JP5577810B2 - POSITION ESTIMATION DEVICE, POSITION ESTIMATION PROGRAM, AND POSITION ESTIMATION METHOD - Google Patents

Description

  The present invention relates to a position estimation device, a position estimation program, and a position estimation method.

  2. Description of the Related Art Conventionally, some terminal devices such as mobile phones have a built-in wireless IC (Integrated Circuit) tag. Such a wireless IC tag stores various data and communicates with a device that reads the data by radio waves or electromagnetic waves. In addition, the wireless IC tag can be attached to various devices as well as the terminal device, and identification, management, and the like of a person or an object to which the wireless IC tag is attached are performed.

  In addition, estimating the position of the wireless IC tag is important when providing product information, position information, and the like to the user of the terminal device. In particular, in a multipath environment such as an underground shopping center or a crowded station, a more accurate position estimation is required. In the position estimation method, a line-of-sight (LOS) environment or a non-line-of-sight (NLOS) environment dynamically appears between the access point and the terminal device. For this reason, it is difficult to use a ranging method using a laser or the like that can be applied only to the LOS environment in a multipath environment.

  Thus, recently, as one aspect, there is a position estimation method using radio waves that can be applied even in an NLOS environment. For example, in position estimation using radio waves, the position estimation is performed with reference to an access point such as a wireless local area network (LAN) whose installation position is known because the distance from the terminal device is relatively small. Relatively small.

  As another mode, there is a position estimation method using an array antenna. For example, in position estimation using an array antenna, since the resolution of identification in the circumferential direction from the access point can be increased, the influence of interference due to multipath waves caused by surrounding objects can be suppressed.

JP 2008-216084 A JP 2005-333489 A JP 2006-2111284 A JP-A-7-231473

  However, the conventional technique has a problem that the position of the object cannot be estimated with high accuracy. Specifically, in the conventional technology, the position of a person in a crowded place, the density of the person, etc. change from moment to moment, resulting in a propagation state different from a measurement environment without people or obstacles. An error will occur.

  Therefore, the technology disclosed in the present application has been made in view of the above, and provides a position estimation device, a position estimation program, and a position estimation method capable of estimating the position of an object with high accuracy. With the goal.

  In order to solve the above-described problems and achieve the object, the position estimation device disclosed in the present application is the received power of the terminal measured in a state where there is no obstacle and the distance between the own device and the terminal is known. And a measured value holding unit that holds the distance between the device and the terminal. In addition, the position estimation apparatus includes a measurement unit that measures the received power of the measurement target terminal that is the measurement target and the degree of congestion in the environment of the measurement target terminal. Further, the position estimation device approximates using an arbitrary function from the relationship between the received power measured by the measurement unit and the degree of congestion, and receives when there is no degree of congestion obtained by extrapolating the approximated function. A reception power calculation unit for obtaining power is included. Further, the position estimation device approximates using an arbitrary function from the relationship between the received power and the distance held in the measurement value holding unit, and based on the approximated function and the received power obtained by the received power calculation unit. And a distance calculation unit for obtaining a distance between the own device and the measurement target terminal.

  One aspect of the position estimation device, the position estimation program, and the position estimation method disclosed in the present application has an effect that the position of the object can be estimated with high accuracy.

FIG. 1 is a diagram illustrating a configuration example of the position estimation apparatus according to the first embodiment. FIG. 2 is a diagram illustrating an example of a function obtained by the received power, the degree of congestion, and approximation according to the first embodiment. FIG. 3 is a diagram illustrating an example of a function obtained by the received power, the distance, and the approximation held in the measurement value holding unit according to the first embodiment. FIG. 4 is a diagram illustrating the distance obtained by the distance calculation unit according to the first embodiment. FIG. 5 is a diagram illustrating a configuration example of the position estimation apparatus according to the second embodiment. FIG. 6A is a diagram illustrating a distance measurement example using the laser distance meter according to the second embodiment. FIG. 6B is a diagram illustrating a distance measurement example using the laser distance meter according to the second embodiment. FIG. 7 is a diagram illustrating the relationship between the distance measured by the congestion degree measurement unit according to the second embodiment and time. FIG. 8 is a diagram illustrating examples of functions obtained by the received power, the degree of congestion, and the least square approximation according to the second embodiment. FIG. 9 is a flowchart illustrating an example of the position estimation process according to the second embodiment. FIG. 10A is a diagram illustrating a result of position estimation performed by the position estimation apparatus according to the second embodiment. FIG. 10B is a diagram illustrating a frequency distribution of distance calculation errors according to the second embodiment. FIG. 10C is a diagram illustrating a position estimation result according to the conventional technique. FIG. 10D is a diagram showing a frequency distribution of distance calculation errors according to the related art. FIG. 11 is a diagram illustrating a temperature measurement example using the infrared thermometer according to the third embodiment. FIG. 12 is a diagram illustrating a relationship between temperature and time measured by the congestion degree measurement unit according to the third embodiment. FIG. 13 is a diagram illustrating an example of a function obtained by the received power, the degree of congestion, and the least square approximation according to the third embodiment. FIG. 14 is a flowchart illustrating an example of position estimation processing according to the third embodiment. FIG. 15 is a diagram illustrating an example of a computer that executes a position estimation program.

  Embodiments of a position estimation device, a position estimation program, and a position estimation method disclosed in the present application will be described below with reference to the accompanying drawings. In addition, this invention is not limited by the following examples. In addition, the embodiments can be appropriately combined within a range that does not contradict the contents.

  The configuration of the position estimation apparatus according to the first embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating a configuration example of the position estimation apparatus according to the first embodiment. For example, as illustrated in FIG. 1, the position estimation device 1 includes a measurement value holding unit 2, a measurement unit 3, a received power calculation unit 4, and a distance calculation unit 5. The position estimation device 1 is, for example, a base station that is an access point having a beam antenna.

  The measured value holding unit 2 holds the received power of the terminal measured in a state where there is no obstacle and the distance between the own device and the terminal is known, and the distance between the own device and the terminal. The measurement unit 3 measures the received power of the measurement target terminal that is the measurement target and the degree of congestion in the environment of the measurement target terminal.

  The received power calculation unit 4 approximates using an arbitrary function from the relationship between the received power measured by the measurement unit 3 and the degree of congestion, and there is no degree of congestion obtained by extrapolating the approximated function. Obtain received power.

  Here, the received power, the degree of congestion, and the function obtained by approximation will be described with reference to FIG. FIG. 2 is a diagram illustrating an example of a function obtained by the received power, the degree of congestion, and approximation according to the first embodiment. In FIG. 2, the vertical axis represents received power (RSS) and the horizontal axis represents density (degree of congestion).

For example, the black dots shown in FIG. 2 indicate the relationship between the received power measured by the measuring unit 3 and the degree of congestion. Then, the received power calculation unit 4 approximates with an arbitrary function from the relationship between the received power and the degree of congestion, and obtains a solid curve shown in FIG. Subsequently, the received power calculation unit 4 obtains the received power RSS ₁ when the degree of congestion obtained by extrapolating the solid curve is zero. When extrapolating the solid curve, the dotted curve shown in FIG. 2 is obtained.

  The distance calculation unit 5 approximates using an arbitrary function from the relationship between the reception power and the distance held in the measurement value holding unit 2, and uses the approximated function and the reception power obtained by the reception power calculation unit 4. Based on this, the distance between the device itself and the measurement target terminal is obtained.

  Here, the distance calculated | required by the distance calculation part 5 which concerns on Example 1 is demonstrated using FIG.3 and FIG.4. FIG. 3 is a diagram illustrating an example of functions obtained by reception power, distance, and approximation held in the measurement value holding unit 2 according to the first embodiment. FIG. 4 is a diagram illustrating the distance obtained by the distance calculation unit 5 according to the first embodiment. 3 and 4, the vertical axis represents received power (RSS), and the horizontal axis represents the distance to the user who has the terminal or the measurement target terminal.

For example, the black dots shown in FIG. 3 indicate the relationship between the received power held in the measured value holding unit 2 and the distance. Then, the distance calculation unit 5 approximates with an arbitrary function from the relationship between the reception power and the distance, and obtains a solid curve shown in FIG. Subsequently, as shown in FIG. 4, the distance calculation unit 5 obtains the distance from the received power RSS ₁ obtained by the received power calculation unit 4 to the user having the measurement target terminal using this curve. The obtained distance is output to a predetermined display unit or notified to another device.

  As described above, the position estimation apparatus 1 includes a graph of the relationship between the reception power when the congestion level is virtually zero and the reception power measured in advance in a non-congested environment and the distance to the user. The distance to the current user is obtained by comparison. As a result, the position estimation apparatus 1 is capable of calculating the distance in a crowded place compared to the conventional technique in which an error occurs in position estimation due to a propagation state different from a measurement environment without a person or an obstacle. The position can be estimated with high accuracy.

[Configuration of Transmission Apparatus According to Second Embodiment]
The configuration of the position estimation apparatus according to the second embodiment will be described with reference to FIG. FIG. 5 is a diagram illustrating a configuration example of the position estimation apparatus according to the second embodiment.

  For example, as illustrated in FIG. 5, the position estimation device 100 includes a beam antenna 101 and a measurement sensor 102. In addition, the position estimation apparatus 100 includes a measurement value holding unit 111. Further, the position estimation device 100 includes a sensor switching unit 121, a user ID (IDentifier) recognition unit 122, a received power measurement unit 123, a congestion degree measurement unit 124, a least square approximation function generation unit 125, and a position estimation unit. 126. The position estimation device 100 is an example of the position estimation device 1 according to the first embodiment.

  The beam antenna 101 is an antenna having directivity, for example, and outputs beams in a plurality of directions. The measurement sensor 102 is a sensor such as a laser distance meter, for example, and operates following the beam antenna 101. The measurement sensor 102 starts measurement using a laser distance meter when notified of the start of measurement of the degree of congestion by a congestion degree measurement unit 124 described later.

  The measurement value holding unit 111 is, for example, the position estimation device 100 in a state where there is no user other than the user who has the terminal, other obstacles, and the distance between the position estimation device 100 and the terminal is known. The received reception power and the distance to the terminal are held. The distance to the terminal is preferably measured using a laser distance meter or other equipment. The measured value holding unit 111 holds data measured as described above in advance. The measurement value holding unit 111 is, for example, a semiconductor memory element such as a random access memory (RAM), a read only memory (ROM), and a flash memory, or a storage device such as a hard disk or an optical disk.

  For example, the sensor switching unit 121 controls the beam antenna 101 and performs switching control of the measurement sensor 102 so that the measurement sensor 102 operates following the beam antenna 101. In the control of the beam antenna 101 by the sensor switching unit 121, the beam direction is fixed when the user ID recognition unit 122 described later notifies that the user ID has been recognized. Then, when the user ID recognition unit 122 cannot confirm the user ID, the sensor switching unit 121 causes the beam antenna 101 to output a beam again to search for a measurement target terminal to be measured.

  For example, when a user ID is returned from the measurement target terminal to the beam output from the beam antenna 101, the user ID recognition unit 122 recognizes the user ID and notifies the sensor switching unit 121 of the user ID. Then, the user ID recognition unit 122 notifies the position estimation unit 126 of the recognized user ID.

  The received power measuring unit 123 receives, for example, a signal transmitted from a measurement target terminal that has received the beam output from the beam antenna 101, and measures the received power (RSS) of the received signal. Then, the received power measuring unit 123 compares the measured received power with a predetermined threshold, and when the received power is equal to or lower than the predetermined threshold, requests the congestion degree measuring unit 124 to measure the degree of congestion. On the other hand, the received power measurement unit 123 determines that the measurement target terminal is located at a location very close to the LOS and the position estimation device 100 when the measured received power is larger than the predetermined threshold. The received power measuring unit 123 notifies the measured received power to the least square approximation function generating unit 125.

  The congestion degree measurement unit 124 notifies the measurement sensor 102 of the start of the congestion degree when, for example, the reception power measurement unit 123 is requested to measure the congestion degree. Then, the congestion degree measurement unit 124 notifies the measured degree of congestion to the least square approximation function generation unit 125.

  Here, the measurement of the distance using the laser rangefinder according to the second embodiment will be described with reference to FIGS. 6A and 6B. 6A and 6B are diagrams illustrating an example of distance measurement using the laser distance meter according to the second embodiment. 6A and 6B show a situation in which the user having the measurement target terminal and the position estimation apparatus 100 become LOS or NLOS in a closed space such as an underground street passage. In FIGS. 6A and 6B, a user having a measurement target terminal is indicated by a shaded circle, and obstacles other than the user are indicated by a black circle. 6A and 6B, the beam output from the beam antenna 101 is indicated by a shaded ellipse, and the laser output by the laser distance meter is indicated by an arrow.

For example, as shown in FIGS. 6A and 6B, the congestion degree measurement unit 124 causes the measurement sensor 102 to scan at an angle of left and right Δθ in the beam direction θ _n of the beam antenna 101, and the distance to the nearest obstacle. Measure. The scanning angle Δθ is, for example, 10 °. Note that the laser output by the laser distance meter of the measurement sensor 102 may be fixed in a fixed direction without being scanned at an angle of [Delta] [theta] left and right since no obstacle is fixed. At this time, for example, the congestion degree measurement unit 124 controls the measurement sensor 102 to output a laser at a period T, and measures the degree of congestion by measuring the distance to the obstacle.

  Here, the relationship between the distance and time measured by the congestion degree measuring unit 124 according to the second embodiment will be described with reference to FIG. FIG. 7 is a diagram illustrating the relationship between the distance and time measured by the congestion degree measurement unit 124 according to the second embodiment. In FIG. 7, the vertical axis indicates the distance to the obstacle, and the horizontal axis indicates time. The “obstacle” refers to a crowd.

  For example, as shown in FIG. 7, the congestion degree measurement unit 124 performs “obstacle A”, “obstacle B”, “obstacle C”, “obstacle D”, “obstacle E” for each period T and Measure the distance to “obstacle F” etc. Further, the congestion degree measuring unit 124 decreases the period T as the congestion degree increases. That is, when the degree of congestion is large, a more useful degree of congestion can be measured by shortening the measurement frequency and increasing the number of updates.

  For example, the least square approximation function generation unit 125 approximates with a least square approximation function from the relationship between the received power measured by the received power measurement unit 123 and the degree of congestion measured by the congestion degree measurement unit 124. Then, the least square approximation function generation unit 125 obtains the received power when there is no congestion degree obtained by extrapolating the approximated function.

  Here, a function obtained by the received power, the degree of congestion, and the least square approximation according to the second embodiment will be described with reference to FIG. FIG. 8 is a diagram illustrating examples of functions obtained by the received power, the degree of congestion, and the least square approximation according to the second embodiment. In FIG. 8, the vertical axis indicates the received power, and the horizontal axis indicates the density or the distance to the obstacle.

For example, the black dots shown in FIG. 8 indicate the relationship between the received power obtained by the received power measuring unit 123 and the distance measured by the congestion degree measuring unit 124. Further, A to F shown in FIG. 8 correspond to A to F shown in FIG. Then, the least square approximation function generation unit 125 approximates with the least square approximation function from the relationship between the received power and the degree of congestion, and obtains a solid line shown in FIG. Subsequently, the least square approximation function generation unit 125 obtains the received power RSS ₁ when the congestion degree obtained by extrapolating the solid line is zero, that is, when reaching the opposite wall. In addition, when extrapolating a solid line, it becomes a dotted line shown in FIG.

  For example, the position estimation unit 126 approximates with a least square approximation function from the relationship between the received power and the distance held in the measurement value holding unit 111. Then, the position estimation unit 126 obtains a distance between the position estimation device 100 and the measurement target terminal based on the approximated function and the received power obtained by the least square approximation function generation unit 125. The calculation of the distance by the position estimation unit 126 is the same as that shown in FIG. The position estimating unit 126 receives the user ID from the user ID recognizing unit 122 and outputs the user ID and the obtained distance to a predetermined display unit or notifies other devices. Further, the other device notifies the route information to the terminal corresponding to the user ID based on the received user ID and distance, or notifies the product information of a nearby shop.

  The sensor switching unit 121 to the position estimation unit 126 are integrated circuits such as an ASIC (Application Specific Integrated Circuit) and an FPGA (Field Programmable Gate Array). Or the sensor switching part 121-the position estimation part 126 are electronic circuits, such as CPU (Central Processing Unit) and MPU (Micro Processing Unit), for example. The measured value holding unit 111 is an example of the measured value holding unit 2 according to the first embodiment. The congestion degree measurement unit 124 and the received power measurement unit 123 are an example of the measurement unit 3 according to the first embodiment. The least square approximation function generation unit 125 is an example of the received power calculation unit 4 according to the first embodiment. The position estimation unit 126 is an example of the distance calculation unit 5 according to the first embodiment.

[Position Estimation Processing According to Second Embodiment]
Next, the position estimation process according to the second embodiment will be described with reference to FIG. FIG. 9 is a flowchart illustrating an example of the position estimation process according to the second embodiment.

For example, as shown in FIG. 9, the position estimation apparatus 100 sets the beam angle of the beam antenna 101 to “θ _n = θ ₁ ” (step S101). And the position estimation apparatus 100 starts the beam scan by the beam antenna 101 (step S102). Subsequently, the position estimation apparatus 100 determines whether or not the user ID has been recognized by the beam scan with the beam angle “θ _n ” (step S103).

At this time, if the user ID cannot be recognized (No at Step S103), the position estimation apparatus 100 sets “n = n + 1” and determines whether “n <= N” (Step S104). N is, for example, the total number of beam directions that can be scanned. Then, when the above condition is not satisfied, that is, when the beam scan started from the beam angle “θ ₁ ” has finished scanning in all N directions (No at Step S104), the position estimation device 100 determines the beam angle “θ _n. = Θ ₁ ”(step S105), the process of step S102 is executed. In addition, the position estimation apparatus 100 performs the process of step S102, when satisfy | filling the said conditions (step S104 affirmation).

  On the other hand, when recognizing the user ID (Yes at Step S103), the position estimation apparatus 100 measures the received power output from the terminal of the corresponding user ID (Step S106). Then, the position estimation apparatus 100 determines whether or not the measured received power is greater than a predetermined threshold (step S107).

  At this time, if the received power is larger than the predetermined threshold (Yes at Step S107), the position estimation apparatus 100 determines that the terminal is located at a location very close to the LOS and the position estimation apparatus 100, and determines the distance to the user, for example. It is determined as 50 cm or the like (step S112). Note that the distance to the user may be estimated as a distance within 1 m, for example. If the distance is within 1 m, the practical error is small.

On the other hand, when the received power is equal to or less than the predetermined threshold (No at Step S107), the position estimation device 100 outputs a laser with a period T in the direction of θ _n and obtains a time average of the distance to the obstacle. The degree of congestion around the user is measured (step S108). That is, the position estimation apparatus 100 can reduce the processing load and perform position estimation with higher accuracy by measuring the degree of congestion in the environment only around the user. Further, when measuring the degree of congestion, it is preferable to shorten the measurement frequency as the degree of congestion increases.

  Then, the position estimation apparatus 100 records the measured received power and the laser distance average in a predetermined memory (step S109). Subsequently, the position estimation apparatus 100 determines whether or not “distance average data number m <= M” is satisfied (step S110). That is, M indicates the number of data sufficient for calculating the distance to the user.

At this time, if it is determined that there is not enough data for calculating the distance to the user (Yes at Step S110), the position estimation apparatus 100 executes the process at Step S108. On the other hand, when it is determined that there is sufficient data for calculating the distance to the user (No at Step S110), the position estimation device 100 generates a least square approximation function from the relationship between the distance average and the received power, RSS ₁ obtained by extrapolation is obtained (step S111).

Then, the position estimation apparatus 100 approximates with a least square approximation function from the relationship between the received power and the distance held in the measurement value holding unit 111, and based on this function and the obtained RSS ₁ , the corresponding user ID The distance to the measurement target terminal is obtained (step S112).

[Effects of Example 2]
As described above, the position estimation apparatus 100 measures the degree of congestion by measuring the distance of obstacles around the measurement target terminal using a laser distance meter, and obtains the distance to the measurement target terminal. The distance to the measurement target terminal can be estimated with high accuracy.

  Here, the effect by Example 2 is demonstrated using FIG. 10A-FIG. 10D. FIG. 10A is a diagram illustrating a result of position estimation performed by the position estimation apparatus 100 according to the second embodiment. FIG. 10B is a diagram illustrating a frequency distribution of distance calculation errors according to the second embodiment. FIG. 10C is a diagram illustrating a position estimation result according to the conventional technique. FIG. 10D is a diagram showing a frequency distribution of distance calculation errors according to the related art. In FIG. 10A and FIG. 10C, the position estimation results are indicated by “x” marks.

  For example, as illustrated in FIG. 10A, the position estimation apparatus 100 performs position estimation by measuring a distance to an obstacle located only around the “circle” indicating the measurement target terminal a predetermined number of times. As a result, the position estimation apparatus 100 can obtain the result of position estimation at a relatively small distance from the measurement target terminal, as indicated by “x” in FIG. 10A. In short, as shown in FIG. 10B, the position estimation apparatus 100 can relatively reduce the error in distance calculation. In FIG. 10B, the vertical axis indicates the frequency, and the horizontal axis indicates the frequency distribution of errors.

  Further, for example, as shown in FIG. 10C, in the position estimation according to the conventional technique, the estimation error becomes large because it cannot cope with the change of the propagation state, and as a result of the position estimation at a position far from the “circle” indicating the measurement target terminal. Is distributed. In short, in the prior art, as shown in FIG. 10D, the error in distance calculation is relatively large. That is, the position estimation apparatus 100 can estimate the position of the object with higher accuracy compared to the conventional technique in which the estimation error increases due to the propagation parameter sequentially changing according to the crowded state.

  By the way, although the case where the laser distance meter is used in the measurement of the degree of congestion has been described in the second embodiment, a non-contact thermometer can also be used. In the third embodiment, a case where a non-contact thermometer is used for measuring the degree of congestion will be described. In the following, a case where an infrared thermometer is used as an example of a non-contact thermometer will be described.

[Measurement Sensor of Position Estimation Device According to Third Embodiment]
The temperature measurement using the infrared thermometer according to Example 3 will be described with reference to FIG. FIG. 11 is a diagram illustrating a temperature measurement example using the infrared thermometer according to the third embodiment. In FIG. 11, the user having the measurement target terminal is indicated by a shaded circle, and obstacles other than the user are indicated by a black circle. In FIG. 11, the beam output from the beam antenna 101 is indicated by a shaded ellipse, and the infrared range output by the infrared thermometer is indicated by a sector.

For example, as shown in FIG. 11, the congestion degree measurement unit 124 controls the measurement sensor 102 to measure an average temperature in a space within a certain angular width at an angle of the beam direction θ _n of the beam antenna. That is, when using an infrared thermometer, it is suitable for an object having a temperature higher than the ambient temperature, such as a human being, and is proportional to the number of human beings within the temperature measurement range of the infrared thermometer. Since the average temperature of the space changes, the degree of congestion can be obtained.

  Here, the degree of congestion using the infrared thermometer according to Example 3 will be described with reference to FIGS. 12 and 13. FIG. 12 is a diagram illustrating a relationship between temperature and time measured by the congestion degree measurement unit 124 according to the third embodiment. In FIG. 12, the vertical axis represents the average space temperature, and the horizontal axis represents time. FIG. 13 is a diagram illustrating an example of a function obtained by the received power, the degree of congestion, and the least square approximation according to the third embodiment. In FIG. 13, the vertical axis represents received power, and the horizontal axis represents density or spatial average temperature.

For example, as illustrated in FIG. 12, the congestion degree measurement unit 124 measures the temperatures of “obstacle H” to “obstacle M” in a space at a certain time. Also, for example, the black dots shown in FIG. 13 indicate the relationship between the received power obtained by the received power measuring unit 123 and the spatial average temperature measured by the congestion degree measuring unit 124. Moreover, HM shown in FIG. 13 corresponds to HM shown in FIG. Then, the least square approximation function generation unit 125 approximates with the least square approximation function from the relationship between the received power and the degree of congestion, and obtains a solid curve shown in FIG. Subsequently, the least square approximation function generation unit 125 obtains the received power RSS ₁ when the degree of congestion obtained by extrapolating the solid curve is zero. When extrapolating the solid curve, the dotted curve shown in FIG. 13 is obtained.

[Position Estimation Processing According to Third Embodiment]
Next, the position estimation process according to the third embodiment will be described with reference to FIG. FIG. 14 is a flowchart illustrating an example of position estimation processing according to the third embodiment. In the following, the same steps as those in the position estimation process shown in FIG. 9 are denoted by the same reference numerals in FIG.

For example, as illustrated in FIG. 14, the position estimation apparatus 100 uses an infrared thermometer to measure the average temperature of the space around the circumferential direction “θ _n ” with a period T, thereby determining the degree of congestion around the user. Measurement is performed (step S208). Then, the position estimation apparatus 100 records the measured received power and the average temperature indicating the degree of congestion measured by the infrared thermometer in a predetermined memory (step S209).

[Effects of Example 3]
As described above, the position estimation apparatus 100 measures the degree of congestion by measuring the temperature of an obstacle around the measurement target terminal using an infrared thermometer, and obtains the distance to the measurement target terminal. The distance to the measurement target terminal can be estimated with high accuracy.

  Now, the embodiments of the position estimation device disclosed in the present application have been described above. However, the present invention may be implemented in various different forms other than the embodiments described above. Therefore, different embodiments in (1) approximation function, (2) device configuration, and (3) program will be described.

(1) Approximate Function In the above embodiment, the case of extrapolation using an arbitrary approximate function has been described. However, the approximate function may be a curve or a straight line.

(2) Configuration of apparatus In addition, information including the processing procedure, control procedure, specific name, various data, parameters, and the like shown in the above-described document or drawing (for example, stored in “measurement value storage unit 111”) Data etc.) can be changed arbitrarily unless otherwise specified.

  Each component of the illustrated position estimation device 100 and the like is functionally conceptual and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various burdens or usage conditions. Can be integrated. For example, the reception power measurement unit 123 and the congestion degree measurement unit 124 may be integrated as a “measurement unit” that measures the reception power via the beam antenna 101 and measures the degree of congestion via the measurement sensor 102. .

(3) Program In the above embodiment, the case where various types of processing are realized by hardware logic has been described. However, it may be realized by executing a program prepared in advance by a computer. Therefore, in the following, an example of a computer that executes a position estimation program having the same function as the position estimation apparatus 1 shown in the above embodiment will be described with reference to FIG. FIG. 15 is a diagram illustrating an example of a computer that executes a position estimation program.

  As shown in FIG. 15, the computer 11 as the position estimation device 1 includes an HDD 13, a CPU 14, a ROM 15, a RAM 16, and the like connected by a bus 18.

  The ROM 15 has a position estimation program that exhibits the same function as the position estimation apparatus 1 shown in the above embodiment, that is, as shown in FIG. 15, a measurement program 15a, a received power calculation program 15b, and a distance calculation program 15c. Are stored in advance. Note that these programs 15a to 15c may be appropriately integrated or distributed in the same manner as each component of the position estimation apparatus 1 shown in FIG.

  Then, the CPU 14 reads these programs 15a to 15c from the ROM 15 and executes them. Thereby, as shown in FIG. 15, the programs 15a to 15c function as a measurement process 14a, a received power calculation process 14b, and a distance calculation process 14c. The processes 14a to 14c correspond to the measurement unit 3, the received power calculation unit 4, and the distance calculation unit 5 illustrated in FIG. Then, the CPU 14 executes a position estimation program based on data (for example, measured value data) recorded in the RAM 16.

  Note that the programs 15a to 15c are not necessarily stored in the ROM 15 from the beginning. For example, each program may be stored in a “portable physical medium” such as a flexible disk (FD), a CD-ROM, a DVD disk, a magneto-optical disk, or an IC card inserted into the computer 11. Further, for example, each program may be stored in a “fixed physical medium” such as an HDD provided inside or outside the computer 11. Further, for example, each program may be stored in “another computer (or server)” connected to the computer 11 through a public line, the Internet, a LAN, a WAN, or the like. Then, the computer 11 may read and execute each program from now on.

DESCRIPTION OF SYMBOLS 100 Position estimation apparatus 101 Beam antenna 102 Measurement sensor 111 Measurement value holding part 121 Sensor switching part 122 User ID recognition part 123 Reception power measurement part 124 Congestion degree measurement part 125 Least square approximation function generation part 126 Position estimation part

Claims (6)

A measured value holding unit that holds the received power of the terminal measured in a state where there is no obstacle and the distance between the own device and the terminal is known, and the distance between the own device and the terminal;
A measurement unit that measures the received power of the measurement target terminal that is the measurement target and the degree of congestion that is the density of obstacles in the environment of the measurement target terminal;
Approximating with an arbitrary function from the relationship between the received power measured by the measuring unit and the degree of congestion, and calculating received power when there is no degree of congestion obtained by extrapolating the approximated function And
Approximate using an arbitrary function from the relationship between the received power and distance held in the measurement value holding unit, and based on the approximated function and the received power obtained by the received power calculating unit, have a distance calculation unit for determining the distance between the measurement target terminal,
The measuring unit is
Measuring the average temperature in the space, the position estimation device according to claim Rukoto seek the congestion degree from the measured average temperature.   The position estimation apparatus according to claim 1, wherein the measurement unit measures received power of the measurement target terminal and a degree of congestion in a surrounding environment of the measurement target terminal.   The said measurement part measures the degree of congestion in the environment of the said measuring object terminal by measuring the temperature of the obstruction per unit time using a non-contact thermometer. The position estimation apparatus described in 1. The position estimation apparatus according to claim 3, wherein the measurement unit changes a measurement cycle in accordance with the degree of congestion. A measurement procedure for measuring the received power of the measurement target terminal that is the measurement target and the degree of congestion that is the density of obstacles in the environment of the measurement target terminal;
Approximating with an arbitrary function from the relationship between the received power measured by the measurement procedure and the degree of congestion, and calculating received power when there is no congestion degree obtained by extrapolating the approximated function Procedure and
A measured value holding unit that holds the received power of the terminal measured in a state where there is no obstacle and the distance between the position estimating device and the terminal is known, and the distance between the position estimating device and the terminal From the relationship between the stored received power and distance, approximate using an arbitrary function, and based on the approximated function and the received power obtained by the received power calculation procedure, the position estimation device and the measurement object Let the computer execute the distance calculation procedure to find the distance between the terminals ,
In the measurement procedure,
Measuring the average temperature in the space, a position estimation program characterized Rukoto from the measured average temperature to execute the process of obtaining the congestion degree to the computer. A measurement step of measuring the received power of the measurement target terminal that is the measurement target and the degree of congestion that is the density of obstacles in the environment of the measurement target terminal;
A first approximation step for approximating using an arbitrary function from the relationship between the received power and the degree of congestion measured in the measurement step;
A received power calculation step for obtaining received power when there is no degree of congestion obtained by extrapolating the function approximated by the approximating step;
A measured value holding unit that holds the received power of the terminal measured in a state where there is no obstacle and the distance between the position estimating device and the terminal is known, and the distance between the position estimating device and the terminal A second approximation step for approximating using an arbitrary function from the relationship between the received power and the distance held;
Based on the received power obtained by the received power calculation step as a function approximated by the second approximate step, seen including a distance calculation step of obtaining a distance between the position estimation device and the measurement target terminal,
In the measuring step,
A position estimation method characterized by measuring an average temperature in a space and obtaining the degree of congestion from the measured average temperature .

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