Position estimation device, position estimation system, position estimation method, control circuit, and storage medium

Abstract

A position estimating device (1) that estimates the position of a mobile station (100) based on ranging results between each of a plurality of fixed stations and the mobile station includes: a distance calculation unit (13) that calculates an estimated distance between each of the plurality of fixed stations and the mobile station for each fixed station based on the estimated position of the mobile station and the positions of the plurality of fixed stations; an error calculation unit (14) that calculates an error between the ranging result and the estimated distance for each fixed station; a least squares method processing unit (16) that is an estimated position adjustment amount calculation unit that calculates an adjustment amount of the estimated position based on the distance error, which is the error calculated by the error calculation unit, and the partial differential result of the estimated distance; and a position information update unit (17) that updates position information indicating the estimated position based on the adjustment amount. The position of the mobile station is estimated by repeatedly executing an estimated position update process that includes a process of calculating the estimated distance for each fixed station, a process of calculating the error for each fixed station, a process of calculating the adjustment amount, and a process of updating the position information, a defined number of times.

Description

Technical Field

[0001] The present disclosure relates to a position estimation device, a position estimation system, a position estimation method, a control circuit, and a storage medium that estimate the position of an object using an ultra-wideband (UWB) wireless signal.

Background Art

[0002] There is a technique for measuring the distance from the propagation time between a fixed station fixed on the ground and a mobile station using the transmission and reception timing of communication by UWB, and estimating the position of the mobile station using the obtained ranging result and the position of the fixed station. The UWB signal transmitted and received between the mobile station and the fixed station for ranging is an ultra-short pulse signal in the time domain. Therefore, when using a UWB signal, it is possible to grasp the transmission and reception timing of communication with high resolution, measure the distance with high accuracy, and thus estimate the position of the mobile station with high accuracy.

[0003] As a general position estimation algorithm used when performing position estimation, in order to estimate the three-dimensional position (x, y, z) of a mobile station, there is a least squares method for solving a three-dimensional non-linear simultaneous equation regarding the positions of a plurality of fixed stations and the ranging results between the fixed stations and the mobile station, and the position of the mobile station is estimated by sequential approximate calculation. However, when reflected waves due to a wall or the like are received by the fixed station and the mobile station, the pulse waveform of the UWB signal is distorted, so that the ranging result becomes longer than the actual distance between the fixed station and the mobile station. As a result, a ranging result with low accuracy is used for position estimation. For this reason, there is a problem that the position of the mobile station cannot be appropriately estimated.

[0004] As a technology for solving such problems, for example, Patent Document 1 discloses a method of identifying whether radio wave propagation between a fixed station and a mobile station is line of sight (LOS) or non-line of sight (NLOS) based on statistical data of the amplitude and delay of a UWB signal, and improving the position estimation accuracy based on the identification result. In the method disclosed in Patent Document 1, as statistical data of the amplitude and delay at the time of receiving a UWB signal, the sharpness of the received waveform of the UWB signal, the average excess delay spread of multipath components, and the root mean square delay spread are used.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] However, in the technology described in Patent Document 1, in an area where the radio wave environment is unknown, it is necessary to collect statistical data on the multipath channel in advance, and there is a problem that accurate position estimation cannot be performed in a state where statistical data has not been obtained in advance. For this reason, the realization of a technology capable of accurately estimating a position without requiring prior preparations such as data collection is desired.

[0007] The present disclosure has been made in view of the above, and an object thereof is to obtain a position estimation device capable of accurately estimating a position even in an environment where the accuracy of distance measurement based on the transmission and reception timing of signals is reduced due to the influence of reflected waves or the like.

Means for Solving the Problems

[0008] In order to solve the above-described problems and achieve the object, the present disclosure provides a position estimation device that estimates the position of a mobile station based on ranging results between each of a plurality of fixed stations and the mobile station derived from wireless communication results between each of the plurality of fixed stations and the mobile station. The position estimation device includes a distance calculation unit that calculates, for each fixed station, an estimated distance that is the distance between each of the plurality of fixed stations and the mobile station based on the estimated position of the mobile station and the positions of the plurality of fixed stations. Calculated based on the transmission and reception timing of radio signals between a fixed station and a mobile station An error calculation unit that calculates, for each fixed station, an error between the ranging result and the estimated distance; an estimated position adjustment amount calculation unit that calculates an adjustment amount of the estimated position based on the distance error that is the error calculated by the error calculation unit and the partial differential result of the estimated distance; and a position information update unit that updates position information indicating the estimated position based on the adjustment amount. The position estimation device is characterized in that it repeatedly executes an estimated position update process including a process in which the distance calculation unit calculates the estimated distance for each fixed station, a process in which the error calculation unit calculates the error for each fixed station, a process in which the estimated position adjustment amount calculation unit calculates the adjustment amount, and a process in which the position information update unit updates the position information, a predetermined number of times to estimate the position of the mobile station.

Effects of the Invention

[0009] The position estimation device according to the present disclosure has an effect that it can estimate the position with high accuracy even in an environment where the accuracy of ranging based on the signal transmission and reception timing is reduced due to the influence of reflected waves and the like.

Brief Description of the Drawings

[0010]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Figure 12

Figure 13

Figure 14

Figure 15

Figure 16

Figure 17

Figure 18

Figure 19

Figure 20

Figure 21

Figure 22

Mode for Carrying Out the Invention

[0011] Hereinafter, a position estimation device, a position estimation system, a position estimation method, a control circuit, and a storage medium according to embodiments of the present disclosure will be described in detail with reference to the drawings.

[0012] Embodiment 1. FIG. 1 is a diagram showing an example of the configuration of a position estimation system 200 according to Embodiment 1. The position estimation system 200 includes a mobile station 100 having a function as a position estimation device and a plurality of fixed stations 210 to 213 fixed to the ground. In FIG. 1, four fixed stations included in the position estimation system 200 are shown, but the position estimation system 200 may have a configuration including five or more fixed stations. In the following description, each of the fixed stations 210 to 213 may be described as fixed station #0 to #3. Also, when it is not necessary to distinguish each of the fixed stations 210 to 213, the description of the reference numerals may be omitted, and they may simply be referred to as "fixed stations".

[0013] The position estimation system 200 measures the distances between the mobile station 100 and each of the fixed stations 210 to 213 based on the transmission and reception timings of wireless signals transmitted and received by wireless communication between the mobile station 100 and each of the fixed stations 210 to 213, and estimates the position of the mobile station 100 based on the obtained plurality of ranging results. Here, the wireless signal used by the position estimation system 200 is, for example, a UWB signal. As described above, when a UWB signal is used, it is possible to grasp the transmission and reception timings of communication with high resolution, and it is possible to estimate the position of the mobile station 100. In the present embodiment and Embodiments 2 to 5 described later, an example of performing ranging using a UWB signal will be described, but each embodiment is also applicable to a system that performs ranging using a wireless signal other than the UWB signal.

[0014] The positions of the mobile station 100 and the fixed stations 210 to 213 are represented by three-dimensional positions, and the coordinate axes defining this three-dimensional space are the x-axis, y-axis, and z-axis. The positions of the fixed stations 210 to 213 are known, and the position of the fixed station 210 (fixed station #0) is (x 0 , y 0 , z 0 ), the position of the fixed station 211 (fixed station #1) is (x 1 , y 1 , z 1 ), the position of the fixed station 212 (fixed station #2) is (x 2 , y 2 , z 2 ), and the position of the fixed station 213 (fixed station #3) is (x 3 , y 3 , z 3 ).

[0015] Each fixed station transmits a notification signal including its own position information, identification information, etc., and the mobile station 100 can recognize the information of the fixed stations that can communicate based on the received notification signal. The mobile station 100 calculates the propagation time for wireless communication from the transmission and reception timing of the UWB signal with the recognized fixed stations, and obtains the ranging result with the fixed stations.

[0016] When transmitting and receiving UWB signals between the mobile station 100 and each fixed station, if there is an object that reflects radio waves such as a wall, as shown in FIG. 1, in addition to the direct wave 231, a reflected wave 232 will be received. In this case, distortion occurs in the waveform of the received UWB signal.

[0017] FIG. 2 is a diagram showing an example of waveform distortion occurring in a multipath environment. As shown in FIG. 2, in a multipath environment, the received waveform 240 detected on the receiving side is distorted as a result of the synthesis of the waveform 241 of the direct wave 231 and the waveform 242 of the reflected wave 232. As shown in FIG. 2, the received waveform 240 with distortion has its signal waveform shifted backward in time compared to the waveform 241 of the direct wave 231. Therefore, the ranging result based on this received waveform 240 tends to show an increase in distance. That is, the error becomes large. When the accuracy of the ranging result decreases in this way, the position estimation accuracy of the mobile station 100 based on the ranging result also decreases.

[0018] Here, an example where there is a decrease in the accuracy of the distance measurement result and an example where there is no decrease in the accuracy of the distance measurement result will be described with reference to FIGS. 3 and 4. FIG. 3 is a diagram showing a first example of the distance measurement result and the position estimation result. Specifically, FIG. 3 shows an example of the relationship between the distance measurement result when the accuracy of the distance measurement result is not decreased and there is no distance measurement error, and the position estimation result of the mobile station 100. FIG. 4 is a diagram showing a second example of the distance measurement result and the position estimation result. Specifically, FIG. 4 shows an example of the relationship between the distance measurement result when the accuracy of the distance measurement result is decreased and there is a distance measurement error, and the position estimation result of the mobile station 100.

[0019] In the example of " (a) no distance measurement error" shown in FIG. 3, the distance measurement result between the mobile station 100 and the fixed station 210 is r 0 , the distance measurement result between the mobile station 100 and the fixed station 211 is r 1 , the distance measurement result between the mobile station 100 and the fixed station 212 is r 2 , and the distance measurement result between the mobile station 100 and the fixed station 213 is r 3 . The black circle indicates the position estimation result 110, which coincides with the actual position of the mobile station 100.

[0020] In the example of " (b) there is a distance measurement error" shown in FIG. 4, due to the influence of reflected waves or the like, the distance measurement result between the mobile station 100 and the fixed station 211 includes an error, and this distance measurement result is r 1 '. Each distance measurement result between the mobile station 100 and the other fixed stations (fixed stations 210, 212, 213) does not include an error, and these each distance measurement result is r 0 , r 2 , r 3 as in FIG. 3. The distance measurement result r 1 ' is larger than the distance measurement result r 1 in the example shown in FIG. 3 (r 1 '> r 1 ). The white circle indicates the actual position 120 of the mobile station 100, and the black circle indicates the position estimation result 110'. As shown in FIG. 4, when there is a distance measurement error, an error occurs in the position estimation result.

[0021] In Embodiment 1, a position estimation device capable of suppressing a decrease in position estimation accuracy will be described even when the accuracy of the distance measurement result is reduced due to the influence of a reflected wave as described above.

[0022] First, based on the examples shown in FIGS. 3 and 4, the principle of the position estimation method by the position estimation device 1 according to Embodiment 1 will be described.

[0023] In the example of FIG. 3, the mobile station 100 can communicate with the fixed stations 210, 211, 212, and 213 in an ideal radio wave propagation state, and the intersection of four circles with the distance measurement results r 0 , r 1 , r 2 and r 3 as their respective radii is the position estimation result. As an algorithm for this position estimation, for example, calculation is performed based on the least squares method. On the other hand, in the example of FIG. 4, that is, when the ideal radio wave propagation state is not present due to the influence of a reflected wave or the like, an error occurs in the distance measurement result. Since the distance measurement result includes an error, the distance measurement results between the fixed stations 210, 211, 212, and 213 and the mobile station 100 are r 0 , r 1 ', r 2 and r 3 respectively, and r 1 '>r 1 . When the position of the mobile station 100 is estimated by the least squares method using the distance measurement result including an error such as r 1 ', the intersection of the four circles with the respective distance measurement results as their radii cannot be obtained. In this case, a position where the sum of the squared errors is minimized is estimated, and this becomes the position estimation result 110'. That is, a position estimation error occurs with respect to the actual position 120 of the mobile station 100 indicated by the white circle. Therefore, the position estimation device 1 according to the present embodiment repeatedly performs the position estimation calculation of the mobile station 100 so that the influence of the distance measurement result having a large distance measurement error affected by a reflected wave or the like among the distance measurement results between the fixed station and the mobile station 100 is reduced. Specifically, the calculation for estimating the position by the least squares method that performs weighting inversely proportional to the square of the distance measurement error with respect to the distance measurement results between each fixed station and the mobile station 100 is repeatedly performed to obtain the position estimation result.

[0024] Hereinafter, the details of the position estimation device 1 according to Embodiment 1 will be described.

[0025] FIG. 5 is a diagram showing a configuration example of the position estimation device 1 according to Embodiment 1. As shown in FIG. 5, in the present embodiment, it is assumed that the position estimation device 1 is provided in the mobile station 100. Note that the position estimation device 1 may exist as a separate device outside the mobile station 100.

[0026] The position estimation device 1 includes an information acquisition unit 11, a position information setting unit 12, a distance calculation unit 13, an error calculation unit 14, a partial differential processing unit 15, a least squares method processing unit 16, a position information update unit 17, an update end determination unit 18, and an estimation process end determination unit 19.

[0027] FIG. 6 is a flowchart showing an example of the operation of the position estimation device 1 according to Embodiment 1 for estimating the position of the mobile station 100.

[0028] With reference to FIGS. 5 and 6, the detailed operation of the position estimation device 1 will be described for each component. Here, as an example, as shown in FIG. 1, the number of fixed stations included in the position estimation system 200 is set to N = 4, and the position information of the mobile station 100 is assumed to be coordinates (x, y, z). The fixed stations included in the position estimation system 200 can transmit and receive UWB signals to and from the mobile station 100, and are fixed stations that can perform distance measurement as viewed from the mobile station 100 side.

[0029] In the position estimation device 1, the information acquisition unit 11 acquires the position information of each fixed station and the distance measurement results between each fixed station and the mobile station 100 (step S11). The information acquisition unit 11 acquires the position information and the distance measurement results, for example, periodically at a predetermined cycle.

[0030] The location information of each fixed station is obtained by receiving the notification signal transmitted from each fixed station and analyzing the received notification signal. The analysis of the notification signal is performed, for example, by a transmission / reception processing unit (not shown) of the mobile station 100. Note that the information acquisition unit 11 may also perform the analysis of the notification signal.

[0031] The ranging results between each fixed station and the mobile station 100 are derived based on the wireless communication results between each fixed station and the mobile station 100. Specifically, the mobile station 100 transmits and receives UWB signals with each fixed station, calculates the propagation time for wireless communication from the transmission / reception timings of each UWB signal, and obtains ranging results indicating the distances to each fixed station from the calculated propagation time. The processing for obtaining the ranging results is performed, for example, by the transmission / reception processing unit of the mobile station 100. Note that the information acquisition unit 11 may perform each process from the calculation of the above propagation time to obtaining the ranging results. It is also possible that the mobile station 100 calculates the above propagation time and the information acquisition unit 11 calculates the ranging results from the propagation time.

[0032] The information acquisition unit 11 may simultaneously acquire the location information of each fixed station and the ranging results between each fixed station and the mobile station 100, or may acquire them at different timings. For example, each time the mobile station 100 receives a notification signal transmitted from each fixed station, the information acquisition unit 11 may acquire the ranging results between each fixed station and the mobile station 100.

[0033] The location information setting unit 12 sets the location information of the mobile station 100 (step S12). Specifically, the location information setting unit 12 sets the location information (x (k) , y (k) , z (k) ) for estimating the location of the mobile station 100. However, k is the number of convergence times for successive approximation, and k = 1, 2,..., N Loop is set. When k = 1, the location information (x (1) , y (1) , z (1)Regarding , it is not necessarily accurate. In step S12, which is executed first after step S11, that is, in the initial stage where the position of the mobile station 100 has not been calculated, the coordinates around a plurality of fixed stations may be set as the initial value of the position information of the mobile station 100. Further, in step S12 (the first execution of step S12) that is executed first after step S11 is executed, the position information setting unit 12 sets the position information and sets the number of repetitions j to j = 1.

[0034] The distance calculation unit 13 calculates the distance between each fixed station and the mobile station 100 (step S13). In this step S13, the distance calculation unit 13 uses the position information of each fixed station acquired by the information acquisition unit 11 in step S11, the position information set by the position information setting unit 12 in step S12, or the position information updated by the position information update unit 17 described later, to calculate the distance between each fixed station and the mobile station 100. Specifically, in step S13 (the first execution of step S13) that is executed first after step S12 is executed, the distance calculation unit 13 calculates the distance between each fixed station and the mobile station 100 using the position information of each fixed station and the position information set by the position information setting unit 12. In subsequent steps S13 (the second and subsequent executions of step S13), the distance calculation unit 13 calculates the distance between each fixed station and the mobile station 100 using the position information of each fixed station and the position information updated by the position information update unit 17. Note that in step S13 that is executed first after step S12 is executed, the distance calculation unit 13 sets the number of convergence times k to k = 1 and then calculates the distance between each fixed station and the mobile station 100.

[0035] Regarding the position information of each fixed station used by the distance calculation unit 13 for distance calculation as (x i , y i , z i ), and the position information of the mobile station 100 as (x (k) , y (k) , z (k) ), when the distance calculation unit 13 calculates the distance r between the i-th fixed station and the mobile station 100 i(k)Calculate according to the following formula (1). In the following description, the distance r calculated by the distance calculation unit 13 i(k) is referred to as the estimated distance r i(k) in some cases.

[0036]

Number

[0037] In formula (1), let i = 0, 1, …, N - 1. Here, N is the number of fixed stations for which distance measurement is possible, and in the case of the configuration shown in FIG. 1, N = 4.

[0038] Note that when the position information of the mobile station 100 after being updated by the position information update unit 17 described later is input via the update end determination unit 18, the distance calculation unit 13 recalculates the estimated distance using the input position information.

[0039] The error calculation unit 14 calculates the distance error (step S14). Specifically, the error calculation unit 14 calculates the distance error Δr, which is the error between the distance r between the i-th fixed station and the mobile station 100 included in the distance measurement result acquired by the information acquisition unit 11 in step S11 i and the estimated distance r calculated by the distance calculation unit 13 i(k) according to the following formula (2). i(k) Calculate according to the following formula (2).

[0040]

Number

[0041] The partial differential processing unit 15 calculates the partial differential of the distance r i (step S15).

[0042] Here, there is a relationship shown by the following formula (3) between the distance error Δr calculated by the error calculation unit 14 i(k) and the calculation of the partial differential of the estimated distance r i(k) as follows.

[0043]

Number

[0044] In Equation (3), Δx (k) , Δy (k) and Δz (k) represent the errors between the x - coordinate, y - coordinate, and z - coordinate of the estimated position of the mobile station 100 and the actual coordinates (actual x - coordinate, y - coordinate, and z - coordinate), respectively.

[0045] From the relationship between the distance error Δr i(k) from each of the plurality of fixed stations #i (i = 0, 1, …, N - 1) obtained from Equation (3) and the partial differential calculation result of the estimated distance r i(k) , the small change amount of the position of the mobile station 100 shown in the following Equation (4) can be calculated from N simultaneous equations. The small change amount of the position of the mobile station 100 shown in Equation (4) corresponds to the adjustment amount for each coordinate of the estimated position of the mobile station 100. In the following description, the "adjustment amount for each coordinate of the estimated position" is referred to as the "adjustment amount of the estimated position".

[0046]

Equation

[0047] The partial differential processing unit 15 performs partial differential calculation of the estimated distance r i(k) according to the following Equation (5).

[0048]

Equation

[0049] Here, regarding the above Equation (3), when distance measurement is possible with N fixed stations, the matrix expression of the partial differential calculation of the estimated distance r i(k) is as shown in the following Equation (6).

[0050]

Equation

[0051] Also, in the above Equation (3), the distance error Δri(k) When it is the vector representation for the fixed number of times, the following equation (7) is obtained.

[0052]

Equation

[0053] The partial differential processing unit 15 calculates the partial differential of the estimated distance r i(k) , and after that, the row matrix representation of the partial differential calculation of the estimated distance r i(k) shown in Equation (6) and the vector representation of the distance error Δr i(k) for the fixed number of times shown in Equation (7) are output to the least squares method processing unit 16.

[0054] The least squares method processing unit 16 calculates the adjustment amount of the estimated position using the least squares method (step S16).

[0055] In step S16, the least squares method processing unit 16, which is the estimated position adjustment amount calculation unit, calculates the adjustment amount of the estimated position of the mobile station 100 by the least squares method without weighting when j = 0. When the vector representation of the adjustment amount Δp (k) of the estimated position of the mobile station 100 is expressed by the following equation (8), the least squares method processing unit 16 uses the vector representation of the distance error Δr (k) shown in Equation (7) to calculate the adjustment amount Δp (k) of the estimated position of the mobile station 100 by the least squares method. In this case, the vector representation of the adjustment amount Δp (k) of the estimated position calculated by the least squares method processing unit 16 is as follows equation (9).

[0056]

Equation

[0057]

Equation

[0058] Also, when 1 < j, the least squares method processing unit 16 calculates the adjustment amount Δp of the estimated position of the mobile station 100 by the weighted least squares method.(k) is calculated. In this case, the adjustment amount Δp of the estimated position calculated by the least squares processing unit 16 (k) has the following vector representation in Equation (10).

[0059]

Equation

[0060] In Equation (10), W is a diagonal matrix for weighting and is given by the following Equation (11).

[0061]

Equation

[0062] The weighting coefficient, which is an element of the diagonal matrix in Equation (11), is W i = 1 / σ i 2 (i = 0, 1, …, N - 1), and the estimated error (variance σ) of distance measurement is used. Specifically, the weighting coefficient W i is the distance error Δr shown in Equation (2), estimated at the time of the convergence number k of the position between the i-th fixed station and the mobile station 100 i(k) is used and is set as shown in the following Equation (12), which is inversely proportional to the square of the distance measurement error.

[0063]

Equation

[0064] However, since the weighting coefficient W shown in Equation (12) approaches infinity as the distance error Δr i approaches zero, there are cases where the contribution of a specific fixed station becomes extremely high. In this case, the position estimation accuracy decreases, and the calculation result of the least squares method becomes unstable in numerical calculations.

[0065] FIG. 7 shows the distance error Δr in the position estimation device 1 according to Embodiment 1 i(k) i(k) i and the weighting coefficient W iIt is a diagram showing the relationship with. As shown in FIG. 7, as the distance error Δr i(k) approaches zero, the weighting coefficient W i becomes an extremely large value. Therefore, in the position estimation device 1 according to the present embodiment, as shown in FIG. 8, by applying a clip process, when the distance error Δr i(k) approaches zero, the situation where the weighting coefficient W i becomes an extremely large value is avoided. Note that FIG. 8 is a diagram for explaining the clip process used in the position estimation device 1 according to Embodiment 1. FIG. 8 shows, as an example, the distance error Δr i when the clip process is performed with the upper limit of the weighting coefficient W i(k) set to 1, and the relationship with the weighting coefficient W i . Note that the set value of the upper limit of the weighting coefficient W i does not necessarily have to be 1. Any value may be set according to the position estimation accuracy and the stability in numerical calculation.

[0066] The calculation result by the least squares method processing unit 16, that is, the vector of the adjustment amount of the estimated position of the mobile station 100 shown by Equation (9) or Equation (10) is input to the position information update unit 17.

[0067] The position information update unit 17 updates the position information of the mobile station 100 (step S17). Specifically, the position information update unit 17 uses the vector of the adjustment amount of the estimated position of the mobile station 100 input from the least squares method processing unit 16, and according to the following Equation (13), the position information (x (k) , y (k) , z (k) ) indicating the estimated position of the mobile station 100 is updated.

[0068]

Equation

[0069] The position information update unit 17 outputs the updated position information of the mobile station 100 to the update end determination unit 18.

[0070] When the updated end determination unit 18 receives the position information of the mobile station 100 from the position information update unit 17, it determines whether to end the estimated position update process, which is the process of updating the position information of the mobile station 100. That is, it determines whether the number of convergence times k is N Loop (step S18).

[0071] When the number of convergence times k is k = N Loop (step S18: Yes), the updated end determination unit 18 determines that the update of the position information is completed, and outputs the position information (x (k) , y (k) , z (k) ), (k = N Loop + 1) of the mobile station 100 input from the position information update unit 17 to the estimation process end determination unit 19. Accordingly, the estimation process end determination unit 19 executes step S19 described later.

[0072] When the number of convergence times k is k < N Loop (step S18: No), the updated end determination unit 18 determines that the update of the position information continues, and outputs the position information (x (k) , y (k) , z (k) ), (k = 1, 2,..., N Loop ) of the mobile station 100 input from the position information update unit 17 to the distance calculation unit 13 as the updated position information. At this time, the updated end determination unit 18 increments the number of convergence times k (step S21). When the distance calculation unit 13 receives the updated position information of the mobile station 100 from the updated end determination unit 18, it recalculates the distance between each fixed station and the mobile station 100 using the input position information (step S13). Thereafter, until the number of convergence times k becomes k = N Loop , the above-described processes of steps S13 to S18 and S21 are repeated in the position estimation device 1.

[0073] When the estimation process end determination unit 19 receives the position information of the mobile station 100 from the updated end determination unit 18, it determines whether to end the position estimation process of the mobile station 100. That is, it determines whether the number of repetition times j is N rep (step S19).

[0074] When the number of repetitions j is j = N rep (step S19: Yes), the estimation process end determination unit 19 determines that the position estimation process has ended, and the position information (x (k) , y (k) , z (k) ), (k = N Loop + 1) of the mobile station 100 input from the update end determination unit 18 is output as the position estimation result (step S20).

[0075] When the number of repetitions j is j < N rep (step S19: No), the estimation process end determination unit 19 determines that the position estimation process continues, and outputs the position information of the mobile station 100 input from the update end determination unit 18 to the position information setting unit 12. At this time, the estimation process end determination unit 19 increments the number of repetitions j (step S22). When the position information of the mobile station 100 is input from the estimation process end determination unit 19, the position information setting unit 12 sets the input position information (step S12). Specifically, the position information setting unit 12 uses the input position information (x (k) , y (k) , z (k) ), (k = N Loop + 1) to set the position information of the (j + 1)-th mobile station 100 according to the following equation (14).

[0076]

Equation

[0077] Thereafter, until the number of repetitions j becomes j = N rep in the position estimation device 1, the above-described processes of steps S12 to S19, S21, and S22 are repeated.

[0078] As described above, the position estimation device 1 according to Embodiment 1 repeats an update process using the least squares method that weights the estimated position of the mobile station 100 so that the influence of the ranging results with large ranging errors affected by reflected waves or the like is reduced among the ranging results between the plurality of fixed stations and the mobile station 100. This can prevent a decrease in position estimation accuracy. Also, the position estimation accuracy of the mobile station 100 can be improved by repeatedly using the same ranging results.

[0079] Embodiment 2. FIG. 9 is a diagram showing a configuration example of the position estimation device 1a according to Embodiment 2. It is assumed that the position estimation device 1a is provided in the mobile station 100 in the same manner as the position estimation device 1 according to Embodiment 1, but the description of the mobile station 100 is omitted in FIG. 9.

[0080] The position estimation device 1a has a configuration in which an averaging processing unit 20 is added to the position estimation device 1 according to Embodiment 1. The components of the position estimation device 1a other than the averaging processing unit 20 are the same as the components with the same reference numerals in the position estimation device 1 according to Embodiment 1. For this reason, the description of the components other than the averaging processing unit 20 is omitted.

[0081] FIG. 10 is a flowchart showing an example of the operation of the position estimation device 1a according to Embodiment 2 for estimating the position of the mobile station 100. The flowchart shown in FIG. 10 is obtained by adding step S30 to the flowchart of FIG. 6 showing the operation of the position estimation device 1 according to Embodiment 1 for performing position estimation. The processing of each step other than step S30 of the position estimation device 1a according to Embodiment 2 is the same as the processing of the position estimation device 1 according to Embodiment 1 with the same step number. For this reason, the description of the processing of each step other than step S30 is omitted. Note that the processing of step S30 is executed by the averaging processing unit 20.

[0082] When the processing result of step S19 in FIG. 10 is “Yes”, the estimated position of the mobile station 100 output by the estimation processing end determination unit 19 is input to the averaging processing unit 20 of the position estimation device 1a. When the estimated position of the mobile station 100 is input from the estimation processing end determination unit 19, the averaging processing unit 20 performs averaging processing on the input estimated position (step S30). That is, the averaging processing unit 20 executes averaging processing on the estimated position of the mobile station 100 so as to suppress a decrease in the position estimation accuracy of the mobile station 100 due to ranging errors between a plurality of fixed stations and the mobile station 100.

[0083] The estimated position obtained by the averaging processing unit 20 executing the averaging processing is output outside the position estimation device 1a as the position estimation result of the mobile station 100, and is also output to the position information setting unit 12. When the position estimation result is input from the averaging processing unit 20, the position information setting unit 12 holds this, and in the first step S12 of the next position estimation operation, sets the held position estimation result as the position information of the mobile station 100.

[0084] FIG. 11 is a diagram showing a first example of the ranging error between the fixed station and the mobile station 100, FIG. 12 is a diagram showing a second example of the ranging error between the fixed station and the mobile station 100, and FIG. 13 is a diagram showing a third example of the ranging error between the fixed station and the mobile station 100. These FIGS. 11 to 13 show examples of the ranging errors between each of the four fixed stations #0 to #3 and the mobile station 100. Specifically, FIG. 11 shows the case where there is no ranging error between each of the fixed stations #0 to #3 and the mobile station 100. FIG. 12 shows the case where a slightly varying ranging error occurs between each of the fixed stations #0 to #3 and the mobile station 100. FIG. 13 shows the case where a large ranging error due to the influence of reflected waves or the like occurs between each of the fixed stations #0 to #3 and the mobile station 100.

[0085] In the first example shown in FIG. 11, ranging errors 30, 31, 32, and 33 between each of the fixed stations #0 to #3 and the mobile station 100 are all zero. Also, in the second example shown in FIG. 12, there is a slight variation among the ranging errors 40, 41, 42, and 43 between each of the fixed stations #0 to #3 and the mobile station 100. Further, in the third example shown in FIG. 13, there is a variation among the ranging errors 50, 51, 52, and 53 between each of the fixed stations #0 to #3 and the mobile station 100. In particular, the ranging result between the fixed station #3 and the mobile station 100 includes a large ranging error 53 due to the influence of reflected waves.

[0086] As in the second example shown in FIG. 12 and the third example shown in FIG. 13, when there is a variation in the ranging error among the fixed stations, a minute error may occur in the calculation result by the least squares method processing unit 16. As a result, an error may also occur in the position estimation result of the mobile station 100. Further, the position estimation result output from the estimation process end determination unit 19 is used as the initial value (x (1) , y (1) , z (1) ) of the position information of the mobile station 100 set by the position information setting unit 12 in the next position estimation operation. Therefore, when the variation in the ranging error among the fixed stations is large, it may be difficult to improve the position estimation accuracy, such as increasing the number of convergence times k of the position estimation or increasing the number of repetition times j to suppress the contribution of the ranging result affected by the reflected waves to the position estimation. To solve such a problem, the position estimation device 1a according to Embodiment 2 includes an averaging processing unit 20. The averaging processing unit 20 averages the estimated position of the mobile station 100 output from the estimation process end determination unit 19, which is obtained each time the information acquisition unit 11 newly acquires the ranging result obtained between the fixed station and the mobile station 100, using an FIR (Finite Impulse Response) filter, an IIR (Infinite Impulse Response) filter, or the like. Thereby, the position estimation accuracy can be improved.

[0087] As described above, the position estimation device 1a according to the second embodiment includes an averaging processing unit 20 that averages the position estimation results obtained by executing the same processing as the position estimation device 1 according to the first embodiment. Thereby, even when there is variation in the ranging error among the fixed stations of the ranging target, the influence of the variation can be suppressed, and the accuracy of the position estimation of the mobile station 100 can be improved. In addition, the number of convergence times and the number of repetition times of the position estimation can be reduced. Further, it is possible to accurately suppress the contribution of the ranging result affected by the reflected wave to the position estimation, and the accuracy of the position estimation of the mobile station 100 can be improved.

[0088] Embodiment 3. Next, Embodiment 3 will be described. The position estimation device according to Embodiment 3 has the same configuration as the position estimation device 1 according to Embodiment 1 (see FIG. 5). However, the weighting coefficient W used in the weighted least squares method processing by the least squares method processing unit 16 i is different from that in the first embodiment. For this reason, in this embodiment, only the least squares method processing unit 16 and the weighting coefficient W used by the least squares method processing unit 16 i will be described, and the description of other components common to the first embodiment will be omitted.

[0089] The weighting coefficient W used in Embodiment 3 i will be described with reference to FIG. 14. Note that FIG. 14 is a diagram showing an example of the weighting coefficient used in the least squares method processing in the position estimation device according to Embodiment 3. FIG. 14 shows the correspondence between the ranging error and the weighting coefficient. In FIG. 14, the horizontal axis represents the absolute value of the ranging error, and the vertical axis represents the weighting coefficient. σ D is the lower limit value of the absolute value of the distance error Δr i , and in FIG. 14, as an example, σ D = 0.03. Also, σ U is the upper limit value of the absolute value of the distance error Δr i , and in FIG. 14, as an example, σ U = 0.15.

[0090] As shown in FIG. 14, when the ranging error between the fixed station and the mobile station 100 is sufficiently small, the positioning device 1 according to Embodiment 3 uses a weighting coefficient W of a magnitude that does not hinder numerical calculation. i to estimate the position of the mobile station 100.

[0091] The weighting coefficient W used by the least squares method processing unit 16 of the positioning device 1 according to Embodiment 3 i shall be given by the following equation (15). In the following equation (15), i represents the number of the fixed station, and i = 0, 1, …, N - 1.

[0092]

Equation

[0093] For the weighting coefficient W of the above equation (12) used in the positioning device 1 according to Embodiment 1 i as the distance error Δr i(k) approaches zero, the weighting coefficient W i becomes an extremely large value, so clip processing was executed. On the other hand, for the weighting coefficient W of equation (15) used in the positioning device 1 according to Embodiment 3 i instead of clip processing, a lower limit value σ i(k) of the square value ((Δr i(k) ) 2 ) of the distance error Δr D 2 is set. Also, as (Δr i(k) ) 2 increases, the weighting coefficient W i that is inversely proportional to the square rapidly decreases and approaches zero. In particular, when the position information of the mobile station 100 initially set by the position information setting unit 12 during position estimation is greatly deviated from the original position of the mobile station 100, the distance error Δr i(k) between the fixed station and the mobile station 100 tends to be large, and the weighting coefficient W i may be smaller than the original value. This is equivalent to a decrease in the number of effective fixed stations that can be used for position estimation, and there is a possibility that the position estimation accuracy decreases. Therefore, the weighting coefficient Wi so that the lower limit value of (Δr i(k) ) 2 the upper limit value σ of U 2 is set.

[0094] As described above, in the position estimation device 1 according to Embodiment 3, the least squares method processing unit 16 sets the upper limit value and the lower limit value for the weighting coefficient W used in the weighted least squares method processing. i Thereby, it is possible to prevent the weighting coefficient W used in the weighted least squares method processing from becoming a large value in numerical calculation, and even when the accuracy of the position information of the mobile station 100 set during the position estimation of the mobile station 100 is low, it is possible to suppress a decrease in the number of effective fixed stations that can be used for position estimation, and it is possible to prevent a decrease in the accuracy of position estimation. i

[0095] Embodiment 4. FIG. 15 is a diagram showing a configuration example of a position estimation device 1b according to Embodiment 4. Note that it is assumed that the position estimation device 1b is provided in the mobile station 100 in the same manner as the position estimation device 1 according to Embodiment 1, but the description of the mobile station 100 is omitted in FIG. 15.

[0096] The position estimation device 1b has a configuration in which the least squares method processing unit 16 of the position estimation device 1 according to Embodiment 1 is replaced with a least squares method processing unit 16b. That is, the least squares method processing used when estimating the position of the mobile station 100 by the position estimation device 1b is different from that of the position estimation device 1 according to Embodiment 1. Components other than the least squares method processing unit 16b of the position estimation device 1b are the same as the components with the same reference numerals in the position estimation device 1 according to Embodiment 1. For this reason, the description of components other than the least squares method processing unit 16b is omitted.

[0097] FIG. 16 is a flowchart showing an example of the operation of the position estimation device 1b according to the fourth embodiment for estimating the position of the mobile station 100. The flowchart shown in FIG. 16 is obtained by replacing step S16 in the flowchart of FIG. 6 showing the operation of the position estimation device 1 according to the first embodiment for performing position estimation with step S16b. The processing of each step other than step S16b of the position estimation device 1b according to the fourth embodiment is the same as the processing of the position estimation device 1 according to the first embodiment with the same step number. For this reason, the description of the processing of each step other than step S16b is omitted.

[0098] In step S16b, the least squares method processing unit 16b calculates the adjustment amount of the estimated position of the mobile station 100 using the least squares method, similarly to the least squares method processing unit 16 of the position estimation device 1 according to the first embodiment. However, the calculation methods of the least squares method processing unit 16b and the least squares method processing unit 16 are partially different.

[0099] In the least squares method processing unit 16 of the position estimation device 1 according to the first embodiment, when the number of repetitions j = 1, the least squares method processing without weighting is executed, and when the number of repetitions j > 1, the least squares method processing with weighting inversely proportional to the square of the distance error is executed. On the other hand, in the least squares method processing unit 16b of the position estimation device 1b according to the fourth embodiment, even when the number of repetitions j = 1, the least squares method processing with weighting is executed. Thereby, the least squares method processing unit 16b further reduces the influence of the ranging result between the fixed station having a large ranging error due to reflected waves or the like and the mobile station 100 compared to the least squares method processing unit 16, and improves the position estimation accuracy.

[0100] When the number of repetitions j = 1, the least squares method processing unit 16b performs weighted least squares method processing using the weighting coefficient W shown by the following formula (16). i to perform weighted least squares method processing.

[0101]

Equation

[0102] Also, when the number of iterations j satisfies 1 < j, the least squares processing unit 16b performs weighted least squares processing using the weighting coefficient W i shown by the following equation (17).

[0103]

Equation

[0104] In equations (16) and (17), i represents the number of the fixed station, and i = 0, 1, …, N - 1. Also, σ represents the allowable variance of the ranging error, Da 2 which is the lower limit of (Δr i(k) ), σ 2 is the upper limit of (Δr Ua 2 ), σ i(k) is the lower limit of (Δr 2 ), and σ Db 2 is the upper limit of (Δr i(k) ). However, σ 2 > σ Ub 2 , and σ i(k) < σ 2 . Here, it is assumed that σ Da 2 > σ Db 2 , and σ Ua 2 < σ Ub 2 .

[0105] A specific example of the weighting coefficient W i shown in equations (16) and (17) will be described with reference to FIGS. 17 and 18. FIG. 17 is a diagram showing a first example of the weighting coefficient used in the least squares processing in the position estimation device 1b according to the fourth embodiment. Specifically, it shows an example of the weighting coefficient W i used when j = 1. FIG. 18 is a diagram showing a second example of the weighting coefficient used in the least squares processing in the position estimation device 1b according to the fourth embodiment. Specifically, it shows an example of the weighting coefficient W i used when j > 1.

[0106] In FIGS. 17 and 18, the horizontal axis represents the absolute value of the ranging error, and the vertical axis represents the weighting coefficient. σ Da , σ Db is the lower limit value of the absolute value of the distance error Δr i . In FIGS. 17 and 18, as an example, σ Da = 0.05, σ Db = 0.03. Also, σ Ua , σ Ub is the upper limit value of the absolute value of the distance error Δr i . In FIGS. 17 and 18, as an example, σ Ua = 0.07, σ Ub = 0.15.

[0107] Comparing FIG. 17 and FIG. 18, in FIG. 17 showing the case where the number of repetitions j = 1, the section where the weighting coefficient W i is at the upper limit value W i = 1 is larger. Therefore, due to the variation in the ranging error between the fixed station and the mobile station 100, a decrease in the value of the weighting coefficient W i can be prevented. Also, under the condition that (Δr i(k) ) 2 > σ Ua 2 , the value of the weighting coefficient W i can be set larger in FIG. 17.

[0108] By setting the weighting coefficient W i as described above, even when the number of repetitions j = 1, in a situation where there is a large variation in the ranging error between the fixed station and the mobile station 100, the least squares method that weights the ranging result between the fixed station and the mobile station 100 according to the ranging error can be used while suppressing the influence of a large ranging error caused by the reflected wave.

[0109] As described above, in the position estimation device 1b according to the fourth embodiment, even when the number of repetitions j described in the first embodiment is j = 1, the weighting coefficient W iExecute the least squares method process for performing weighting using this. As a result, it is possible to prevent a decrease in the value of the weighting coefficient due to variations in the ranging error between the fixed station and the mobile station 100, suppress the influence of a large ranging error due to reflected waves, and achieve an improvement in the position estimation accuracy.

[0110] Embodiment 5. FIG. 19 is a diagram showing a configuration example of the position estimation device 1c according to Embodiment 5. It is assumed that the position estimation device 1c is provided in the mobile station 100 in the same manner as the position estimation device 1 according to Embodiment 1, but the description of the mobile station 100 is omitted in FIG. 19.

[0111] The position estimation device 1c has a configuration in which an attitude information acquisition unit 21 and a position information correction unit 22 are added to the position estimation device 1a according to Embodiment 2 shown in FIG. 9. Components other than the attitude information acquisition unit 21 and the position information correction unit 22 of the position estimation device 1c are the same as the components with the same reference numerals in the position estimation device 1a according to Embodiment 2. Therefore, descriptions of components other than the attitude information acquisition unit 21 and the position information correction unit 22 are omitted.

[0112] The attitude information acquisition unit 21 acquires the attitude information of the mobile station 100. The attitude information is, for example, acceleration, azimuth, geomagnetic information, etc., and is calculated using the sensing results of sensors mounted on the mobile station 100. The acquisition period of the attitude information by the attitude information acquisition unit 21 is shorter than the period in which the information acquisition unit 11 acquires the position information of each fixed station and executes the position estimation operation of the mobile station 100.

[0113] The position information correction unit 22 corrects the position information indicating the position estimation result of the mobile station 100 output from the averaging processing unit 20 based on the attitude information. The position information correction unit 22 outputs the corrected position information to the position information setting unit 12 at a determined timing. For example, the position information correction unit 22 outputs the corrected position information to the position information setting unit 12 at the timing when the position estimation operation of the mobile station 100 starts and the position information setting unit 12 sets the initial value of the position information of the mobile station 100. That is, the position information corrected by the position information correction unit 22 is used as the initial value of the position information of the mobile station 100 in the next position estimation operation. As described above, since the period in which the attitude information acquisition unit 21 acquires the attitude information is shorter than the period in which the position estimation operation is executed, the position information correction unit 22 corrects the position information based on the latest attitude information, for example, every time the attitude information acquisition unit 21 acquires the attitude information. At this time, the position information correction unit 22 may correct the position information based on the latest attitude information and the past attitude information. The position information correction unit 22 holds the position information input from the averaging processing unit 20 and the plurality of attitude information repeatedly input from the attitude information acquisition unit 21. When the information acquisition unit 11 acquires the position information of each fixed station, the position information held at that time is corrected based on the held attitude information, and the corrected position information may be output to the position information setting unit 12. Alternatively, the position information correction unit 22 holds the position information input from the averaging processing unit 20. After the information acquisition unit 11 acquires the position information of each fixed station, the position information held is corrected based on the latest attitude information first acquired by the attitude information acquisition unit 21, and the corrected position information may be output to the position information setting unit 12. Whether to use only the latest attitude information or a plurality of attitude information including the latest attitude information for the correction of the position information may be determined according to the type of the attitude information.

[0114] FIG. 20 is a flowchart showing an example of the operation of the position estimation device 1c according to Embodiment 5 for estimating the position of the mobile station 100. The flowchart shown in FIG. 20 is obtained by adding steps S31 to S35 to the flowchart of FIG. 10 showing the operation of the position estimation device 1a according to Embodiment 2 for performing position estimation. The processing of each step other than steps S31 to S35 of the position estimation device 1c according to Embodiment 5 is the same as the processing of the position estimation device 1a according to Embodiment 2 with the same step number. Therefore, the description of the processing of each step other than steps S31 to S35 is omitted.

[0115] Before executing step S11, the position estimation device 1c executes steps S31 to S35. That is, the position estimation device 1c first checks whether it holds the previous position estimation result (step S31). Specifically, it checks whether there is position information output from the averaging processing unit 20 to the position information correction unit 22 in the previous position estimation operation of the mobile station 100. If it does not hold the previous position estimation result (step S31: No), the position estimation device 1c checks whether to execute position estimation (step S34). The position estimation device 1c determines to execute position estimation when it satisfies a predetermined condition. If the position estimation device 1c does not execute position estimation (step S34: No), it repeats step S34 and waits until it is time to execute position estimation. When the position estimation device 1c executes position estimation (step S34: Yes), it executes step S11. Then, it proceeds to step S12, and the position information setting unit 12 sets an initial value of the position information of the mobile station 100 using the method described in Embodiment 1 or the like.

[0116] On the other hand, when the previous position estimation result is held (step S31: Yes), the position information correction unit 22 acquires the attitude information of the mobile station 100 from the attitude information acquisition unit 21 (step S32), and corrects the previous position information based on the attitude information (step S33). The previous position information is the above-described previous position estimation result. For example, when the attitude information includes the acceleration and azimuth information of the mobile station 100, the position information correction unit 22 corrects the previous position information using these information and the elapsed time since the previous position information was acquired.

[0117] After correcting the previous position information in step S33, the position estimation device 1c checks whether to execute position estimation (step S35). This step S35 is the same process as step S34 described above. When the position estimation device 1c does not execute position estimation (step S35: No), it returns to step S32 and repeats steps S32 and S33. At this time, in step S33, the position information corrected in the previous step S33 is corrected by the latest attitude information acquired in step S32. Thus, when the position estimation device 1c holds the previous position estimation result (position information), the process of correcting the position information based on the attitude information of the mobile station 100 is repeated until the timing to execute position estimation. When the position estimation device 1c executes position estimation (step S35: Yes), it executes step S11. In step S12 executed subsequently to step S11 at this time, the position information setting unit 12 sets the previous position information after being corrected by the position information correction unit 22 as the initial value of the position information of the mobile station 100.

[0118] As described above, when there is previous position information indicating the estimation result of the previous position estimation operation, the position estimation device 1c according to Embodiment 5 sets the corrected position information obtained by correcting the previous position information based on the attitude information of the mobile station 100 as the initial value of the position information of the mobile station 100 in the newly executed position estimation operation. In the position estimation device 1 according to Embodiment 1, in the case of the first position estimation (the repeated process of the first steps S12 to S17), estimation was performed by the least squares method without weighting. However, in the position estimation device 1c according to Embodiment 5, since the position information corrected using the attitude information can be estimated as the initial value, the weighted least squares method can be implemented from the beginning. Further, since the previous position information corrected using the attitude information is used as the initial value, compared with Embodiment 2 in which the previous position information without correction is used as the initial value, position estimation with an improved convergence speed can be realized.

[0119] Note that in this embodiment, an example of adding the attitude information acquisition unit 21 and the position information correction unit 22 to the position estimation device 1a according to Embodiment 2 has been described. However, the attitude information acquisition unit 21 and the position information correction unit 22 may be added to the position estimation device 1 according to Embodiment 1. In this case, when the estimation process end determination unit 19 outputs the position estimation result to the outside, this position estimation result may also be output to the position information correction unit 22.

[0120] Next, the hardware configuration of the mobile station 100 in which the fixed stations 210 to 213 and the position estimation devices 1, 1a, 1b, 1c described in Embodiments 1 to 5 are provided will be described. The fixed stations 210 to 213 according to Embodiments 1 to 5 and the mobile station 100 in which the position estimation devices 1, 1a, 1b, 1c are provided include a processing circuit. By this processing circuit executing each process for performing the position estimation described in each of Embodiments 1 to 5, each function of the fixed stations 210 to 213 and the position estimation devices 1, 1a, 1b, 1c according to Embodiments 1 to 5 is realized.

[0121] FIG. 21 is a diagram showing an example in the case where the processing circuits included in the fixed stations 210 to 213 or the mobile station 100 according to Embodiments 1 to 5 are configured by a processor and a memory. When the processing circuit is configured by a processor 601 and a memory 602, each function of the processing circuit included in the fixed stations 210 to 213 or the mobile station 100 is realized by software, firmware, or a combination of software and firmware. The software or firmware is described as a program and stored in the memory 602. In the processing circuit, the processor 601 reads and executes the program stored in the memory 602, thereby realizing each function. That is, the processing circuit includes a memory 602 for storing a program by which the processing of the fixed stations 210 to 213 or the mobile station 100 is ultimately executed. Also, these programs can be said to cause a computer to execute the processing procedures or methods of the fixed stations 210 to 213 or the mobile station 100. Note that the program stored in the memory 602 may be provided in a state stored in a storage medium or may be provided via a communication path.

[0122] Here, the processor 601 may be, for example, a CPU (Central Processing Unit), a processing device, an arithmetic device, a microprocessor, a microcomputer, or a DSP (Digital Signal Processor). Also, the memory 602 includes, for example, non-volatile or volatile semiconductor memories such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable ROM), EEPROM (registered trademark) (Electrically EPROM), magnetic disks, flexible disks, optical disks, compact disks, mini disks, or DVDs (Digital Versatile Discs).

[0123] Also, the processing circuit included in the fixed stations 210 to 213 or the mobile station 100 according to Embodiments 1 to 5 may be configured using dedicated hardware.

[0124] FIG. 22 is a diagram showing an example in the case where the processing circuits included in the fixed stations 210 to 213 or the mobile station 100 according to Embodiments 1 to 5 are configured by dedicated hardware. When the processing circuit is configured by dedicated hardware, the processing circuit 603 shown in FIG. 22 corresponds to, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a combination thereof. Each function of the fixed stations 210 to 213 or the mobile station 100 may be realized by the processing circuit 603 according to the function, or each function may be realized together by the processing circuit 603.

[0125] Note that, regarding each function of the fixed stations 210 to 213 or the mobile station 100 according to Embodiments 1 to 5, a part may be realized by dedicated hardware and a part may be realized by software or firmware. In this way, the processing circuit can realize each of the above functions by dedicated hardware, software, firmware, or a combination thereof.

[0126] The configurations shown in the above embodiments are merely examples, and it is possible to combine them with other known technologies, to combine the embodiments with each other, and to omit or change a part of the configuration without departing from the gist.

Description of Reference Numerals

[0127] 1, 1a, 1b, 1c position estimation device, 11 information acquisition unit, 12 position information setting unit, 13 distance calculation unit, 14 error calculation unit, 15 partial differential processing unit, 16, 16b least squares method processing unit, 17 position information update unit, 18 update end determination unit, 19 estimation processing end determination unit, 20 averaging processing unit, 21 attitude information acquisition unit, 22 position information correction unit, 100 mobile station, 110, 110' position estimation result, 120 actual position of the mobile station, 200 position estimation system, 210, 211, 212, 213 fixed station, 231 direct wave, 232 reflected wave, 240 received waveform, 241 waveform of the direct wave, 242 waveform of the reflected wave.

Claims

1. 1. A position estimation device that estimates a position of a mobile station based on a distance measurement result between each of a plurality of fixed stations and the mobile station, the distance measurement result being derived based on a wireless communication result between each of the plurality of fixed stations and the mobile station, a distance calculation unit that calculates an estimated distance between each of the plurality of fixed stations and the mobile station based on the estimated position of the mobile station and positions of the plurality of fixed stations; an error calculation unit that calculates an error between the distance measurement result calculated based on transmission and reception timing of radio signals between the fixed station and the mobile station and the estimated distance for each of the fixed stations; an estimated position adjustment amount calculation unit that calculates an adjustment amount of the estimated position based on a distance error, which is the error calculated by the error calculation unit, and a partial differentiation result of the estimated distance; a position information update unit that updates position information indicating the estimated position based on the adjustment amount; Equipped with a process in which the distance calculation unit calculates the estimated distance for each of the fixed stations, a process in which the error calculation unit calculates the error for each of the fixed stations, a process in which the estimated position adjustment amount calculation unit calculates the adjustment amount, and a process in which the position information update unit updates the position information, the process being repeated a predetermined number of times to estimate the position of the mobile station; A position estimation device comprising:

2. the estimated position adjustment amount calculation unit calculates the adjustment amount using a least squares method that performs weighting inversely proportional to a square value of the distance error; 2. The position estimation device according to claim 1 .

3. the estimated position adjustment amount calculation unit calculates the adjustment amount using a least squares method that does not perform the weighting in a first estimated position update process, and calculates the adjustment amount using a least squares method that performs weighting inversely proportional to the square of the distance error in a second or subsequent estimated position update process.

3. The position estimation device according to claim 2.

4. The weighting coefficient used in the weighting is set to a value within a range between a predetermined minimum value and a predetermined maximum value based on the squared value of the distance error.

3. The position estimation device according to claim 2.

5. When the estimated location update process has been repeatedly executed the predetermined number of times, a location indicated by the updated location information obtained is set as a new estimated location of the mobile station, and the estimated location update process is repeatedly executed the predetermined number of times, thereby executing a location estimation process the predetermined number of times.

2. The position estimation device according to claim 1 .

6. When the estimated location update process has been repeatedly executed the predetermined number of times, a location indicated by the updated location information obtained is set as a new estimated location of the mobile station, and the estimated location update process is repeatedly executed the predetermined number of times to execute a location estimation process a predetermined number of times; a weighting coefficient used in the weighting is set to a value within a range of a predetermined minimum value and a predetermined maximum value based on a square value of the distance error; a weighting coefficient used in the weighting in a first position estimation process is a minimum value when a squared value of the distance error is equal to or less than a first value, and a weighting coefficient used in the weighting in a second or subsequent position estimation process is a minimum value when a squared value of the distance error is equal to or less than a second value that is smaller than the first value.

3. The position estimation device according to claim 2.

7. an averaging processing unit that performs an averaging process on the location information obtained by executing the location estimation process the specified number of times, and the location information after the averaging process is performed is set as a location estimation result of the mobile station; 7. The position estimation device according to claim 5 or 6.

8. an attitude information acquisition unit for acquiring attitude information of the mobile station; a position information correction unit that corrects the position information after the averaging process is performed by the averaging processing unit based on the attitude information; Equipped with when starting a position estimation operation for estimating the position of the mobile station by repeatedly executing the position estimation process, the position information obtained in the previous position estimation operation is subjected to the averaging process by the averaging processing unit and the correction by the position information correction unit, and the corrected position information is set as an initial value of the position information of the mobile station.

8. The position estimation device according to claim 7.

9. The mobile station is provided with the position estimation device according to claim 1 ; The fixed station; A position estimation system comprising:

10. A position estimation method in which a position estimation device estimates a position of a mobile station based on distance measurement results between each of a plurality of fixed stations and the mobile station, the distance measurement results being derived based on results of wireless communication between each of the plurality of fixed stations and the mobile station, comprising: a distance calculation step of calculating an estimated distance between each of the plurality of fixed stations and the mobile station, based on the estimated position of the mobile station and positions of the plurality of fixed stations; an error calculation step of calculating, for each of the fixed stations, an error between the distance measurement result calculated based on transmission and reception timing of radio signals between the fixed station and the mobile station and the estimated distance; an estimated position adjustment amount calculation step of calculating an adjustment amount of the estimated position based on the distance error, which is the error calculated in the error calculation step, and a partial differentiation result of the estimated distance; a position information updating step of updating position information indicating the estimated position based on the adjustment amount; a predetermined number of times to estimate the position of the mobile station.

11. A control circuit for controlling a position estimation device that estimates a position of a mobile station based on a distance measurement result between each of a plurality of fixed stations and the mobile station, the distance measurement result being derived based on a wireless communication result between each of the plurality of fixed stations and the mobile station, a distance calculation step of calculating an estimated distance between each of the plurality of fixed stations and the mobile station, based on the estimated position of the mobile station and positions of the plurality of fixed stations; an error calculation step of calculating, for each of the fixed stations, an error between the distance measurement result calculated based on transmission and reception timing of radio signals between the fixed station and the mobile station and the estimated distance; an estimated position adjustment amount calculation step of calculating an adjustment amount of the estimated position based on the distance error, which is the error calculated in the error calculation step, and a partial differentiation result of the estimated distance; a position information updating step of updating position information indicating the estimated position based on the adjustment amount; a predetermined number of times to estimate the position of the mobile station.

12. A storage medium storing a program for controlling a position estimation device that estimates a position of a mobile station based on a distance measurement result between each of a plurality of fixed stations and the mobile station, the distance measurement result being derived based on a wireless communication result between each of the plurality of fixed stations and the mobile station, the storage medium comprising: The program is a distance calculation step of calculating an estimated distance between each of the plurality of fixed stations and the mobile station, based on the estimated position of the mobile station and positions of the plurality of fixed stations; an error calculation step of calculating, for each of the fixed stations, an error between the distance measurement result calculated based on transmission and reception timing of radio signals between the fixed station and the mobile station and the estimated distance; an estimated position adjustment amount calculation step of calculating an adjustment amount of the estimated position based on the distance error, which is the error calculated in the error calculation step, and a partial differentiation result of the estimated distance; a position information updating step of updating position information indicating the estimated position based on the adjustment amount; a predetermined number of times to estimate the position of the mobile station.

Images