JP7420289B2 - Method and device for visualizing accuracy of position estimation by wireless communication - Google Patents

Description

The present disclosure relates to a method and apparatus for visualizing the accuracy of position estimation by wireless communication.

A concept called cyber-physical fusion is being discussed as a future social infrastructure. Cyber-physical fusion makes it possible to provide new high-value-added services by utilizing IoT (Internet-of-Things) technology and AI (Artificial Intelligent) to understand and analyze the state of real space.

When grasping and analyzing the state of real space, it is important to know where and under what circumstances the collected information was obtained, and the importance of location information is increasing. BACKGROUND OF THE INVENTION Positioning technology that acquires location information through wireless communication has been widely studied. Recently, as shown in Non-Patent Document 1, The Third Partnership Project (3GPP) Release
It has been discussed in standards such as IEEE 802.16 and IEEE 802.11az, and continues to receive attention from a technical perspective as it aims to further improve accuracy.

Various position estimation methods have been proposed so far. For example, there are methods that use received power, methods that use the angle of arrival of radio waves, methods that use arrival time and round trip time of radio waves, and methods that use machine learning to estimate from channel information linked to location information. However, each method has advantages and disadvantages, so they may be used in combination. For example, it is generally said that the time of arrival of radio waves has less variation and is more accurate than the received power. However, in order to measure the arrival time of radio waves, there are implementation issues, such as the need for receiving devices at all receiving points that receive position estimation signals to be synchronized with high accuracy.

Furthermore, in either method, the accuracy of position estimation varies depending on the environment in which positioning is performed. For example, in a non-line-of-sight environment, radio waves arrive while being repeatedly reflected, so the arrival time of radio waves tends to be longer. Therefore, in the case of a position estimation method that calculates distance using the arrival time or round trip time of radio waves, the distance between the transmission point and the reception point is estimated to be longer than the actual distance. Furthermore, even if it is not out of line of sight, in an environment where there are many structures that reflect radio waves in the surrounding area, such as in a building area, estimation errors often occur because the power of the reflected waves is greater than that of the direct waves. As the importance of location information increases, understanding the accuracy of location estimation is also becoming an important factor.

R. Keating, M. Saily, J. Hulkkonen, and J. Karjalainen, “Overview of Positioning in 5G New Radio”, 2019 16th International Symposium on Wireless Communication Systems, Aug. 2019.

From the standpoint of a provider of data analysis using location information or a service using location information, the accuracy of location estimation is a very important element that is directly linked to the reliability of the service. Therefore, when starting a service, there is a need to understand the accuracy of position estimation in the service area.

Furthermore, as described above, the accuracy of position estimation varies depending on the position estimation method. In addition, if the accuracy of position estimation in a service area can be ascertained in advance, it will be possible to use this information to determine which position estimation method should be adopted during service development. Note that the position estimation accuracy can be known as the specification value of the developed position estimation system. However, these are just guidelines, and you won't know how much accuracy you can actually achieve until you use it. Furthermore, because estimation accuracy varies depending on the usage environment, information on specification values alone is insufficient.

The present disclosure has been made in view of the above circumstances, and aims to provide a technology that can visualize the accuracy of position estimation while taking into account wireless communication environmental conditions specific to a service area.

In order to achieve the above object, the present disclosure provides a method for visualizing the accuracy of position estimation by wireless communication. The first step of the method is to calculate respective numerical values for a plurality of mutually independent factors that influence the accuracy of position estimation based on the environmental conditions of wireless communication. The second step of the method is to convert the numerical value of each of the plurality of factors into a dimensionless quantity using the reference value of each of the plurality of factors. The third step of this method is to calculate the accuracy of position estimation using a first-order polynomial in which the dimensionless quantities of each of the plurality of factors are used as explanatory variables and the accuracy of position estimation is used as an objective variable. The fourth step of the method is to display the calculation result of the accuracy of the position estimation.

Furthermore, in order to achieve the above object, the present disclosure provides a device that visualizes the accuracy of position estimation by wireless communication. The apparatus includes one or more memories storing one or more programs and one or more processors coupled to the one or more memories. One or more processors execute at least the first to fourth processes when executing one or more programs. The first process is a process of calculating respective numerical values for a plurality of mutually independent factors that influence the accuracy of position estimation based on the environmental conditions of wireless communication. The second process is a process of converting each numerical value of a plurality of factors into a dimensionless quantity using a reference value of each of the plurality of factors. The third process is a process of calculating the accuracy of position estimation using a first-order polynomial in which the dimensionless quantities of each of a plurality of factors are used as explanatory variables and the accuracy of position estimation is used as an objective variable. The fourth process is a process of displaying the calculation result of the position estimation accuracy.

According to the method and device according to the present disclosure, the accuracy of position estimation is calculated using a first-order polynomial whose explanatory variables are dimensionless quantities of each of a plurality of factors that affect the accuracy of position estimation, and the accuracy of position estimation is the objective variable. By calculating and displaying, the accuracy of position estimation can be visualized.

FIG. 2 is a diagram for explaining an example of a position estimation method using wireless communication. FIG. 1 is a block diagram for explaining a position estimation accuracy visualization device according to a first embodiment of the present disclosure. FIG. 3 is a diagram for explaining an example of information input to an input unit. FIG. 6 is a diagram illustrating an example of calculation of a radio wave path by a propagation calculation unit. FIG. 6 is a diagram illustrating an example of calculation of received power and arrival time of each path by a propagation calculation unit. It is a block diagram for explaining the function of an accuracy estimating part. 12 is a flowchart for explaining a procedure for calculating a parameter F5 by an accuracy estimator. FIG. 6 is a diagram for specifically explaining the process performed in calculating the parameter F5. It is a figure showing the example of a display by a display part. FIG. 2 is a block diagram for explaining a position estimation accuracy visualization device according to a second embodiment of the present disclosure. FIG. 2 is a block diagram illustrating an example of a hardware configuration of a position estimation accuracy visualization device according to each embodiment of the present disclosure.

1. Outline of position estimation method using wireless communication FIG. 1 is a diagram for explaining an example of a position estimation method using wireless communication. The target of position estimation by wireless communication is, for example, a mobile station 2 including a mobile terminal such as a smartphone or a mobile object such as a car. Wireless communication is performed between the mobile station 2 and one or more base stations 4 whose locations are fixed. To estimate the position of the mobile station 2, a plurality of base stations 4 that can simultaneously communicate with the mobile station 2 are used.

In position estimation, the mobile station 2 becomes a transmission point that transmits a signal for position estimation. Hereinafter, the mobile station 2 will be referred to as a transmission point 2. As a signal for position estimation, for example, an SRS (Sounding Reference Signal) is used. The mobile station 2 emits radio waves containing signals for position estimation in all directions. A plurality of base stations 4 existing around the mobile station 2 serve as reception points that receive radio waves including signals for position estimation. Hereinafter, the base station 4 will be referred to as a receiving point 4. Note that the transmission point 2 and the reception point 4 constitute a MIMO system. However, there is no limit to the number and type of antennas at each of the transmitting point 2 and the receiving point 4.

Estimating the position of the mobile station 2 can be performed in various ways. One example is a method that uses the arrival time of radio waves from a transmission point to a reception point. In this method, the arrival times of radio waves are compared between a plurality of (for example, three) reception points 4 that received radio waves transmitted from the transmission point 2 at the same time. Specifically, information regarding the arrival time of radio waves is sent from each reception point 4 to the position estimation system 6. The position estimation system 6 is, for example, a server located on a communication network. The position estimation system 6 estimates the current position of the transmission point 2 on the map based on the arrival time of radio waves at each reception point 4 and map information.

All position estimation methods that have been proposed so far, including the position estimation method exemplified here, include estimation errors. For example, although the position estimation method exemplified here is a position estimation method using time of arrival, estimation errors are also included in position estimation methods using received power, position estimation methods based on machine learning, and the like. The method and device for visualizing the accuracy of position estimation according to each embodiment of the present disclosure makes it possible to easily determine whether or not a position estimation method to be evaluated is applicable to an application by visualizing the accuracy of position estimation. This is what I did. There are no limitations on the position estimation method to be evaluated.

2. Position estimation accuracy visualization device according to the first embodiment FIG. 2 is a block diagram for explaining the position estimation accuracy visualization device 10 according to the first embodiment. The position estimation accuracy visualization device 10 is a device that visualizes the accuracy of position estimation by converting it into numerical values and displaying it, and this device 10 executes a method of visualizing the accuracy of position estimation. The position estimation accuracy visualization device 10 includes an input section 11, a propagation calculation section 12, an accuracy estimation section 13, and a display section 14 according to their functions. Hereinafter, the functions of each part constituting the position estimation accuracy visualization device 10 will be explained with reference to the drawings.

The input unit 11 receives input of information regarding environmental conditions of wireless communication. FIG. 3 is a diagram for explaining an example of information input to the input unit 11. The environmental conditions for wireless communication include information on the area in which position estimation accuracy is evaluated. As shown in FIG. 3, the area information includes maps, structures, and their layouts. Furthermore, the environmental conditions for wireless communication include the layout of the transmitting point 2 and the receiving point 4, as shown in FIG. Furthermore, the wireless parameters of the wireless communication system used for position estimation, the position estimation method, and related parameters are also included in the wireless communication environmental conditions.

The propagation calculation unit 12 uses the information input to the input unit 11 to calculate the propagation path of radio waves from the transmission point to the reception point. For example, a ray tracing method can be used as a method for calculating the propagation path. By using the ray tracing method, propagation paths corresponding to maps and structures can be calculated. In the following description, it is assumed that the ray tracing method is used as the propagation path calculation method. However, the ray tracing method is just one example of a method for calculating the propagation path, and the propagation path may be calculated using other methods.

FIG. 4 is a diagram showing an example of calculation of a radio wave path by the propagation calculation unit 12. Specifically, when structures, transmitting points 2, and receiving points 4 are arranged on a map as shown in Figure 3, the radio wave path from transmitting point 2 to receiving point 4 is determined by the ray tracing method. A calculated example is shown. In the ray tracing method, radio waves emitted from the transmitting point 2 are regarded as light rays, and the trajectory of the light rays reaching the receiving point 4 after being reflected, diffracted, and transmitted by surrounding structures is determined. The method for determining the trajectory of the light ray may be, for example, an imaging method or a launching method. The trajectory of the light beam is the path of the radio wave from the transmission point 2 to the reception point 4, and in the example shown in FIG. 4, five paths from P1 to P5 are calculated. Among these, the path P1 is a direct wave path that directly reaches the receiving point 4 from the transmitting point 2.

The propagation calculation unit 12 calculates, for each evaluation point, for example, the communication distance, the number of paths, the received power of each path, the arrival time (or delay) of each path, the number of reception points that can receive direct waves, and the channel response. In the example shown in FIG. 4, the communication distance is the distance from the transmission point 2 to the reception point 4, and the number of paths is five from P1 to P5. The received power of each path is calculated by a known method based on the amplitude and phase of the radio wave at the receiving point 4. The arrival time of each path is calculated in a known manner based on the path length of the path. FIG. 5 is a diagram showing an example of calculation of the received power and arrival time of each path by the propagation calculation unit 12. Further, the channel response is calculated by a known method based on the configuration of each antenna at the receiving point 4 and the transmitting point 2, and the amplitude and phase of the radio waves of each path at the receiving point 4.

The accuracy estimation unit 13 uses the information output from the propagation calculation unit 12 to calculate the position estimation accuracy at each evaluation point. The position estimation accuracy is calculated using, for example, a first-order polynomial shown in equation (1) below. In this first-order polynomial, the position estimation accuracy is the objective variable, and F1, F2, F3, F4, and F5 are explanatory variables. a, b, c, d, and e are weighting factors.
(Position estimation accuracy) = a*F1+b*F2+c*F3+d*F4+e*F5...Formula (1)

F1, F2, F3, F4, and F5 in the above first-order polynomial are parameters related to five mutually independent factors that affect position estimation accuracy. F1 is a parameter calculated based on the communication distance. F2 is a parameter calculated based on the number of passes. F3 is a parameter calculated based on the received power and arrival time (or delay) of each path. F4 is a parameter calculated based on the number of reception points that can receive direct waves. And F5 is a parameter calculated based on the channel response.

FIG. 6 is a block diagram for explaining the functions of the accuracy estimation section 13. In order to calculate each of the above parameters F1 to F5, the accuracy estimation unit 13 includes an F1 calculation unit 131,
It includes an F2 calculation section 132, an F3 calculation section 133, an F4 calculation section 134, and an F5 calculation section 135.

The F1 calculation unit 131 calculates the parameter F1 in consideration of the characteristic that the longer the communication distance is, the more likely the position estimation accuracy is to deteriorate. A reference value of communication distance is set in advance in the F1 calculation unit 131. The communication distance reference value is a value that is expected to provide the required position estimation accuracy, and can be set arbitrarily by the user. For example, if it is assumed that a position estimation error of 10 m is acceptable, and the communication distance that satisfies the position estimation error of 10 m is 50 m, the reference value of the communication distance that is the output of the propagation calculation unit 12 is 50 m. The F1 calculation unit 131 calculates, for example, the ratio of the communication distance reference value to the communication distance calculation value output from the propagation calculation unit 12 (reference value/calculation value) as the parameter F1. The parameter F1 is a dimensionless quantity obtained by making the communication distance, which is a factor that influences position estimation accuracy, dimensionless using its reference value.

The F2 calculation unit 132 calculates the parameter F2 in consideration of the characteristic that the position estimation accuracy is more likely to deteriorate as the number of passes increases. A reference value for the number of passes is set in advance in the F2 calculation unit 132. The reference value for the number of passes is a value that is expected to provide the required position estimation accuracy, and can be set arbitrarily by the user. The F2 calculating unit 132 calculates, for example, the ratio of the reference value of the number of paths to the calculated value of the number of paths output from the propagation calculating unit 12 (reference value/calculated value) as the parameter F2. The parameter F2 is a dimensionless quantity obtained by making the number of passes, which is a factor that affects position estimation accuracy, dimensionless using its reference value.

The F3 calculation unit 133 calculates the parameter F3 in consideration of the characteristic that when the received power of a plurality of paths is about the same, the longer the arrival time (delay) of a path is, the more likely the position estimation accuracy is to deteriorate. Specifically, the F3 calculation unit 133 extracts paths with the same received power from among the paths. Then, the maximum value of the arrival time difference (maximum arrival time difference) among the paths having the same received power is calculated. In the example shown in FIG. 5, paths P1, P2, and P3 have the same received power, and the difference between the arrival time of path P1 and the arrival time of path P3 is the maximum arrival time difference. A reference value for the maximum arrival time difference is set in advance in the F3 calculation unit 133. The reference value of the maximum arrival time difference is a value that is expected to provide the required position estimation accuracy, and can be set arbitrarily by the user. The F3 calculating unit 133 calculates, for example, the ratio (reference value/calculated value) of the reference value of the maximum arrival time difference to the calculated value of the maximum arrival time difference calculated as described above (reference value/calculated value) as the parameter F3. The parameter F3 is a dimensionless quantity obtained by making the maximum arrival time difference, which is a factor that affects position estimation accuracy, dimensionless using its reference value.

The F4 calculation unit 134 calculates the parameter F4 in consideration of the characteristic that the position estimation accuracy is more likely to deteriorate as the number of reception points that can receive direct waves is smaller. A reference value for the number of reception points is set in advance in the F4 calculation unit 134. The reference value of the number of reception points is a value that is expected to provide the required position estimation accuracy, and can be set arbitrarily by the user. The F4 calculation unit 134 calculates, for example, the ratio of the reference value of the number of reception points to the calculated value of the number of reception points output from the propagation calculation unit 12 (reference value/calculation value) as the parameter F4. The parameter F4 is a dimensionless quantity obtained by making the number of reception points, which is a factor that influences position estimation accuracy, dimensionless using its reference value.

Next, the calculation of the parameter F5 based on the channel response by the F5 calculation unit 135 will be explained. The value of the channel response affects the position estimation accuracy, for example, when position estimation is performed from channel information linked to position information using machine learning. If there are multiple points with highly correlated channel responses, errors are likely to occur in position estimation. Therefore, the F5 calculation unit 135 calculates the parameter F5 according to the procedure shown in the flowchart in FIG.

In step S1, the F5 calculation unit 135 selects a total of two points: a place where the accuracy of position estimation is desired and one comparison point. In step S2, the F5 calculation unit 135 calculates a channel correlation value using the channel response obtained at each point. The F5 calculation unit 135 repeats the processing of step S1 and step S2. That is, a different comparison location is selected in step S1, and a channel correlation value is calculated for the selected comparison location in step S2. When the calculation of channel correlation values for all comparison locations is completed, the F5 calculation unit 135 next performs the process of step S3.

In step S3, the F5 calculation unit 135 extracts locations where the channel correlation value is greater than or equal to a preset threshold value from among all comparison locations. Subsequently, in step S4, the F5 calculation unit 135 calculates the distance from the location for which the accuracy of position estimation is desired for all the locations extracted in step S3. Then, the maximum distance is determined from among the calculated distances.

Here, FIG. 8 is a diagram for specifically explaining the processing performed in steps S3 and S4. FIG. 8 shows a location TL on the map for which the accuracy of position estimation is desired and the locations of all comparison locations L1 to L14. In the example shown in FIG. 8, among the comparison locations L1 to L14, there are a total of five locations where the channel correlation value is greater than or equal to the threshold value: L2, L5, L8, and L11. Of the distances D2, D5, D8, and D11 from the location TL for which the accuracy of position estimation is desired to each location L2, L5, L8, and L11, the maximum distance is the distance D5 to the location L5. In this example, the distance D5 is determined as the maximum distance in step S4.

In step S5, the F5 calculation unit 135 sets the maximum allowable distance as a reference value. The reference value may be set every time, or a preset reference value may be used. In step F6, the F5 calculation unit 135 calculates, for example, the ratio of the reference value of the maximum distance to the calculated value of the maximum distance calculated as described above (reference value/calculated value) as a parameter F5. The parameter F5 is a dimensionless quantity obtained by making the maximum distance to a highly similar place, which is a factor that affects position estimation accuracy, dimensionless using its reference value.

Returning to FIG. 6 again, the description of the function of the accuracy estimation unit 13 will be continued. The accuracy estimation unit 13 includes a position estimation accuracy calculation unit 130. The parameters F1, F2, F3, F4, and F5 calculated by the F1 calculation unit 131, F2 calculation unit 132, F3 calculation unit 133, F4 calculation unit 134, and F5 calculation unit 135 are input to the position estimation accuracy calculation unit 130. be done. The position estimation accuracy calculation unit 130 calculates the position estimation accuracy using the first-order polynomial expressed by the above equation (1).

Note that the weighting coefficients a, b, c, d, and e constituting the first-order polynomial can be arbitrarily set by the user. Since the relationship expressed by the first-order polynomial differs depending on the position estimation method employed, different values may be set for the weighting coefficients a, b, c, d, and e depending on the position estimation method. Further, if the factors of the specific error that are dominant in the assumed radio environment are different, the weighting coefficients a, b, c, d, and e may be set so as to reflect many of the factors. Weighting coefficients corresponding to factors not considered by the position estimation method are set to 0. For example, if no channel response is used, e=0.

As described above, the position estimation accuracy visualization device 10 uses the propagation calculation unit 12 and the accuracy estimation unit 13 to calculate respective numerical values for a plurality of mutually independent factors that affect position estimation accuracy based on the environmental conditions of wireless communication. Perform the processing to do. Next, in the position estimation accuracy visualization device 10, the accuracy estimation unit 13 performs a process of converting each numerical value of the plurality of factors into a dimensionless quantity using the reference value of each of the plurality of factors. Then, the position estimation accuracy visualization device 10 causes the accuracy estimation unit 13 to perform a process of calculating the position estimation accuracy using a first-order polynomial in which the dimensionless quantities of the plurality of factors are explanatory variables and the position estimation accuracy is the objective variable. conduct.

Returning to FIG. 2 again, the description of the functions of the position estimation accuracy visualization device 10 will be continued. The position estimation accuracy calculated by the accuracy estimation section 13 is output to the display section 14. The display unit 14 displays the calculation result of the position estimation accuracy output from the accuracy estimation unit 13 as a graph or a map. For example, a map is displayed with reference to map information input through the input unit 11, and the position estimation accuracy of a corresponding position on the map is displayed. As a display method, accuracy may be displayed as a numerical value or may be displayed in color.

FIG. 9 is a diagram showing an example of display on the display unit 14. As shown in FIG. 9, on a map where structures are placed, areas with high position estimation accuracy and areas with low position estimation accuracy may be displayed in different colors. For example, the area may be displayed in different colors, such as red if the position estimation accuracy is high and blue if it is low. Moreover, instead of color-coding into two colors depending on whether the position estimation accuracy is high or low, it is also possible to color-code each area in multiple stages according to the value of the position estimation accuracy.

3. Position estimation accuracy visualization device of second embodiment In setting the weighting coefficients a, b, c, d, and e of the first-order polynomial expressed by the above equation (1), the actual values of position estimation measured in advance are used. Good too. In order to utilize actual measured values of position estimation for setting weighting coefficients, the position estimation accuracy visualization device 10 of the second embodiment is configured as shown in FIG. 10. The position estimation accuracy visualization device 10 of the second embodiment includes an input section 11, a propagation calculation section 12, an accuracy estimation section 13, a display section 14, an error calculation section 15, and a weight estimation section 16 according to their functions. Since the input unit 11, propagation calculation unit 12, accuracy estimation unit 13, and display unit 14 are the same as those in the first embodiment, the error calculation unit 15 and weight estimation unit 16 will be explained below.

The error calculation unit 15 receives input of position estimation information (actual measurement value) obtained through actual measurement and correct position information (correct value) corresponding thereto. The error calculation unit 15 calculates an error from the input actual measurement value and correct value. For example, the distance between the measured value and the correct value is calculated as the error. The error calculation unit 15 outputs the error calculation result to the weight estimation unit 16.

The weight estimation unit 16 uses the calculation results of errors at various locations output from the error calculation unit 15 to calculate the linear estimation accuracy expressed by the above equation (1) so as to approach the position estimation accuracy obtained by actual measurement. Adjust the weighting coefficients a, b, c, d, and e of the polynomial. In this case, the position estimation accuracy on the left side of the above equation (1) may be calculated using the following equation (2). Note that the allowable error on the right side of equation (2) is a value that is expected to provide the required position estimation accuracy, and can be set arbitrarily by the user.
(Position estimation accuracy) = (Tolerance error) / (Error output from the error calculation unit) ...Formula (2)

By calculating the weighting coefficients a, b, c, d, and e in this way, it is possible to obtain the weighting coefficients a, b, c, d, and e corresponding to the position estimation method used and the location where the position estimation is performed. can. The obtained weighting coefficients a, b, c, d, and e are output to the accuracy estimating section 13 and applied to the first-order polynomial expressed by equation (1).

In the second embodiment, actual position estimation values are measured in advance at a location where position estimation is performed, and the measurement results are reflected in the settings of weighting coefficients a, b, c, d, and e. As a result, according to the second embodiment, the actual measured value of position estimation is used to calculate the weighting coefficient, and the result calculated in the propagation calculation unit is used for the position estimation accuracy. Accuracy can be confirmed including locations where measurements have not been made.

4. Hardware Configuration of Position Estimation Accuracy Visualization Device The hardware configuration of the position estimation accuracy visualization device 10 of each embodiment of the present disclosure will be described with reference to FIG. 11. FIG. 11 is a block diagram showing an example of the hardware configuration of the position estimation accuracy visualization device 10.

Each function of the position estimation accuracy visualization device 10 shown in FIGS. 2 and 10 is realized by, for example, the computer 100, the input device 105, and the display device 106. Computer 100 includes one or more processors 101 (hereinafter simply referred to as processors 101) and one or more memories 102 (hereinafter simply referred to as memory 102) coupled to processors 101. Memory 102 includes a main storage device and an auxiliary storage device. The memory 102 stores one or more programs 103 (hereinafter simply referred to as programs 103) executable by the processor 101 and various information related thereto.

When the processor 101 executes the program 103, various processing by the processor 101 is realized. The functions of the input section 11, propagation calculation section 12, precision estimation section 13, and display section 14 shown in FIG. 2 are realized by the program 103 being executed by the processor 101. The functions of the input section 11, propagation calculation section 12, accuracy estimation section 13, display section 14, error calculation section 15, and weight estimation section 16 shown in FIG. 10 are also realized by the program 103 being executed by the processor 101. . The program 103 can be stored in the main storage device or in a computer-readable recording medium that is an auxiliary storage device.

The input device 105 includes input devices such as a keyboard and a mouse. The functions of the input device 105 include a function of inputting data into the computer 100 via a USB memory, etc.
It also includes a function to input data into the computer 100 via the AN or a function to download data from the Internet. The display device 106 is a display having a display screen that can be viewed by the user.

5. Others The embodiments described above can be modified and implemented in various ways without departing from the gist of the present disclosure. In other words, in the above embodiments, when the number, amount, amount, range, etc. of each element is mentioned, unless it is specifically specified or it is clearly specified by the number in principle, the mentioned The technology according to the present disclosure is not limited to the number. Furthermore, the structures and the like described in the above embodiments are not necessarily essential to the technology according to the present disclosure, unless specifically specified or clearly specified in principle.

2 Transmission point (mobile station)
4 Receiving point (base station)
6 Position estimation system 10 Position estimation accuracy visualization device 11 Input section 12 Propagation calculation section 13 Accuracy estimation section 14 Display section 15 Error calculation section 16 Weight estimation section 100 Computer 101 Processor 102 Memory 103 Program 105 Input device 106 Display devices P1, P2, P3, P4, P5 pass

Claims (8)

A method for visualizing the accuracy of position estimation by wireless communication, the method comprising:
calculating respective numerical values for a plurality of mutually independent factors that influence the accuracy based on the environmental conditions of the wireless communication;
converting each numerical value of the plurality of factors into a dimensionless quantity using the reference value of each of the plurality of factors;
calculating the accuracy using a first-order polynomial with dimensionless quantities of each of the plurality of factors as explanatory variables and the accuracy as an objective variable;
Displaying the calculation result of the accuracy;
A method characterized by comprising: The method according to claim 1,
The step of calculating the accuracy includes calculating the accuracy for each area in which the position estimation is performed,
The method characterized in that the step of displaying the calculation result includes the step of displaying the calculation result at a position corresponding to the area on a map. The method according to claim 1 or 2,
The method further comprises the step of adjusting a weighting coefficient of the first-order polynomial based on an error between the actual measured value of the position estimation and the correct value. The method according to any one of claims 1 to 3,
The plurality of factors include factors that depend on the propagation path of the radio wave,
A method characterized in that the step of calculating the numerical value includes the step of calculating the propagation path based on the environmental conditions of the wireless communication. A device that visualizes the accuracy of position estimation by wireless communication,
one or more memories storing one or more programs;
one or more processors coupled with the one or more memories,
When the one or more processors execute the one or more programs,
a process of calculating respective numerical values for a plurality of mutually independent factors that influence the accuracy based on the environmental conditions of the wireless communication;
a process of converting each numerical value of the plurality of factors into a dimensionless quantity using a reference value of each of the plurality of factors;
a process of calculating the accuracy using a first-order polynomial with dimensionless quantities of each of the plurality of factors as explanatory variables and the accuracy as an objective variable;
An apparatus characterized in that the apparatus comprises the steps of: displaying the calculation result of the accuracy; The apparatus according to claim 5,
The process of calculating the accuracy includes a process of calculating the accuracy for each area in which the position estimation is performed,
An apparatus characterized by comprising: the process of displaying the calculation result; and the process of displaying the calculation result at a position corresponding to the area on a map. The device according to claim 5 or 6,
When the one or more processors execute the one or more programs,
An apparatus characterized in that the apparatus further executes a process of adjusting a weighting coefficient of the first-order polynomial based on an error between an actual measured value of the position estimation and a correct value. The device according to any one of claims 5 to 7,
The plurality of factors include factors that depend on the propagation path of the radio wave,
An apparatus characterized in that the process of calculating the numerical value includes a process of calculating the propagation path based on the environmental conditions of the wireless communication.

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