Location estimation system, information processing device, location estimation method

Abstract

This improves the accuracy of estimating the position of a target object based on the radio wave strength of the received signal. [Solution] An information processing device 500 estimates the position of a target communication terminal 10 based on the received radio wave strength from the target communication terminal 10 received by at least three or more communication terminals 100 capable of communicating with the target communication terminal 10. The device ranks the top three communication terminals in order of the strength of the received radio wave strength from the target communication terminal 10, calculates the centroid coordinates based on the position coordinates of the top three ranked communication terminals, calculates the distance between the centroid coordinates and the multiple communication terminals, updates the ranking of the top three communication terminals in order of proximity, and calculates weighted centroid coordinates based on the received radio wave strength using the following formula. TIFF2026125377000042.tif24170 The position of the target communication terminal 10 is estimated based on weighted centroid coordinates.

Description

[Technical Field]

[0001] The present invention relates to a position estimation system, an information processing device, and a position estimation method. [Background technology]

[0002] As a technique for estimating the position and movement path of a target object, for example, a proximity estimation method is known that detects the communication terminal (anchor node) that has the maximum radio wave strength, i.e., the received signal strength indicator (RSSI), received from the target communication terminal (target communication terminal). Another technique for estimating the position and movement path of a target object is known, for example, a method that estimates the distance between the anchor node and the target communication terminal based on the RSSI at each anchor node, and then estimates the position using the principle of tripoint positioning.

[0003] Furthermore, as a technique for estimating the position of a target communication terminal based on the radio wave strength received from the target communication terminal, a positioning device is known that receives a beacon from a radio station, determines the distance to the radio station based on the received radio wave strength, and performs positioning based on the distance to the radio station and the position of the radio station (see Patent Document 1). [Prior art documents] [Patent Documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2013-124885 [Overview of the project] [Problems that the invention aims to solve]

[0005] However, in environments with significant multipath effects, such as indoors, the RSSI fluctuates considerably. Consequently, in such environments, when estimating the position and movement path of an object, the accuracy of proximity estimation and distance estimation deteriorates, resulting in a problem of degraded position estimation accuracy.

[0006] The present invention takes the above problems as an example, and aims to provide a technology for improving the accuracy when estimating the position of a target object based on the radio wave intensity of a received signal from a communication terminal.

Means for Solving the Problems

[0007] In order to achieve the above object, a position estimation system according to the present invention includes a target communication terminal, at least three or more plurality of communication terminals capable of communicating with the target communication terminal, and an information processing device that estimates the position of the target communication terminal according to the received radio wave intensity from the target communication terminal received by three of the plurality of communication terminals. The information processing device ranks the top three communication terminals in descending order of the received radio wave intensity from the target communication terminal, calculates the centroid coordinates based on the position coordinates of the top three communication terminals after ranking, calculates the distances between the centroid coordinates and the plurality of communication terminals, updates the ranking of the top three communication terminals in ascending order of the distances, and calculates weighted centroid coordinates according to the following formula based on the received radio wave intensity, TIFF2026125377000002.tif24170 Estimate the position of the target communication terminal based on the weighted centroid coordinates.

Effects of the Invention

[0008] According to the position estimation system according to the present invention, the accuracy when estimating the position of a target object based on the radio wave intensity of a received signal from a communication terminal can be improved.

Brief Description of the Drawings

[0009] [Figure 1] It is a functional block diagram schematically showing the configuration of a position estimation system according to an embodiment of the present invention. [Figure 2] It is a functional block diagram schematically showing the position estimation process by a server in the position estimation system according to the present embodiment. [Figure 3]This is a schematic diagram illustrating an example of distance estimation using three anchor nodes and a target communication terminal in the target communication terminal position estimation process. [Figure 4] This is a schematic diagram illustrating an example of a facility that is subject to the location estimation process and movement path estimation process in the location estimation system according to this embodiment. [Figure 5] This is a schematic diagram showing an example of the transmission timing of beacon signals in the position estimation system according to this embodiment. [Figure 6] This is a schematic diagram showing an example of the relationship between the calculated centroid coordinates, the position coordinates of the top three ranked anchor nodes, and the transmission position of the beacon signal in the position estimation system according to this embodiment. [Figure 7] This is a schematic diagram showing an example of the relationship between the centroid coordinates, the positions of the top 3 ranked anchor nodes after updating, and the beacon signal transmission position in the position estimation system according to this embodiment. [Figure 8] This graph illustrates the difference in weighting due to differences in the integer exponent n used in the process of calculating weighted centroid coordinates based on RSSI in the position estimation system according to this embodiment. [Figure 9] This is a schematic diagram illustrating the process of estimating the position of a target communication terminal based on the measured distance between three anchor nodes and the target communication terminal in the position estimation system according to this embodiment. [Figure 10] This graph illustrates the position estimation processing results based on weighted centroid coordinates in the position estimation system according to this embodiment, when the number of RSSI samples is NS=1. [Figure 11] This graph illustrates the position estimation processing results based on weighted centroid coordinates in the position estimation system according to this embodiment, when the number of RSSI samples is NS=4. [Figure 12] This graph illustrates the position estimation processing results based on weighted centroid coordinates in the position estimation system according to this embodiment, when the number of RSSI samples is NS=8. [Figure 13]This is a schematic diagram showing an example of the transmission location of a beacon signal at a facility that is subject to location estimation processing and movement path estimation processing in the location estimation system according to this embodiment. [Figure 14] This is a schematic diagram showing the movement path estimation result based on weighted centroid coordinates when the number of RSSI samples is NS=1 in the position estimation system according to this embodiment. [Figure 15] This is a schematic diagram showing the movement path estimation result based on weighted centroid coordinates when the number of RSSI samples is NS=4 in the position estimation system according to this embodiment. [Figure 16] This is a schematic diagram showing the movement path estimation result based on weighted centroid coordinates when the number of RSSI samples is NS=8 in the position estimation system according to this embodiment. [Figure 17] This graph shows the results of the position estimation process using the repeated least squares method when the number of RSSI samples is NS=1 in the position estimation system according to this embodiment. [Figure 18] This graph shows the results of the position estimation process using the repeated least squares method when the number of RSSI samples is NS=4 in the position estimation system according to this embodiment. [Figure 19] This graph shows the results of the position estimation process using the repeated least squares method when the number of RSSI samples is NS=8 in the position estimation system according to this embodiment. [Figure 20] This is a schematic diagram showing the travel path estimation result based on the repeated least squares method when the number of RSSI samples is NS=1 in the position estimation system according to this embodiment. [Figure 21] This is a schematic diagram showing the movement path estimation result based on the repeated least squares method when the number of RSSI samples is NS=4 in the position estimation system according to this embodiment. [Figure 22] This is a schematic diagram showing the travel path estimation result based on the repeated least squares method when the number of RSSI samples is NS=8 in the position estimation system according to this embodiment. [Figure 23]This is a flowchart illustrating the position estimation process of a target communication terminal in the position estimation system according to this embodiment. [Modes for carrying out the invention]

[0010] 1. Overview of the Embodiment First, a general overview of a typical embodiment of the invention disclosed in this application will be provided. In the following description, reference numerals in the drawings corresponding to the components of the invention are indicated in parentheses as an example.

[0011] [1] A position estimation system (1) comprising a target communication terminal (10), at least three or more communication terminals (100) capable of communicating with the target communication terminal, and an information processing device (500) that estimates the position of the target communication terminal according to the received radio wave intensity from the target communication terminal received by three of the communication terminals, wherein the information processing device ranks the top three communication terminals in order of the strength of the received radio wave intensity from the target communication terminal, calculates the centroid coordinates based on the position coordinates of the top three ranked communication terminals, calculates the distance between the centroid coordinates and the multiple communication terminals, updates the ranking of the top three communication terminals in order of proximity of the distance, and calculates weighted centroid coordinates based on the received radio wave intensity using the following formula, TIFF2026125377000003.tif24170 A position estimation system that estimates the position of the target communication terminal based on the weighted centroid coordinates.

[0012] [2] The position estimation system according to [1], wherein the information processing device estimates the position of the target communication terminal by iterative least squares using the weighted centroid coordinates as initial values, and selects either the position estimation result of the target communication terminal based on the weighted centroid coordinates or the position estimation result of the target communication terminal by iterative least squares as the position estimation result of the target communication terminal based on the weighted centroid coordinates or the position estimation result of the target communication terminal by iterative least squares as the position estimation result of the target communication terminal.

[0013] [3] The position estimation system according to [2], wherein the information processing device determines whether the accuracy of the position estimation result of the target communication terminal's position estimation result by the iterative least squares method has deteriorated based on the magnitude of the update amount vector, and if it determines that the accuracy of the position estimation has not deteriorated, it selects the position estimation result of the target communication terminal's position by the iterative least squares method as the position estimation result of the target communication terminal, and if it determines that the accuracy of the position estimation has deteriorated, it selects the position estimation result of the target communication terminal's position based on the weighted centroid coordinates as the position estimation result of the target communication terminal.

[0014] [4] The position estimation system according to any one of [1] to [3], wherein the information processing device performs a process to estimate the movement path of the target communication terminal based on the estimated position coordinates of the target communication terminal.

[0015] [5] An information processing device (500) that estimates the position of a target communication terminal (10) according to the received radio wave strength from the target communication terminal received by at least three or more communication terminals (100) capable of communicating with the target communication terminal, ranks the top three communication terminals in order of the strength of the received radio wave strength from the target communication terminal, calculates the centroid coordinates based on the position coordinates of the top three ranked communication terminals, calculates the distance between the centroid coordinates and the multiple communication terminals, updates the ranking of the top three communication terminals in order of proximity of the distance, and calculates weighted centroid coordinates based on the received radio wave strength using the following formula: Information processing device for estimating the position of the target communication terminal based on the weighted centroid coordinates.

[0016] [6] A method for estimating the position of a target communication terminal (10) based on the received radio wave intensity from the target communication terminal received by at least three or more communication terminals (100) capable of communicating with the target communication terminal, wherein the information processing device (500) performs the following steps: ranks the top three communication terminals in order of the strength of the received radio wave intensity from the target communication terminal; calculates the centroid coordinates based on the position coordinates of the top three ranked communication terminals and calculates the distance between the centroid coordinates and the multiple communication terminals; updates the ranking of the top three communication terminals in order of proximity of the distance; calculates weighted centroid coordinates based on the received radio wave intensity using the following formula, and TIFF2026125377000005.tif24170 A position estimation method that performs a process to estimate the position of the target communication terminal based on the weighted centroid coordinates.

[0017] 2. Specific Examples of Embodiments The following describes a position estimation system, information processing device, and position estimation method according to embodiments of the present invention with reference to the drawings.

[0018] Figure 1 is a functional block diagram schematically showing the configuration of a position estimation system according to an embodiment of the present invention. As shown in Figure 1, the position estimation system 1 consists of a target communication terminal 10, an anchor node 100 acting as a communication terminal, and a server 500. In the position estimation system 1, the target communication terminal 10 is a terminal that moves together with the target object whose position is to be estimated. In the position estimation system 1, the anchor node 100 is a terminal that communicates wirelessly with the target communication terminal 10 and acquires information necessary for estimating the distance to the target communication terminal 10, which is required for the position estimation method.

[0019] The anchor node 100 is, for example, an electronic device that receives a beacon signal of a predetermined frequency. The anchor node 100 may be a device used to estimate the position coordinates of the target communication terminal 10 by wireless communication such as a radio beacon, or it may be an electronic device such as a smartphone, tablet terminal, or various types of computers.

[0020] In the position estimation system 1, in order to estimate the position coordinates of the target communication terminal 10, at least three anchor nodes 100 are required to be able to communicate with the target communication terminal 10. Furthermore, when estimating the position coordinates of the target communication terminal 10, the process of estimating the distance between the target communication terminal 10 and the anchor nodes 100 that are able to communicate with it is performed for each of the three anchor nodes 100. In the position estimation system 1, the number of anchor nodes 100 is not particularly limited as long as there are three or more.

[0021] The target communication terminal 10, like the anchor node 100, can be any electronic device capable of communicating with the anchor node 100 via wireless communication, such as a smartphone, tablet, or various types of computers. The target communication terminal 10 and the anchor node 100 may be the same electronic device, or they may be different electronic devices capable of communicating with each other.

[0022] Both the target communication terminal 10 and the anchor node 100 have control units 11, 110, storage units 12, 120, and communication units 13, 130.

[0023] The control units 11 and 110 are implemented by a computer such as a microcomputer, which is comprised of a processor such as an MCU (Micro Control Unit) (not shown) and a memory for calculations such as RAM (Random Access Memory). The MCU is a computing device that realizes various functions as a target communication terminal 10 or anchor node 100 by executing the calculation processing of a program. The memory is a volatile memory in which the program processed by the MCU is stored. The control units 11 and 110 store the functional programs stored in the storage units 12 and 120 into the memory. The functional programs stored in the storage units are programs for realizing various functions of the target communication terminal 10 or anchor node 100 in this embodiment. Programs corresponding to the functions to be realized are sequentially stored in the memory and executed sequentially by the MCU. The program is composed of functions and fixed values ​​corresponding to the function. When the program is executed, not only functions but also data, which are fixed values, are required.

[0024] The memory units 12 and 120 store identification information that can uniquely identify each target communication terminal 10 or anchor node 100 within the position estimation system 1, the position coordinates of each target communication terminal 10 or anchor node 100 itself, and programs that can be executed by the control units 11 and 110 described above.

[0025] Both communication units 13 and 130 are capable of communicating with the anchor node 100 or the target communication terminal 10 by transmitting and receiving beacon signals of a predetermined frequency.

[0026] Server 500 is an example of an information processing device. Server 500 can, for example, communicate the communication results between the anchor node 100 and the target communication terminal 10 via wireless or wired communication. Server 500 is an example of a computer, such as a PC or server device, realized by a processor (such as an MCU, not shown), a memory for calculations (such as RAM, or Random Access Memory), and a memory unit for storing programs and processing data. The MCU is a calculation unit that realizes various functions of Server 500, as described below, by executing the calculations of the program. The memory is a volatile memory in which programs processed by the MCU are stored. Server 500 stores the functional programs stored in the memory. The functional programs stored in the memory are programs for realizing various functions of Server 500 in this embodiment. The memory sequentially stores programs corresponding to the functions to be realized and is executed sequentially by the MCU. The program consists of functions and fixed values ​​corresponding to the function. When a program is executed, not only functions but also fixed value data are required.

[0027] The server 500, with the hardware configuration and program described above, comprises functional blocks such as the control unit 501, storage unit 502, and communication unit 503.

[0028] The control unit 501, in cooperation with the MCU and memory, executes a program stored in the storage unit 502, thereby realizing its function as an information processing device in the position estimation system 1 by the server 500, and performing the following processing, and executing the position estimation method for the target communication terminal 10.

[0029] The memory unit 502 is implemented using non-volatile memory such as EEPROM (Electrically Erasable Programmable Read-Only Memory). The memory unit 502 stores functional programs for implementing various functions. The memory unit 502 also stores various processing data used by the server 500, such as information used when estimating the position coordinates of the target communication terminal 10, specifically information on the first distance, second distance, and third distance received from the anchor node 100, and information on calculation formulas used to estimate the position coordinates of the target communication terminal 10.

[0030] The communication unit 503 can communicate with external devices, i.e., multiple anchor nodes 100, by means of a communication interface (not shown), for example, via wireless or wired communication. The communication unit 503 may also be able to communicate with the target communication terminal 10.

[0031] The server 500 may also be equipped with an operation unit and a display unit, which are input interfaces for the user to operate the server 500 and output interfaces for the user to perceive the operating status of the server 500.

[0032] Examples of hardware configurations for implementing the control unit include various touch panels, keyboards, numeric keypads, buttons, etc. However, the hardware configuration for implementing the control unit is not limited to the examples described above; it only needs to have the functionality to receive input from the user to operate the server 500. The control unit may, for example, accept operations via commands from various communication interfaces via the communication unit 503, or it may accept operations via voice command input.

[0033] The hardware configuration for the display unit is a display device equipped with a functional unit for the user to perceive the operating status of the server 500, such as an LCD (Liquid Crystal Display) or an organic EL. If the operation unit and display unit are, for example, a touch panel, then the operation unit function and the display unit function are integrated. Furthermore, the server 500 may not have some of the functions of an operation unit or display unit. Also, the server 500 is not limited to having an operation unit and display unit; for example, the operation unit and display unit functions of the server 500 may be realized from other information processing terminals such as an anchor node 100, a smartphone, or a tablet terminal.

[0034] Next, we will describe the specific processing of the method for estimating the position of the target communication terminal 10, which is performed by the server 500 in the position estimation system 1.

[0035] Figure 2 is a functional block diagram schematically showing the position estimation process performed by the server 500 in the position estimation system according to this embodiment.

[0036] As shown in Figure 2, the server 500 implements the following functional blocks for performing position estimation by executing a computer program capable of performing position estimation: an anchor node ranking processing unit 510, a centroid coordinate calculation unit 511, an anchor node re-ranking processing unit 512, a weighted centroid coordinate calculation unit 513, a distance conversion unit 514, an iterative least squares calculation unit 515, an estimation result selection unit 516, and a fixed lag smoothing processing unit 517. Using these functional blocks, the server 500 estimates the position of the target communication terminal 10 according to the RSSI, i.e., the radio wave intensity from the target communication terminal received by three of the three or more anchor nodes 100 capable of communicating with the target communication terminal 10.

[0037] The details of the method for estimating the position of the target communication terminal 10 in the above-described position estimation system 1 will now be explained.

[0038] Figure 3 is a schematic diagram illustrating an example of distance estimation between the three anchor nodes 100 and the target communication terminal 10 in the position estimation process of the target communication terminal 10. Figure 4 is a schematic diagram illustrating an example of a facility targeted for position estimation and movement path estimation processing in the position estimation system 1.

[0039] As shown in Figure 3, the position estimation system 1 emits a beacon signal from the target communication terminal 10, and the three anchor nodes 100 simultaneously receive the beacon signal. The system estimates the distance d from the power intensity (RSSI) of the received signal, and then estimates the position of the target communication terminal 10 by tripoint positioning based on the estimated distance d.

[0040] In the position estimation system 1, the server 500 estimates the position of the target communication terminal 10 in a facility such as the one shown in Figure 4, and estimates the movement path of the target communication terminal 10 based on the estimated position information. In the facility shown in Figure 4, multiple anchor nodes 100, indicated by black dots, are installed on structures such as shelves 300 and walls 400. In the facility shown in Figure 4, the width w1 of the horizontally extending passage between shelves 300 and walls 400 is, for example, 1.7m, the width w2 of the horizontally extending passage between shelves 300 is, for example, 1.4m, and the width w3 of the vertically extending passage is, for example, 2.0m. Also, the spacing D1 between anchor nodes 100 is, for example, 3.0m. Note that the widths w1~w3 of the passages and the spacing D1 are merely examples and are not limited to the values ​​described above.

[0041] Figure 5 is a schematic diagram showing an example of the beacon signal transmission timing in the position estimation system 1.

[0042] As shown in Figure 5, the target communication terminal 10 receives multiple (e.g., N) messages at every secondary time interval (e.g., 100 milliseconds) during the primary time interval (e.g., 1 second). S The operation of transmitting a beacon signal (times) is repeated. In this embodiment, every N time interval, SThe number of beacon signals to be sent back is also referred to as the number of RSSI samples.

[0043] The anchor node ranking processing unit 510 ranks the received radio wave intensities (RSSI) from the target communication terminal 10 received by each of the anchor nodes 100 in descending order of intensity (S101).

[0044] FIG. 6 is a schematic diagram showing an example of the relationship among the calculated centroid coordinates CP, the positions R1, R2, R3 of the top three ranked anchor nodes 100, and the beacon signal transmission position BTP in the position estimation system 1.

[0045] The centroid coordinate calculation unit 511 calculates the centroid coordinates based on the position coordinates of the top three anchor nodes 100 in the rank as a result of the ranking (S102). The centroid coordinates (x c , y c ) can be calculated by the following formula (1). In formula (1), x R1 , x R2 , x R3 represent the x coordinates at the positions R1, R2, R3 of the anchor node 100. Also, in formula (1), y R1 , y R2 , y R3 represent the y coordinates at the positions R1, R2, R3 of the anchor node 100.

[0046] TIFF2026125377000006.tif13170

[0047] The anchor node re-ranking processing unit 512 calculates the distance between the centroid coordinates and the multiple anchor nodes 100 (S103). Based on the calculated distances, the anchor node re-ranking processing unit 512 determines whether the top three anchor nodes 100 ranked in S101 should be excluded (S104). The anchor node re-ranking processing unit 512 also determines whether the top three are the same as the top three in terms of proximity from the centroid coordinates, thereby determining whether any of the top three anchor nodes 100 should be excluded.

[0048] In Figure 6, the beacon signal transmission location BTP is unknown location information. In Figure 6, the anchor node 100 at position coordinate R3 is farther from the centroid coordinate CP than the other anchor nodes 100 at position coordinates R1 and R2. Also, the anchor node 100 at position coordinate R3 is not included within the circle centered on the centroid coordinate CP calculated by equation (1). In other words, in the example shown in Figure 6, the anchor node 100 at position coordinate R3 is to be excluded from the top three ranked anchor nodes 100. If there is an anchor node to be excluded, the anchor node re-ranking processing unit 512 updates the ranking of the top three anchor nodes 100 in order of the closest calculated distance (S105).

[0049] Figure 7 is a schematic diagram illustrating an example of the relationship between the centroid coordinates CP, the positions S1, S2, and S3 of the top three ranked anchor nodes 100 after the update, and the beacon signal transmission position BTP in a position estimation system.

[0050] As shown in Figure 7, the positions S1, S2, and S3 of the top three ranked anchor nodes 100 after the update are all within the range of a circle centered on the centroid coordinate CP calculated by equation (1).

[0051] The weighted centroid coordinate calculation unit 513 calculates the weighted centroid coordinate (x) based on RSSI using the following equation (2). wc , y wcCalculate (S106). In equation (2), x S1 ,x S2 ,x S3 This shows the x-coordinates at positions S1, S2, and S3 of anchor node 100. Also, in equation (2), y S1 ,y S2 ,y S3 This indicates the y-coordinates at positions S1, S2, and S3 of anchor node 100.

[0052] TIFF2026125377000007.tif7170

[0053] In equation (2), the weighting coefficient is given by equation (3) below.

[0054] TIFF2026125377000008.tif41170

[0055] The weighted centroid coordinate calculation unit 513 estimates the position of the target communication terminal 10 based on the weighted centroid coordinate calculated by equation (2) (S107).

[0056] The derivation of the weight coefficients shown in equation (3) will be explained. For distance estimation using RSSI, the RSSI for distance d is obtained by equation (4). TIFF2026125377000009.tif32170

[0057] In equation (4), RSSI0 is the RSSI value at a short distance d0 (e.g., 1.0m). Also, γ is the Path Loss Exponent (PLE). Furthermore, X σ This represents a time-varying variation due to multipath effects and is an unknown value. Therefore, the distance is estimated as shown in equation (5) below.

[0058] TIFF2026125377000010.tif26170

[0059] According to equation (5), the distance d from the RSSI is given by the following equation (6).

[0060] TIFF2026125377000011.tif26170

[0061] The distance from the target communication terminal 10 to the anchor node i is d. i Therefore, the weight coefficients for the positions S1, S2, and S3 of the top three ranked anchor nodes 100 that are close to the centroid coordinates after the update are given by the following equation (7).

[0062] TIFF2026125377000012.tif37170

[0063] The RSSI variable term in equation (7) can be expressed using the Maclaurin series expansion as shown in equation (8) below.

[0064] TIFF2026125377000013.tif34170

[0065] To simplify equation (8), if we use only the nth-order term in equation (8) and allocate it inversely among the anchor nodes, the weight coefficient at anchor node i, given the order n, can be expressed as in equation (9).

[0066] TIFF2026125377000014.tif33170

[0067] According to equation (9), the weight coefficient can be obtained by a simple calculation. In equation (9), it is necessary to select the order n, but in an out-of-line environment as shown in Figure 4, it is known that γ takes a value of around 3.0.

[0068] Figure 8 is a graph illustrating the difference in weighting due to differences in the integer exponent n used in the process of calculating weighted centroid coordinates based on RSSI in the position estimation system. In Figure 8, in equation (7), the sign n represents the weight between two anchor nodes when γ=3.1, and in equation (9), the sign n1 represents the weight between two anchor nodes when n=1, the sign n2 represents the weight between two anchor nodes when n=2, the sign n3 represents the weight between two anchor nodes when n=3, the sign n4 represents the weight between two anchor nodes when n=4, and the sign n5 represents the weight between two anchor nodes when n=5.

[0069] w according to equation (7) i Comparing (γ) with the weight coefficients obtained from equation (9), we find that in equation (9), w i The integer exponent n that approaches (γ) is n=4. In practice, since RSSI includes errors due to multipath variation, it is acceptable to use a lower exponent value, such as n=3, to mitigate its effects.

[0070] The distance conversion unit 514 converts RSSI to distance using the above-described equation (5) (S108). The distances converted at the three anchor nodes are then used to calculate the distances.

[0071] Let's use TIFF2026125377000015.tif6170.

[0072] The iterative least squares calculation unit 515 uses the weighted centroid coordinates as initial values ​​and estimates the position of the target communication terminal 10 based on the distance converted by the distance conversion unit 514 using the iterative least squares method (S109).

[0073] Specifically, the iterative least squares calculation unit 515 uses the weighted centroid coordinates calculated by the weighted centroid coordinate calculation unit 513, weighted by RSSI, as initial values ​​to estimate the position of the target communication terminal 10 using the iterative least squares method. If the iteration index is k, the initial value at initial index k=1 is given by the following equation (10).

[0074] TIFF2026125377000016.tif25170

[0075] Also, weighted centroid coordinates (x wc ,y wc The distance from ) to the positions S1, S2, and S3 of each anchor node is given by the following equation (11). In equation (11), i = 1, 2, and 3.

[0076] TIFF2026125377000017.tif25170

[0077] Weighted centroid coordinates (x) in the vicinity of the estimated position wc ,y wc The distance (coordinate distance) from ) to the positions S1, S2, and S3 of each anchor node is given by the Taylor expansion of equation (11) as follows: equation (12).

[0078] TIFF2026125377000018.tif34170

[0079] Error ε between measured distance and coordinate distance i Taking this into consideration, the distance measured is given by the following equation (13).

[0080] TIFF2026125377000019.tif27170

[0081] Substituting equation (12) into equation (13) and summarizing the three anchor nodes, we obtain the following equation (14).

[0082] TIFF2026125377000020.tif54170 Figure 9 is a schematic diagram illustrating the process of estimating the position of the target communication terminal 10 in the position estimation system based on the measured distance between the three anchor nodes 100 and the target communication terminal 10. Figure 9 shows the difference Δd between the estimated distance and the coordinate distance between the three anchor nodes 100 and the target communication terminal 10. i To minimize the sum of squares, use equation (15) below.

[0083] TIFF2026125377000021.tif32170

[0084] Equation (14) can be expressed in matrix notation as equation (16) below. TIFF2026125377000022.tif31170

[0085] From equation (16), the update amount in iterative minimization is given by equation (17) below.

[0086] TIFF2026125377000023.tif31170

[0087] When the update amount is added to the estimated value and the estimated position is updated, the following equation (18) is obtained.

[0088] TIFF2026125377000024.tif32170

[0089] The iterative least squares calculation unit 515 repeatedly calculates the residual error ε between the measured distance and the coordinate distance by repeating the calculations from equation (13) to equation (18). i As the size decreases, the accuracy of the estimated position improves.

[0090] The estimation result selection unit 516 uses the estimation result of the target communication terminal 10's position using the iterative least squares method as a selection index to select either the estimation result of the target communication terminal 10's position based on weighted centroid coordinates, or the estimation result of the target communication terminal 10's position using the iterative least squares method, as the estimation result of the target communication terminal 10's position.

[0091] The estimation result selection unit 516 selects an estimation result based, for example, on the magnitude of the update vector in the estimation result of the location of the target communication terminal 10 using the iterative least squares method. Specifically, the estimation result selection unit 516 determines, based on the magnitude of the update vector, whether or not the accuracy of the location estimation in the estimation result of the location of the target communication terminal 10 using the iterative least squares method has deteriorated.

[0092] In the repeated least squares calculation unit 515, if the distance error of the measured distance is large, or if the position error of the initial estimated position is large, the estimation accuracy may deteriorate by the repeated least squares method. Therefore, the estimation result selection unit 516 monitors the magnitude of the update amount vector using the selection index E given by the following equation (19).

[0093] TIFF2026125377000025.tif25170

[0094] If the estimation result selection unit 516 determines that the accuracy of the position estimation has not deteriorated, it selects the position estimation result of the target communication terminal 10 using the repeated least squares method as the position estimation result of the target communication terminal 10. On the other hand, if it determines that the accuracy of the position estimation has deteriorated, the estimation result selection unit 516 selects the position estimation result of the target communication terminal 10 based on weighted centroid coordinates as the position estimation result of the target communication terminal 10.

[0095] Specifically, the estimation result selection unit 516 determines that the repeated least squares method is not working effectively if the selection index E shown in equation (19) does not decrease with each iteration of the calculation, or if the selection index E is greater than a predetermined value. In that case, the estimation result selection unit 516 outputs the weighted centroid coordinates, which are the initial values ​​calculated by the weighted centroid coordinate calculation unit 513.

[0096] The fixed lag smoothing processing unit 517 performs a process to estimate the movement path of the target communication terminal 10 based on the estimated position coordinates of the target communication terminal 10. The fixed lag smoothing processing unit 517 can, for example, use Kalman filter smoothing to connect multiple estimated position coordinates of the target communication terminal 10 and process them into a smoothed movement path.

[0097] The state vector at time t used in the fixed lag smoothing processing unit 517 can be expressed by the following equation (20).

[0098] TIFF2026125377000026.tif27170

[0099] In equation (20), the estimated position at time t (complex value) is TIFF2026125377000027.tif6170 Let's assume that.

[0100] Furthermore, in equation (20), the velocity including direction (complex number) Let's call it TIFF2026125377000028.tif7170.

[0101] The expanded state vector obtained by arranging the state vectors in equation (20) vertically is represented by equation (21).

[0102] TIFF2026125377000029.tif41170

[0103] The predicted expansion state estimate at time t can be expressed by equation (22) using the expansion transition matrix F.

[0104] TIFF2026125377000030.tif32170

[0105] The extended transition matrix F can be expressed by equation (23) using the transition matrix A.

[0106] TIFF2026125377000031.tif35170

[0107] The transition matrix A is the transition matrix of states from the state at time t-1 to time t, and is defined as equation (24) below.

[0108] JPEG2026125377000032.jpg23169

[0109] In equation (24), dt is the time interval for estimating the position. I2 is a 2x2 identity matrix. Furthermore, using the posterior covariance matrix P(t) at time t-1, the prior covariance matrix (uncertainty of the estimate) at time t is calculated as shown in equation (25).

[0110] TIFF2026125377000033.tif27170

[0111] In equation (25), b is the system noise vector, σ 2 This is the system noise variance. The filter distance at time t is obtained from the augmented state estimate using the observation vector c=[1…0]. T Using this method, the Kalman gain is calculated as shown in equation (26).

[0112] TIFF2026125377000034.tif28170

[0113] In equation (26), TIFF2026125377000035.tif6170 is the observed noise variance.

[0114] The position of the weighted centroid coordinates at time t can be expressed as a complex number: z(t)=x wc (t) + j·y wc (t)

[0115] When the position estimate at time t is extracted from the state estimate using the observation vector, equation (22) is updated to the following equation (27).

[0116] TIFF2026125377000036.tif32170

[0117] Furthermore, the posterior covariance matrix is ​​updated to the following equation (28).

[0118] TIFF2026125377000037.tif32170

[0119] In equation (28), I 2(L+1) This is the identity matrix with 2(L+1) rows and 2(L+1) columns.

[0120] Based on the above, by extracting the estimated positions of the state vector elements and plotting them as a time series, we can obtain the estimated path after smoothing.

[0121] Next, we will show the results of position estimation and movement path estimation using the weighted centroid coordinate calculation unit 513, as well as the results of position estimation and movement path estimation using the iterative least squares calculation unit 515, as described above.

[0122] Figure 10 shows the number of RSSI samples in the position estimation system, N S This graph illustrates the position estimation process results based on weighted centroid coordinates when = 1. Figure 11 shows the position estimation system with N RSSI sample count. S This graph illustrates the position estimation process results based on weighted centroid coordinates when = 4. Figure 12 shows the position estimation system with N RSSI samples. S This graph illustrates the position estimation process results based on weighted centroid coordinates when = 8.

[0123] In Figures 10 to 12, the vertical axis shows the value of the cumulative distribution function (CDF), and the horizontal axis shows the distance of the error in the position estimation result. In Figures 10 to 12, the distribution of the position estimation result calculated by the weighted centroid coordinate calculation unit 513 is shown by a solid line denoted as R1. In Figures 10 to 12, the distribution of the position estimation result calculated without using the weighted centroid coordinate calculation unit 513, i.e., based on the position coordinates of the top 3 anchor nodes 100 in the rank calculated by the centroid coordinate calculation unit 511, is shown by a dashed line denoted as RA1. In Figures 10 to 12, the distribution of the position estimation result (proximity estimation) based on the maximum received signal strength of RSSI is shown by a dotted line denoted as RA2.

[0124] As can be seen from Figures 10 to 12, the position estimation of the centroid coordinates calculated by the weighted centroid coordinate calculation unit 513 has less error compared to the results of other position estimations.

[0125] Figure 13 is a schematic diagram showing an example of the beacon signal transmission locations at a facility targeted for location estimation and movement path estimation processing in the location estimation system. In Figure 13, the beacon signal transmission locations from the target communication terminal 10 are 600 locations, the movement model of the target communication terminal 10 is a stop-and-go model, and the fastest movement speed is 1.0 m / s.

[0126] Figure 14 shows the number of RSSI samples in the position estimation system, N S This is a schematic diagram showing the movement path estimation results based on weighted centroid coordinates when = 1. Figure 15 shows the position estimation system with an RSSI sample count of N S This is a schematic diagram showing the movement path estimation results based on weighted centroid coordinates when = 4. Figure 16 shows the position estimation system with an RSSI sample count of N S This is a schematic diagram showing the movement path estimation results based on weighted centroid coordinates when = 8.

[0127] Figures 14 to 16 show that the error between the estimated position of the centroid coordinates calculated by the weighted centroid coordinate calculation unit 513 and the transmission position of the beacon signal shown in Figure 13 decreases as the number of RSSI samples increases.

[0128] Figure 17 shows the number of RSSI samples in the position estimation system, N S This graph shows the results of the position estimation process using the repeated least squares method when = 1. Figure 18 shows the position estimation system with N RSSI samples. S This graph shows the results of the repeated least squares method for position estimation when = 4. Figure 19 shows the position estimation system with N RSSI samples. S This graph shows the results of the position estimation process using the repeated least squares method when = 8.

[0129] In Figures 17 to 19, the vertical axis shows the value of the cumulative distribution function (CDF), and the horizontal axis shows the distance of the error in the position estimation result. In Figures 17 to 19, the distribution of the position estimation result calculated by the iterative least squares calculation unit 515 is shown by a solid line labeled R2. In Figures 17 to 19, similar to Figures 10 to 12, the distributions R1, RA1, and RA2 of the position estimation result calculated by the weighted centroid coordinate calculation unit 513 are shown.

[0130] Figures 17 to 19 show that the position estimate calculated by the iterative least squares calculation unit 515 has less error compared to the results of other position estimates.

[0131] Figure 20 shows the number of RSSI samples in the position estimation system, N S This is a schematic diagram showing the results of estimating the movement path based on repeated least squares when = 1. Figure 21 shows the position estimation system with an RSSI sample count of N S This is a schematic diagram showing the results of estimating the movement path based on repeated least squares when = 4. Figure 22 shows the position estimation system with an RSSI sample count of N S This is a schematic diagram showing the results of estimating a travel path based on repeated least squares when = 8.

[0132] Figures 20 to 22 show that the position estimate calculated by the iterative least squares calculation unit 515 shows a smaller error with the beacon signal transmission position shown in Figure 13 as the number of RSSI samples increases. Furthermore, Figures 20 to 22 show that the position estimate calculated by the iterative least squares calculation unit 515 shows an even smaller error with the beacon signal transmission position shown in Figure 13 compared to the position estimate calculated by the weighted centroid coordinate calculation unit 513 shown in Figures 14 to 16.

[0133] Figure 23 is a flowchart showing the position estimation process performed by the server 500 in the position estimation system according to this embodiment.

[0134] In server 500, the anchor node ranking processing unit 510 ranks the top three anchor nodes 100 based on the strength of the received radio signal from the target communication terminal 10 (step S101).

[0135] In server 500, the centroid coordinate calculation unit 511 calculates the centroid coordinates based on the position coordinates of the top three ranked anchor nodes 100 (step S102).

[0136] On server 500, the anchor node reranking processing unit 512 calculates the distance between the centroid coordinates and the multiple anchor nodes 100 (step S103).

[0137] The anchor node re-ranking processing unit 512 determines whether to exclude the top 3 anchor nodes 100 that were ranked in S101 based on the calculated distance (step S104). The anchor node re-ranking processing unit 512 also determines whether the top 3 are the same as the top 3 in order of proximity from the centroid coordinate, thereby determining whether there are any of the top 3 anchor nodes 100 that should be excluded. If it is determined that no anchor nodes should be excluded (S104: NO), the process proceeds to step S106.

[0138] If there are anchor nodes to be excluded (S104: NO), the anchor node re-ranking processing unit 512 updates the ranking of the top 3 anchor nodes 100 in order of their calculated distance (step S105).

[0139] In server 500, the weighted centroid coordinate calculation unit 511 calculates the weighted centroid coordinate (x) based on the received radio wave intensity using the following equation (9). wc , y wc The weighted centroid coordinate calculation unit 511 calculates the weighted centroid coordinate (step S106). Based on the weighted centroid coordinate, the position of the target communication terminal 10 is estimated (step S107).

[0140] TIFF2026125377000038.tif24170

[0141] In server 500, the distance conversion unit 514 converts the received radio signal strength (RSSI) into distance (step S108). In server 500, the iterative least squares calculation unit 515 uses the weighted centroid coordinates as initial values ​​and estimates the position of the target communication terminal 10 based on the distance converted in S108 using the iterative least squares method (step S109).

[0142] In the server 500, the estimation result selection unit 516 selects either the estimation result of the target communication terminal 10's position based on weighted centroid coordinates or the estimation result of the target communication terminal 10's position based on the repeated least squares method as the estimation result of the target communication terminal 10's position (step S110).

[0143] The fixed lag smoothing processing unit 517 performs a process to estimate the movement path of the target communication terminal 10 based on the estimated position coordinates of the target communication terminal 10 (step S111).

[0144] According to the position estimation method executed by the server 500 in the position estimation system 1 described above, when estimating position and movement paths based on RSSI at multiple anchor nodes, position estimation can be easily performed without having to measure and set environment-specific parameters in advance.

[0145] Furthermore, according to the position estimation method executed by the server 500 in the position estimation system 1, the movement path can be estimated by having the fixed lag smoothing processing unit 517 perform time-series smoothing on the estimated position. Therefore, the position estimation method executed by the server 500 in the position estimation system 1 enables low-cost position estimation and movement path estimation.

[0146] Furthermore, those skilled in the art may modify the present invention as appropriate in accordance with prior art knowledge. Such modifications, insofar as they still possess the configuration of the present invention, are of course included within the scope of the present invention.

[0147] For example, in position estimation system 1, an example was described in which the information processing device that performs the position estimation method is a server 500, but the present invention is not limited to this. The information processing device that performs the position estimation method may be an information processing device other than the server 500, and the information processing device and the communication terminal 100 may be a single device.

[0148] For example, in the position estimation system 1, the processing in step S109 by the iterative least squares calculation unit 515 and the processing in step S110 by the estimation result selection unit 516 may be omitted, and the movement path may be estimated by the fixed lag smoothing processing unit 517 based on the estimation result of the position of the target communication terminal 10 based on the weighted centroid coordinates calculated by the weighted centroid coordinate calculation unit 513. [Explanation of Symbols]

[0149] 1...Position estimation system, 10...Target communication terminal, 11...Control unit, 12...Storage unit, 13...Communication unit, 100...Communication terminal (anchor node), 110...Control unit, 120...Storage unit, 130...Communication unit, 300...Shelf, 400...Wall, 500...Information processing device (server), 501...Control unit, 502...Storage unit, 503...Communication unit, 510...Anchor node ranking processing unit, 511...Centroid coordinate calculation unit, 512...Anchor node re-ranking processing unit, 513...Weighted centroid coordinate calculation unit, 514...Distance conversion unit, 515...Iterative least squares calculation unit, 516...Estimated result selection unit, 517...Fixed lag smoothing processing unit

Claims

1. Target communication terminal and At least three or more communication terminals capable of communicating with the aforementioned target communication terminal, An information processing device that estimates the position of the target communication terminal according to the received radio wave strength from the target communication terminal received by three of the multiple communication terminals, A position estimation system equipped with, The aforementioned information processing device is The three communication terminals with the strongest received radio wave strength from the aforementioned target communication terminals are ranked accordingly. Based on the position coordinates of the top three ranked communication terminals, the centroid coordinates are calculated. The distance between the centroid coordinates and the multiple communication terminals is calculated, The ranking of the top three communication terminals, ordered by proximity, is updated. Based on the received radio wave intensity, the weighted centroid coordinates are calculated using the following formula: The position of the target communication terminal is estimated based on the weighted centroid coordinates. Location estimation system.

2. The aforementioned information processing device is Using the aforementioned weighted centroid coordinates as initial values, the position of the target communication terminal is estimated using the least squares method repeatedly. Based on the magnitude of the update vector in the estimation result of the target communication terminal's position using the repeated least squares method, one of the following is selected as the estimation result of the target communication terminal's position: the estimation result of the target communication terminal's position based on the weighted centroid coordinates, or the estimation result of the target communication terminal's position using the repeated least squares method. The position estimation system according to claim 1.

3. The aforementioned information processing device is Based on the magnitude of the update amount vector, it is determined whether or not the accuracy of the position estimation in the position estimation result of the target communication terminal by the repeated least squares method has deteriorated. If it is determined that the accuracy of the position estimation has not deteriorated, the position estimation result of the target communication terminal using the repeated least squares method is selected as the position estimation result of the target communication terminal. If it is determined that the accuracy of the position estimation has deteriorated, the position estimation result of the target communication terminal based on the weighted centroid coordinates is selected as the position estimation result of the target communication terminal. The position estimation system according to claim 2.

4. The aforementioned information processing device is The process of estimating the movement path of the target communication terminal is executed based on the estimated position coordinates of the target communication terminal. A position estimation system according to any one of claims 1 to 3.

5. An information processing device that estimates the position of a target communication terminal based on the received radio wave intensity from the target communication terminal, received by at least three or more communication terminals capable of communicating with the target communication terminal. The three communication terminals with the strongest received radio wave strength from the aforementioned target communication terminals are ranked accordingly. Based on the position coordinates of the top three ranked communication terminals, the centroid coordinates are calculated. The distance between the centroid coordinates and the multiple communication terminals is calculated, The ranking of the top three communication terminals, ordered by proximity, is updated. Based on the received radio wave intensity, the weighted centroid coordinates are calculated using the following formula: The position of the target communication terminal is estimated based on the weighted centroid coordinates. Information processing device.

6. The information processing device is a method for estimating the position of a target communication terminal based on the received radio wave intensity from the target communication terminal, which is received by at least three or more communication terminals capable of communicating with the target communication terminal. The aforementioned information processing device is A process of ranking the top three communication terminals based on the strength of the received radio signal from the target communication terminal. Based on the position coordinates of the top three ranked communication terminals, the centroid coordinates are calculated. A process for calculating the distance between the centroid coordinates and the plurality of communication terminals. A process to update the ranking of the top three communication terminals in order of proximity. Based on the received radio wave intensity, the process involves calculating the weighted centroid coordinates using the following formula, and The process of estimating the position of the target communication terminal based on the weighted centroid coordinates is performed. Location estimation method.

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