An indoor TOA positioning method and device based on adaptive correction factor

Abstract

The application discloses an indoor TOA positioning method and device based on an adaptive correction factor, and belongs to the technical field of indoor positioning. The method comprises the following steps: determining the distance between a mobile station and multiple base stations based on TOA measurement values, establishing multiple range circles with each base station as the center and the distance as the radius, and determining the minimum range circle; constructing an error correction equation, introducing a correction factor to dynamically correct the TOA measurement values; counting the number of intersection points between any two range circles under different correction factors in the minimum range circle, taking the correction factor value corresponding to the peak value of the number of intersection points as the optimal error correction parameter; correcting the TOA measurement values based on the error correction equation by using the optimal error correction parameter, and calculating the coordinates of the mobile station based on the corrected TOA measurement values to realize indoor positioning. The application realizes simple, non-iterative, high-precision and strong anti-interference indoor positioning, can meet general indoor positioning requirements, and improves the reliability and efficiency of the positioning system.

Description

Technical Field

[0001] This invention belongs to the field of indoor positioning technology, specifically relating to an indoor TOA positioning method and device based on an adaptive correction factor. Background Technology

[0002] With the rapid development of wireless communication networks and mobile internet, location-based services (LBS), such as target tracking, security alerts, and location-based advertising, have become one of the most promising and promising applications. Currently, the Global Positioning System (GPS) is the most commonly used outdoor location sensing technology. However, in many scenarios, such as indoor areas, underground spaces, tunnels, and urban areas with tall buildings, the performance of satellite navigation is unsatisfactory. The main reason for this is the weak satellite signals reaching the ground and their inability to penetrate buildings to determine the receiver's location. In such situations, using GPS becomes impractical. When satellite navigation systems are unavailable, indoor positioning technology can effectively solve the problem.

[0003] Currently, most methods for providing indoor positioning and navigation services rely on Wi-Fi, Bluetooth, or optical sensors, which can be densely distributed indoors. However, these methods suffer from limited coverage, susceptibility to signal interference, high costs, and uncertain business models. In contrast, mobile stations based on wireless communication base stations can avoid these problems.

[0004] Because the signal between the mobile station and the wireless communication base station is easily interfered with by obstacles and multipath effects, accurately estimating the mobile station's location based on measurements containing this noise is a problem that needs to be solved. Although the location estimation problem has been extensively studied, some issues still require further improvement. The efficiency and accuracy of location estimation remain key challenges for indoor positioning in complex non-line-of-sight (NLOS) scenarios. NLOS scenarios are ubiquitous in modern cities, both indoors (e.g., basements, shopping malls) and outdoors (e.g., urban areas with high-rise buildings).

[0005] Current positioning algorithms can be broadly categorized into range-based and range-free algorithms. Most existing positioning systems are range-based, and their positioning accuracy is generally higher than that of range-free algorithms. Common range-based algorithms include Time of Arrival (TOA), Time Difference of Arrival (TDOA), Angle of Arrival (AOA), and Received Signal Strength Indication (RSSI). This invention focuses on TOA-based positioning algorithms. Currently, indoor positioning algorithms based on TOA mainly include Least Squares Localization (LS), Weighted Least Squares Localization (WLS), Nano algorithm, neural network positioning algorithms, and Range Error Classification Localization (REC) algorithms. LS positioning algorithms fail to deeply analyze the causes of errors, only approximating the true location point through iteration. The choice of initial values ​​significantly impacts positioning accuracy, and the algorithm lacks robustness in complex scenarios. For WLS, Nano, and REC positioning algorithms, it is first necessary to identify non-line-of-sight (NLOS) propagation measurements, and then perform orientation correction or assign different weights to each observation based on the identification results. Nguyen et al. used a deep long-short-term memory (LSTM) network combined with convolutional neural network (CNN) features to identify NLOS propagation measurements in wireless local area networks (WLANs) based on RSSI. The performance of this method in indoor propagation environments has been verified. However, in real-world environments, it is difficult to identify NLOS propagation based solely on TOA measurements, and positioning accuracy cannot be guaranteed. Wu et al. proposed an artificial neural network positioning algorithm based on error learning and matching of TOA measurements. Although simulation results can demonstrate the effectiveness of this positioning algorithm, it still needs to be verified through actual experiments. Furthermore, the REC positioning algorithm is based on the maximum likelihood principle, which places high demands on the distribution of base stations. It has higher accuracy and stronger robustness when the base stations are evenly distributed.

[0006] Therefore, developing an indoor positioning algorithm that can efficiently and accurately identify NLOS propagation, reduce errors, and has low requirements for base station distribution in complex non-line-of-sight scenarios based solely on TOA measurements, while possessing strong robustness, is key to improving indoor positioning quality and promoting its widespread application. Summary of the Invention

[0007] In view of the above, the purpose of this invention is to provide an indoor TOA positioning method and device based on an adaptive correction factor. Starting from the causes of positioning errors, this invention introduces an adaptive error correction factor to eliminate or reduce the interference of various noises on TOA measurement values. Combined with the method of statistically analyzing the number of intersection points within the minimum circle and selecting intersection points based on standard deviation, the coordinates of mobile devices are accurately calculated. This achieves simple, iterative, high-precision, and interference-resistant indoor positioning, which can meet general indoor positioning needs and improve the reliability and efficiency of the positioning system.

[0008] To achieve the above-mentioned objectives, the present invention provides the following technical solution:

[0009] An indoor TOA positioning method based on an adaptive correction factor provided in this invention includes the following steps:

[0010] The distance between the mobile station and multiple base stations is determined based on the TOA measurement value. Multiple range circles are established with each base station as the center and the distance as the radius, and the smallest range circle is determined.

[0011] An error correction equation is constructed, in which a correction factor is introduced to dynamically correct the TOA measurement value;

[0012] Within the smallest range circle, count the number of intersections between any two range circles under different correction factors, and use the correction factor value corresponding to the peak value of the number of intersections as the optimal error correction parameter.

[0013] The TOA measurement value is corrected based on the error correction equation using the optimal error correction parameters, and the rover coordinates are calculated based on the corrected TOA measurement value to achieve indoor positioning.

[0014] Preferably, the minimum radius circle must satisfy the following condition: the mobile station is located within a circle centered on the base station and with the distance determined by the TOA measurement as its radius.

[0015] Preferably, the correction relationship defined by the error correction equation is that the correction factor is multiplied by the TOA measurement value to obtain the corrected TOA measurement value.

[0016] Preferably, the value of the correction factor is determined within the range of 0.5 to 1.

[0017] Preferably, the method for calculating the coordinates of the rover station includes:

[0018] Based on the optimal error correction parameters All TOA measurements are calibrated to generate a new range circle, and all intersections within the minimum range circle are selected and denoted as the initial set of intersections. ;

[0019] Calculate the initial set of intersection points Find the centroid coordinates and calculate the intersection points within the set. Distance to the center of mass Elimination distance greater than The intersection of the means yields the set of intermediate intersection points. ;

[0020] Calculate the set of intermediate intersection points Mean distance from the midpoint to the centroid with standard deviation Elimination distance greater than The intersection points are used to obtain the final set of intersection points. ;

[0021] Set of final intersection points The arithmetic mean of the coordinates of all intersection points is used as the final estimated coordinates of the mobile station.

[0022] Preferably, in a fixed indoor positioning environment, the optimal error correction parameters for multiple test locations are pre-determined, and an error correction parameter map covering the positioning area is generated by interpolation. When performing rapid positioning of the mobile station, the preset optimal correction parameters for the area where it is located are directly called from the error correction parameter map, and the TOA measurement value is corrected and calculated in one go using these parameters.

[0023] Preferably, in positioning applications in a specific area, the TOA measurement values ​​are uniformly corrected and calculated using universal optimal error correction parameters pre-calibrated for that area in the same positioning environment to improve positioning efficiency.

[0024] Secondly, embodiments of the present invention also provide an indoor TOA positioning device based on an adaptive correction factor, which is implemented using the above-mentioned indoor TOA positioning method based on an adaptive correction factor, including: a range constraint module, an error correction module, a parameter optimization module, and a coordinate positioning module;

[0025] The range constraint module is used to determine the distance between the mobile station and multiple base stations based on the TOA measurement value. Multiple range circles are established with each base station as the center and the distance as the radius, and the smallest range circle is determined among them.

[0026] The error correction module is used to construct an error correction equation, in which a correction factor is introduced to dynamically correct the TOA measurement value.

[0027] The parameter optimization module is used to count the number of intersections between any two range circles under different correction factors within the minimum range circle, and the correction factor value corresponding to the peak value of the number of intersections is used as the optimal error correction parameter.

[0028] The coordinate positioning module is used to correct the TOA measurement value based on the error correction equation using the optimal error correction parameters, and to calculate the rover coordinates based on the corrected TOA measurement value to achieve indoor positioning.

[0029] Thirdly, embodiments of the present invention also provide an electronic device, including a memory and one or more processors, wherein the memory is used to store a computer program, and the processor is used to implement the above-described indoor TOA positioning method based on adaptive correction factors when executing the computer program.

[0030] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which, when executed by a computer, implements the above-described indoor TOA positioning method based on adaptive correction factors.

[0031] Compared with the prior art, the beneficial effects of the present invention include at least the following:

[0032] This invention introduces an adaptive correction factor. Dynamic correction of TOA measurements effectively overcomes positive deviation interference caused by non-line-of-sight (NLOS) propagation. Simultaneously, the system utilizes a minimum-range circular constraint to locate the region, adaptively seeking the optimal region based on the statistical peak value of the number of circular intersections. This invention avoids the complex iterative process of traditional algorithms, significantly reducing computational complexity and time overhead. Furthermore, by using the standard deviation criterion to filter high-confidence intersection clusters, discrete error points are effectively eliminated, thus achieving stable and accurate positioning results even in environments with strong interference. Ultimately, this invention achieves indoor positioning with strong anti-interference capabilities, high computational efficiency, and reliable accuracy, significantly improving the practicality and reliability of TOA positioning methods in complex environments. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 This is a flowchart illustrating the indoor TOA positioning method based on adaptive correction factors provided in an embodiment of the present invention.

[0035] Figure 2 This is a diagram showing the relationship between the minimum range circle and the actual location of the mobile station (MS) provided in an embodiment of the present invention.

[0036] Figure 3 The different embodiments of the present invention provide The effect of the value on the correction of time delay error;

[0037] Figure 4 This is a statistical chart of the total number of intersection points within the minimum range circle provided in the embodiments of the present invention;

[0038] Figure 5 This is provided by the embodiments of the present invention. The effect of time delay error correction;

[0039] Figure 6 This is a schematic diagram of mobile station coordinate solving provided in an embodiment of the present invention;

[0040] Figure 7 This is the error distribution in the BAS-30 positioning environment provided in the embodiments of the present invention;

[0041] Figure 8 This is a contour map of the correction factor in the BAS-30 positioning environment provided in this embodiment of the invention;

[0042] Figure 9 This is a schematic diagram of the structure of an indoor TOA positioning device based on an adaptive correction factor provided in an embodiment of the present invention. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the scope of protection of this invention.

[0044] The inventive concept of this invention is as follows: Addressing the problems of large errors, susceptibility to interference, and complex calculations in existing TOA indoor positioning methods under wireless communication base station environments, particularly in non-line-of-sight (Line-of-Sight) environments, this invention provides an indoor TOA positioning method and device based on an adaptive correction factor. By introducing an adaptive correction factor, the TOA measurement value is dynamically adjusted and corrected according to real-time noise. Furthermore, a minimum range circle is innovatively defined, and the number of intersections between any two range circles within this minimum range circle is used as a statistical measure. The optimal parameters are determined by the peak value of the number of intersections under different correction factors. Then, considering the influence of discrete intersections, abnormal intersections are filtered and removed based on the standard deviation. Finally, the mobile device coordinates are accurately calculated using the filtered valid intersections, thereby effectively improving indoor positioning accuracy and stability while simplifying calculations.

[0045] like Figure 1As shown in the embodiment, an indoor TOA positioning method based on an adaptive correction factor is provided, including the following steps:

[0046] S1. Based on the TOA measurement value, determine the distance between the mobile station and multiple base stations. Establish multiple range circles with each base station as the center and the distance as the radius, and determine the smallest range circle among them.

[0047] In the embodiment, for a specific mobile station (MS), due to time delay error ( ) is a positive error ( And much greater than the measurement error caused by clock asynchrony, the mobile station must be located centered on the base station (BAS) and at a measurement distance ( Within a circle with a radius of , and defining a minimum circle, the measured distance is the time of arrival (TOA) multiplied by the signal transmission speed. For example... Figure 2 As shown, the data from the 1100 groups of mobile stations in Experiment 1 are all located within a radius of [missing information]. Within the circle. Based on this geometric constraint, restricting the subsequent search and calculation process to this minimum circle can significantly reduce the solution area, eliminate a large number of invalid solutions, and provide a reliable computational basis for subsequent error correction and intersection statistics.

[0048] S2, construct the error correction equation, in which a correction factor is introduced to dynamically correct the TOA measurement value.

[0049] In practical applications, non-line-of-sight (NLOS) positioning environments can cause time delay errors. Clock asynchrony can cause measurement errors. The elevation difference of base stations (BAS) is much smaller than the horizontal distance. Without considering elevation values, all the range circles cannot intersect at a single point; the intersection points are discretely distributed around the mobile stations (MS). As the accuracy of mobile network time services increases, measurement errors caused by clock asynchrony become more significant. Much smaller than time delay error For a set of BAS and MS, the error It is a small systematic error caused by a set of multiple BAS distributed around the MS. This can be eliminated by calculating the average value. .

[0050] In the embodiment, the distance between BAS and MS is taken into account in the NLOS positioning environment. Time delay error caused by NLOS positioning environment There is a positive correlation between them, and It is a positive error, a time delay error. The TOA measurement values ​​conform to a specific functional relationship as follows: To simplify the model, this invention introduces a correction factor. To describe time delay error and TOA measurement value ( The relationship between the two is given by the error correction equation: ,in Indicates the time delay error ratio. This indicates the corrected TOA measurement value. This represents the correction factor.

[0051] S3. Within the minimum range circle, count the number of intersections between any two range circles under different correction factors, and use the correction factor value corresponding to the peak value of the number of intersections as the optimal error correction parameter.

[0052] In the embodiments, such as Figure 3 As shown, based on experimental data analysis, excessively large or small values... This value is not conducive to eliminating or reducing the impact of time delay errors. Therefore, in the embodiments, The value is limited to a reasonable range of 0.5 to 1. As the value changes from 0.5 to 1, the number of intersection points between any two range circles within the smallest range circle increases, then decreases again. When... When the value is too small, the circle tends to separate. When When the value is close to 1, the intersection points between the circles become more dispersed. For example... Figure 5 As shown, when When the value is appropriate, the actual intersection points are concentrated on a single point. This value provides the best correction for time delay errors. For example... Figure 4 As shown, the total number of intersection points within the smallest circle. As a statistical indicator, determine Peak value, used to obtain the optimal value. The value is used as the optimal error correction parameter.

[0053] S4 uses the optimal error correction parameters to correct the TOA measurement value based on the error correction equation, and calculates the rover coordinates based on the corrected TOA measurement value to achieve indoor positioning.

[0054] In the embodiments, the optimal one is determined After taking the values, we calculate the rover coordinates based on the intersection points, such as... Figure 6 As shown, the red dots represent the initial set of intersection points. The blue dots represent the final set of intersection points. The red "+" indicates the location of the mobile station (MS).

[0055] The specific steps are as follows:

[0056] (1) Based on the optimal error correction parameters All TOA measurements are calibrated to generate a new range circle, and all intersections within the minimum range circle are selected and denoted as the initial set of intersections. ;

[0057] (2) Calculate the initial set of intersection points centroid coordinates And calculate each intersection point within the set. Distance to the center of mass Elimination distance greater than The intersection of the means yields the set of intermediate intersection points. ;

[0058] (3) Calculate the set of intermediate intersection points Mean distance from the midpoint to the centroid with standard deviation Elimination distance greater than The intersection points are used to obtain the final set of intersection points. ;

[0059] (4) Final intersection set The coordinates of each point in the array are: Coordinates of the mobile station (MS) The calculation is as follows: , .

[0060] like Figure 7 As shown, this invention uses a positioning environment with 30 base stations (BAS) as an example, obtaining 1100 TOA measurement data points, and performs error analysis on the method. The coordinates of the mobile station (MS) were calculated using the above method, and the error vector was calculated based on the MS's true coordinates. The error distribution is as follows: Figure 7 As shown, a Delaunay triangulation network (hereinafter referred to as the BAS network) was constructed based on 30 BASs to better analyze the error distribution. The arrows indicate the direction of the error, and their lengths represent the magnitude of the error. It should be noted that due to the small size of the errors, all errors are magnified by a factor of two in the figure. It can be seen that the positioning accuracy of the mobile station (MS) is higher within the BAS network, while the positioning accuracy outside the BAS network is relatively poor. Outside the BAS network, the direction of the error is mostly far away from the BAS network.

[0061] like Figure 8 As shown, under the constraints of the BAS network, the localization based on multiple mobile stations (MSs) was plotted. Value distribution diagram. Within the BAS network, when MSs are located within the BAS network, The values ​​are mostly 0.706 and 0.707; however, when located outside the BAS network, The values ​​are mostly 0.703, 0.704, and 0.705. Within the network... The value is slightly higher than that outside the network. Value, within the network The value is more stable.

[0062] Therefore, in a fixed indoor positioning environment, the optimal error correction parameters for multiple test locations are determined in advance. Furthermore, an error correction parameter map covering the positioning area is generated through interpolation. When performing rapid positioning of the mobile station, the preset optimal correction parameters of the area are directly called from the error correction parameter map, and the TOA measurement value is corrected and calculated in one go using these parameters, which can improve positioning efficiency.

[0063] Meanwhile, in positioning applications in specific areas (such as warehouses, airports, etc.), in the same positioning environment, the TOA measurement values ​​are uniformly corrected and calculated by directly using the universal optimal error correction parameters pre-calibrated for that area to improve positioning efficiency.

[0064] In summary, the indoor TOA positioning method based on adaptive correction factors provided in this invention outperforms algorithms such as least squares (LS) and Nano in terms of average positioning error, maximum positioning error, and positioning error variance. In the experimental data, 97.36% of the positioning errors were less than 1 meter in absolute value. Even with a slight decrease in positioning accuracy when using a universal error correction factor, 85.82% of the positioning errors were still less than 1 meter in absolute value, meeting the needs of most indoor positioning applications.

[0065] Based on the same inventive concept, such as Figure 9 As shown, this embodiment of the invention also provides an indoor TOA positioning device 900 based on an adaptive correction factor, including: a range constraint module 910, an error correction module 920, a parameter optimization module 930, and a coordinate positioning module 940.

[0066] The range constraint module 910 is used to determine the distance between the mobile station and multiple base stations based on the TOA measurement value. Multiple range circles are established with each base station as the center and the distance as the radius, and the smallest range circle is determined.

[0067] Error correction module 920 is used to construct error correction equations, in which correction factors are introduced to dynamically correct the TOA measurement values.

[0068] The parameter optimization module 930 is used to count the number of intersections between any two range circles under different correction factors within the minimum range circle, and the correction factor value corresponding to the peak value of the number of intersections is used as the optimal error correction parameter.

[0069] The coordinate positioning module 940 is used to correct the TOA measurement value based on the error correction equation using the optimal error correction parameters, and to calculate the rover coordinates based on the corrected TOA measurement value to achieve indoor positioning.

[0070] Based on the same inventive concept, embodiments of the present invention also provide an electronic device, including a memory and one or more processors, wherein the memory is used to store a computer program, and the processor is used to implement the above-described indoor TOA positioning method based on adaptive correction factors when executing the computer program.

[0071] Based on the same inventive concept, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which, when executed by a computer, implements the above-described indoor TOA positioning method based on adaptive correction factors.

[0072] It should be noted that the indoor TOA positioning device, electronic device, and computer-readable storage medium based on adaptive correction factors provided in the above embodiments all belong to the same inventive concept as the indoor TOA positioning method based on adaptive correction factors. For details of their specific implementation process, please refer to the embodiments of the indoor TOA positioning method based on adaptive correction factors, which will not be repeated here.

[0073] The specific embodiments described above illustrate the technical solution and beneficial effects of the present invention in detail. It should be understood that the above description is only the most preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, additions, and equivalent substitutions made within the scope of the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An indoor TOA positioning method based on an adaptive correction factor, characterized in that, Includes the following steps: The distance between the mobile station and multiple base stations is determined based on the TOA measurement value. Multiple range circles are established with each base station as the center and the distance as the radius, and the smallest range circle is determined. An error correction equation is constructed, and the correction relationship is defined as multiplying the correction factor by the TOA measurement value to obtain the corrected TOA measurement value. Within the smallest range circle, count the number of intersections between any two range circles under different correction factors, and use the correction factor value corresponding to the peak value of the number of intersections as the optimal error correction parameter. The TOA measurement value is corrected using the optimal error correction parameters and the error correction equation. The rover coordinates are then calculated based on the corrected TOA measurement value to achieve indoor positioning. The methods for calculating the coordinates of the mobile station include: Based on the optimal error correction parameters All TOA measurements are calibrated to generate a new range circle, and all intersections within the minimum range circle are selected and denoted as the initial set of intersections. ; Calculate the initial set of intersection points Find the centroid coordinates and calculate the intersection points within the set. Distance to the center of mass Elimination distance greater than The intersection of the means yields the set of intermediate intersection points. ; Calculate the set of intermediate intersection points Mean distance from the midpoint to the centroid with standard deviation Elimination distance greater than The intersection points are used to obtain the final set of intersection points. ; Set of final intersection points The arithmetic mean of the coordinates of all intersection points is used as the final estimated coordinates of the mobile station.

2. The indoor TOA positioning method based on adaptive correction factor according to claim 1, characterized in that, The minimum radius circle must satisfy the following condition: the mobile station is located within a circle centered on the base station and with a radius equal to the distance determined by the TOA measurement value.

3. The indoor TOA positioning method based on adaptive correction factor according to claim 1, characterized in that, The value of the correction factor is determined within the range of 0.5 to 1.

4. The indoor TOA positioning method based on adaptive correction factor according to claim 1, characterized in that, In a fixed indoor positioning environment, the optimal error correction parameters for multiple test locations are pre-determined, and an error correction parameter map covering the positioning area is generated by interpolation. When performing rapid positioning of the mobile station, the preset optimal correction parameters of the area are directly called from the error correction parameter map, and the TOA measurement value is corrected and calculated in one go using these parameters.

5. The indoor TOA positioning method based on adaptive correction factor according to claim 1, characterized in that, In positioning applications in specific areas, the TOA measurement values ​​are uniformly corrected and calculated by using the universal optimal error correction parameters pre-calibrated for that area in the same positioning environment to improve positioning efficiency.

6. An indoor TOA positioning device based on an adaptive correction factor, implemented using the indoor TOA positioning method based on an adaptive correction factor as described in any one of claims 1 to 5, characterized in that, include: Range constraint module, error correction module, parameter optimization module, and coordinate positioning module; The range constraint module is used to determine the distance between the mobile station and multiple base stations based on the TOA measurement value. Multiple range circles are established with each base station as the center and the distance as the radius, and the smallest range circle is determined among them. The error correction module is used to construct an error correction equation, in which a correction factor is introduced to dynamically correct the TOA measurement value. The parameter optimization module is used to count the number of intersections between any two range circles under different correction factors within the minimum range circle, and the correction factor value corresponding to the peak value of the number of intersections is used as the optimal error correction parameter. The coordinate positioning module is used to correct the TOA measurement value based on the error correction equation using the optimal error correction parameters, and to calculate the rover coordinates based on the corrected TOA measurement value to achieve indoor positioning.

7. An electronic device comprising a memory and one or more processors, the memory being used to store a computer program, characterized in that, The processor is used to implement the indoor TOA positioning method based on adaptive correction factor as described in any one of claims 1 to 5 when executing a computer program.

8. A computer-readable storage medium storing a computer program thereon, characterized in that, When the computer program is executed by a computer, it implements the indoor TOA positioning method based on adaptive correction factor as described in any one of claims 1 to 5.

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