold and the distance deviation; S33: if the distance deviation is less than or equal to the distance threshold, the current positioning point is marked as a valid positioning point in combination with the positioning point selection mechanism; If the distance deviation is greater than the distance threshold, the current positioning point is marked as a suspected drift point in combination with the positioning point selection mechanism and stored in the device log. At the same time, the movement trend of the first N valid positioning points is detected; S34: If the movement trend is continuous deviation, the current positioning point is determined to be a valid movement and is marked as a valid positioning point; if the movement trend is a jump deviation, the last positioning point is marked as a valid positioning point.

5. The base station positioning dynamic deviation correction method based on base points according to claim 1, characterized in that: The step S4 comprises the following steps: S41: Statistically determine the cumulative value of the moving distance of the valid positioning point using a dynamic sliding window according to the terminal device status; S42: If the accumulated moving distance value is greater than or equal to the physical threshold, the accumulated moving distance value is determined to be invalid data; if the accumulated moving distance value is less than the physical threshold, the accumulated moving distance value is determined to be valid data, and correction calculation is performed on the valid positioning point at the same time; S43: Using Kalman filter algorithm combined with particle filter algorithm to denoise the effective positioning points and obtain noise-free positioning points; S44: Exponentially weighted average the noise-free positioning points according to the time-variable deviation correction mechanism to obtain the final positioning point.

6. The base station positioning dynamic deviation correction method based on base points according to claim 1, characterized in that: The step S5 includes the following steps: S51: Judge the validity and movement trend of M consecutive final positioning points; S52: If they are all valid positioning points and the movement trends are consistent, determine the current final positioning point as the base point; if they are all valid positioning points but the movement trends are opposite, keep the base point unchanged and record it in the time series database; S53: Combine the deviation correction calculation times of the valid positioning points to adaptively optimize the physical threshold; S54: If the deviation correction calculation times are greater than or equal to the set value, the terminal device automatically switches the positioning source and automatically marks the positioning error points; if the deviation correction calculation times are less than the set value, the terminal device keeps the positioning source unchanged.

Images