JP2011058928A - System, device, method and program for estimating position - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To estimate a position of a mobile station with high precision even in an NLOS state or in an environment where a direct wave and a reflected wave are mixedly received. <P>SOLUTION: The position estimating system 10 for estimating a position of a mobile station based on predetermined signals obtained by one-way or two-way communication between a first base station 201 to a fourth base station 204 and the mobile station 100 includes: a distance measuring part 310 for measuring, as a first distance, a distance between each of the plurality of the base stations and the mobile station for each base station based on the obtained predetermined signals; an error estimating part 320 for estimating a bias amount indicating an error amount contained in the first distance between one of the base stations and the mobile station measured by the distance measuring part 310 this time by using a bias amount estimated to be contained in the first distance between the other plurality of the base stations among the plurality of the base stations and the mobile station at the previous time or prior to the previous time; and a position estimating part 340 for estimating the position of the mobile station by using the first distance and the bias amount estimated this time. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a position estimation system, a position estimation apparatus, a position estimation method, and a program. More specifically, the present invention relates to a position estimation system, a position estimation device, and a position estimation method for performing communication between a mobile station and a plurality of base stations and estimating the position of the mobile station based on a predetermined signal as a result of the communication. And the program.

  Conventionally, a positioning system has been proposed in which a mobile station communicates with a plurality of base stations, and the position of the mobile station is estimated on the basis of a radio signal or a transmission / reception time as a communication result. For example, Patent Documents 1 to 3 propose systems for transmitting and receiving radio signals between a plurality of radio base stations and a mobile station and estimating the position of the mobile station.

  Some wireless signals use radio waves, sound waves, light, magnetism, and the like. The major ones of the methods for obtaining the position using them are roughly classified into the RSSI (Received Signal Strength Indicator) method (refer to Patent Document 1) using the signal reception strength, and the TOA (Time Of Arrival) using the signal propagation time. ) Method (refer to Patent Document 2), TDOA (Time Difference Of Arrival) method using a signal propagation time difference, and AOA (Angle Of Arrival) method (refer to Patent Document 3) using a signal reception direction.

  As shown in Patent Document 1, the RSSI method is a method of estimating a distance from a signal receiving intensity and then estimating a position by triangulation. This method is characterized in that it is difficult to estimate the distance with high accuracy, but it does not require strict and high-accuracy time management and can be easily built into various devices. Since it is difficult to estimate the distance from the received intensity, some positions are estimated by learning and discriminating patterns of multiple received signals, but this cannot be estimated unless there is a learned area nearby. There is a problem.

  The TOA method is a method of measuring a distance from a signal propagation time and estimating the position by triangulation from there. For example, let t be the signal propagation time when a signal is transmitted from the mobile station to the base station (when the communication direction is reversed or there are two-way communication), and the signal propagation speed is c. The distance l between the base station and the mobile station can be obtained by l = c × t. In the case of a radio signal as an example of a radio signal, the propagation speed of the radio wave in the air is generally constant (approximately 300,000 km / sec), so that stable position accuracy can be easily realized if the clock accuracy is sufficiently high. . For example, when all the clocks of the mobile station and the base station are synchronized, the propagation time t can be measured by one communication. There is another method for obtaining the distance without synchronization, but in that case, the radio wave transmitted from the mobile station arrives at the base station, and it is necessary to detect the radio wave received from the base station at the mobile station. The processing load increases.

  For example, in the TWR (Two Way Ranging) method, which is a ranging method used in the TOA method, a signal is transmitted from the mobile station to the base station, and the base station that has received the signal immediately returns a response to the mobile station. Is a one-way propagation by subtracting the processing time required for loopback at the base station and dividing by 2 from the round-trip propagation time from when the station sends the signal to when it receives the signal from the base station. You can ask for time. In any case, a high-accuracy internal clock is necessary to measure the signal propagation time. For example, when radio waves are used, a distance error of about 30 cm occurs with a time error of about 1 ns.

  The TDOA method is based on the propagation time of the signal as in the TOA method, but without the distance between the base station and the mobile station being measured, the signals transmitted from the mobile station by multicast transmission are simultaneously received by a plurality of base stations, The position is obtained based on the reception time difference. The reception time difference between the signals received by the two base stations is a distance difference seen from the mobile station when multiplied by the signal propagation speed. Since a position where the same distance difference can be generated from two base stations draws a hyperbola, when signals are simultaneously received by three or more base stations, a plurality of hyperbolas are obtained, and the positions are determined by obtaining the intersections thereof. . Compared with the TOA method, this method does not require the mobile station to receive a signal, and the number of signal transmissions required for one positioning is small (usually, the position is determined by one signal transmission from the mobile station). The time must be synchronized precisely between base stations, and there is always an error in the clock built in the base station, so time synchronization is performed according to the accuracy of the clock. There is a need.

  The AOA method is a method of performing triangulation based on the arrival angle of signals when a plurality of base stations receive signals from mobile stations. The arrival angle of the signal can be estimated by using, for example, an array antenna in the case of radio waves, a microphone array in the case of sound waves, and using a MUSIC (Multiple Signal Classification) method. Since a reception time difference between antennas (microphones) that are very close to each other is used, it is difficult to sample individual received signals with very high accuracy.

  As described above, each method has advantages and disadvantages in various situations, and there is no method that is always the best in all cases. In particular, as a common problem of the systems using these radio signals, there is an influence of reflected waves.

For example, Patent Document 2 proposes a method for reducing the influence of reflected waves in a system that estimates the position using the TOA method. Usually, there is a line of sight (LOS) between the base station and the mobile station, and when communication is performed by a direct wave passing through a straight line (D _{1 to} D _{4 in} FIG. 1), a straight line is used. It is possible to determine the distance. However, in reality, reflection may occur due to the structure Ob or the like along the route, and when a distance is measured using such a reflected wave, a distance longer than the linear distance (D ₁ ′ in FIG. 1) is obtained. It will be. This is a path through which a direct wave connecting the base station and the mobile station in the shortest path connects each other with a straight line, and all other paths through which reflected waves pass are longer than the line D ₁ ′> D ₁ This is because However, by using this relationship in reverse, it is possible to select a route that is as close to a straight path as possible. For example, in the case of a composite wave in which a direct wave and a reflected wave are mixed in one communication, the component that arrives first is the component due to the direct wave, and if the propagation time can be obtained from this component, the linear distance Can be calculated. In addition, for example, when the signal propagation time can be measured multiple times, and the measurement value by the reflected wave and the direct wave is mixed, the measurement result by the direct wave can be selected by selecting the minimum measurement value. Based on this, a linear distance can be obtained. In addition, the process of selecting this minimum value is to select the reflected wave with the smallest difference compared to the direct wave, even if there is no measurement result of the direct wave and all are based on the reflected wave. A value close to a linear distance that reduces measurement errors can be selected. If the reception quality of communication is used together, poor quality communication such as multiple reflected waves can be eliminated, and it may be possible to select the one closer to the direct wave. When measurement is performed continuously over a long period of time, a more likely position can be calculated by calculating an average moving speed viewed from the base station of the mobile station.

  Patent Document 3 discloses a technique for increasing the position accuracy by combining the TDOA method and the AOA method. In the AOA scheme, when the angle resolution is constant, the position resolution decreases as the distance between the base station and the mobile station increases. On the other hand, when the distance from the base station is sufficiently close, it has high position resolution. Due to this feature, the base station with the earliest signal reception time is the base station closest to the mobile station, and the position resolution is high, and high weighting is performed. In this way, the most probable position is estimated by changing the weight according to the time and taking the weighted average. Further, Patent Document 3 proposes a method of measuring a plausible position by performing TDOA positioning in order to obtain a reception time and taking a weighted average by weighting them.

JP 2009-85780 A JP 2001-275148 A JP 2007-13500 A

  However, in the above method, for example, there is no line of sight between the base station and the mobile station (such a state is hereinafter referred to as NLOS (Non Line of Light)), and the direct wave does not reach and propagates only by the reflected wave. It is very difficult to estimate the position correctly when a path is constructed or when direct wave measurement cannot be performed sufficiently.

  For example, in the method of Patent Document 2, even if the NLOS state is present, it is assumed that the NLOS state is temporarily canceled due to the movement of the mobile station or the environment changes with time, and a direct wave arrives. is doing. For example, when the mobile station is continuously moving on the road outdoors and is temporarily in the NLOS state due to the influence of buildings such as buildings, the LOS state (Line of light: outlook There are many cases where distance measurement by direct waves is possible in the long term. In such a case, the position can be estimated correctly to some extent even in Document 2. However, for example, when position detection is performed on a person or object in an indoor environment such as an office space, the detection target often does not move continuously when the NLOS state is caused by a structure such as an indoor wall or shelf. Therefore, there is a problem that the NLOS state is not easily resolved. The method of Patent Document 2 cannot cope with such a problem. For example, in the case of radio waves, direct waves and reflected waves are mixedly mixed in environments where there are wall surfaces that reflect radio waves well, such as indoors that are not anechoic chambers. It is often the case that a direct wave is missed by this problem. In such a case, the frequency with which direct waves can be received becomes a problem. When the frequency is low, there is a problem in that position measurement cannot be performed with sufficient accuracy.

  In addition, in the method of Patent Document 3, if a reflected wave is picked up when there is a mobile station near a base station with a high resolution of the AOA method, the incident angle of the signal changes more than when the mobile station is far away. This causes a significant decrease in positional accuracy.

  In view of the above problems, the present invention estimates the position of a mobile station with high accuracy even in the above-described NLOS state or in an environment where a direct wave and a reflected wave are mixedly received. With the goal.

  In order to solve the above problems, according to an aspect of the present invention, based on a predetermined signal acquired by one-way or two-way communication between a plurality of base stations whose positions are specified and a mobile station that is a position estimation target. A position estimation system for estimating a position of the mobile station, wherein each base station measures a distance between each of the plurality of base stations and the mobile station as a first distance based on the acquired predetermined signal A distance measurement unit, and a bias amount indicating an error amount included in the first distance between one base station and the mobile station among the plurality of base stations measured by the distance measurement unit, Or an error estimating unit that estimates using a bias amount estimated to be included in the first distance between the plurality of base stations and the mobile station among the plurality of base stations before the previous time, and The first measured by the distance measuring unit Distance, and the position estimation system and a position estimating section for estimating the position of the mobile station using the current estimated bias amount by the error estimation unit is provided.

  The distance measuring unit measures a propagation time of a signal between each base station and the mobile station from the predetermined signal, and multiplies the measured propagation time by a given propagation speed to obtain the first distance. Each may be calculated.

  The error estimation unit estimates a density distribution of a plurality of state vectors for estimating a probable distance between each base station and the mobile station based on the first distance, and the density distribution of the estimated state vectors The second distance may be calculated as a probable distance between each of the base stations and the mobile station, and the position estimation unit may estimate the position of the mobile station based on the second distance. The state vector may be a one-dimensional or more vector having elements of the bias amount and the estimated distance that is the second distance. Further, in order to accurately estimate the bias amount and the second distance even when there are a plurality of radio wave propagation paths, the state vector is a two-dimensional or more multidimensional vector having two elements of the bias amount and the estimated distance. Also good.

  The error estimation unit may obtain a bias amount based on the estimated density distribution of the state vector, and calculate the second distance from the obtained bias amount and the first distance.

  When the error estimation unit determines that the density distribution of the state vector has converged by comparing the variance value of the density distribution of the state vector with a given threshold value, The second distance may be calculated from the first distance.

  When the error estimation unit determines that the density distribution of the state vector is not converged by comparing the variance value of the density distribution of the state vector and a given threshold, the first distance is used as it is. The second distance may be used.

  The distance measurement unit acquires the predetermined signal every predetermined time, measures the first distance every predetermined time based on the acquired predetermined signal, and the error estimation unit determines that the first distance is Each time measurement is performed, the state vector density distribution may be updated, and the second distance may be calculated based on the updated state vector density distribution.

  In order to solve the above problem, according to another aspect of the present invention, the position of the local station is based on a predetermined signal acquired by one-way or two-way communication with a plurality of base stations whose positions are specified. A distance measuring unit that measures the distance between each of the plurality of base stations and the own station as a first distance based on the acquired predetermined signal for each base station, and this time, A bias amount indicating an error amount included in the first distance between one base station of the plurality of base stations measured by the distance measurement unit and the own station is set to the previous or previous time. An error estimation unit that estimates using a bias amount estimated to be included in the first distance between the plurality of other base stations and the own station, and the distance measurement unit Current estimation by the first distance and the error estimation unit Using said bias amount mobile station and a position estimating section for estimating the position of the own station is provided.

  In order to solve the above problem, according to another aspect of the present invention, a predetermined acquired by one-way or two-way communication between a plurality of base stations whose positions are specified and a mobile station that is a position estimation target. A position estimation method for estimating a position of the mobile station based on a signal, based on the acquired predetermined signal, for each base station with a distance between each of the plurality of base stations and the mobile station as a first distance And a bias indicating an error amount included in the first distance between one of the plurality of base stations measured in the distance measurement step and the mobile station. An error estimation that estimates the amount using the bias amount estimated to be included in the first distance between the mobile station and a plurality of other base stations of the plurality of base stations before or before the previous time Step and the distance measuring step Position estimating method comprising: a position estimation step of estimating a location of the mobile station using the current estimated bias amount at the calculated first distance and the error estimation step Te is provided.

  In order to solve the above problem, according to another aspect of the present invention, a predetermined acquired by one-way or two-way communication between a plurality of base stations whose positions are specified and a mobile station that is a position estimation target. A program for causing a computer to perform a process of estimating the position of the mobile station based on a signal, based on the acquired predetermined signal, a distance between each of the plurality of base stations and the mobile station is a first A distance measurement process for measuring each base station as a distance, and this time, included in the first distance between one of the plurality of base stations and the mobile station measured by the distance measurement process A bias amount indicating an error amount is used as the bias amount estimated to be included in the first distance between the mobile station and a plurality of other base stations among the plurality of base stations before or before the previous time. Position estimation processing A program for causing a computer to execute a position estimation process for estimating the position of the mobile station using the first distance calculated by the distance measurement process and the bias amount currently estimated by the position estimation process. Is provided.

  As described above, according to the present invention, it is possible to estimate the position of the mobile station with high accuracy even in an NLOS state or in an environment where a direct wave and a reflected wave are mixedly received.

1 is an overall configuration diagram of a position estimation system according to an embodiment of the present invention. It is an internal block diagram of the position estimation apparatus which concerns on the same embodiment. It is the flowchart which showed the estimation process which concerns on the same embodiment. It is a figure for demonstrating the position estimation method which concerns on the embodiment. It is a figure for demonstrating the position estimation method which concerns on the embodiment. It is a figure for demonstrating the position estimation method which concerns on the embodiment. It is the figure which showed notionally the convergence process of the state vector based on the embodiment.

  Exemplary embodiments of the present invention will be described below in detail with reference to the accompanying drawings. In addition, in this specification and drawing, about the component which has the substantially same function structure, duplication description is abbreviate | omitted by attaching | subjecting the same code | symbol.

[Overall configuration of position estimation system]
First, an overall configuration of a position estimation system according to an embodiment of the present invention will be described with reference to FIG. The position estimation system 10 according to the present embodiment includes a mobile station 100, a first base station 201, a second base station 202, a third base station 203, and a fourth base station 204. The position estimation system 10 estimates the position of the mobile station 100. The first base station 201 to the fourth base station 204 have known positions or can acquire the positions at the time of position estimation calculation, and can perform one-way or two-way communication with the mobile station 100. The position estimation system 10 estimates the position of the mobile station 100 based on a predetermined signal acquired by transmission or reception as a result of communication between the first base station 201 to the fourth base station 204 and the mobile station 100. It has become.

  The first base station 201 to the fourth base station 204 are installed in the same manner as, for example, indoor wireless LAN base stations and mobile phone base stations. In addition, the first base station 201 to the fourth base station 204 can be shared as a communication network by adding data to the positioning signal. Further, if there is a means for specifying the positions of the first base station 201 to the fourth base station 204, it is not necessary to fix the base station, and the mobile station 100 may be movable.

  The mobile station 100 can be applied to various forms such as a PC (Personal Computer), a sensor network node, a mobile phone, a PDA (Personal Digital Assistant), and an active tag. Here, an example in which there is one mobile station and four base stations will be described. However, there may be a plurality of mobile stations, and any number of base stations may be used as long as there are two or more base stations. Normally, three or more base stations are required for position estimation by triangulation. However, if there are restrictions related to position (for example, the area where people are present is determined to some extent) in addition to radio waves, the base station Even if there are two stations, the position may be estimated. For example, an area where the distance from two base stations is x meters and y meters, respectively, exists in a ring shape in the space, but there are people on the office floor (for example, a plane 1 m above the floor) or in the office. If an intersection point with a constraint condition such as a movable range is obtained, one point may be obtained. In such a case, position detection is possible even from two stations.

[Internal configuration of position estimation device]
FIG. 2 shows an internal configuration (block) diagram of the position estimation apparatus 300 according to the present embodiment. The position estimation apparatus 300 may be built in the base station or may be built in the mobile station. It may exist separately from the base station or mobile station. In the present embodiment, the position estimation device 300 is built in the base station. The position estimation apparatus 300 includes a distance measurement unit 310, an error estimation unit 320, an error storage unit 330, and a position estimation unit 340.

The distance measuring unit 310 includes a first distance measuring unit 311, a second distance measuring unit 312, a third distance measuring unit 313, and a fourth distance measuring unit 314. The first ranging unit 311 to the fourth ranging unit 314 are configured to transmit the first base station based on a predetermined signal acquired by communication between the mobile station 100 and the first base station 201 to the fourth base station 204. The observation distance between the station 201 to the fourth base station 204 and the mobile station 100 is measured for each base station. That is, the first ranging unit 311 to the fourth ranging unit 314 send communication results (corresponding to the predetermined signal) from the first base station 201 to the fourth base station 204 to the mobile station 100. Obtaining and outputting the observation distance between the mobile station 100 and each base station. For example, the first distance measuring unit 311 calculates the observation distance (D ₁ ′ in FIG. 1) from the communication result between the mobile station 100 and the first base station 201. Similarly, the second distance measuring means 302, the third distance measuring unit 313, and the fourth distance measuring unit 314 calculate observation distances D ₂ , D ₃ , and D ₄ from the communication result with the mobile station 100.

  Note that the communication results used to determine the distance in each distance measuring unit do not necessarily have to be obtained from the base station, and after collecting on the mobile station side, a plurality of base stations can be collectively delivered to a specific base station. Alternatively, it may be passed to the distance measuring unit via another communication path. Any communication path or protocol can be used here. Also, when there are multiple mobile stations, distance collection and positioning calculation are performed for each mobile station. For mobile stations where the error is not sufficiently converged, a mobile station in which the error has converged sufficiently in the vicinity. It is also possible to take a method such as diverting the error information.

The first ranging unit 311 to the fourth ranging unit 314 calculate the signal propagation time between the first base station 201 to the fourth base station 204 and the mobile station 100 from the predetermined signal (communication result). Each observation distance is calculated by measuring and multiplying the measured propagation time by a given propagation velocity. The calculated observation distances between the first base station 201 to the fourth base station 204 and the mobile station 100 are the observation distances D ₁ , D ₂ , D ₃ , D ₄ when there are no obstacles. Become. However, in the present embodiment, reflection occurs due to the structure Ob or the like along the path, and the distance is measured using such a reflected wave, so that an observation distance D ₁ ′ longer than the linear distance is calculated.

  Note that the first distance measuring unit 311 to the fourth distance measuring unit 314 repeatedly acquire the predetermined signal every predetermined time and measure the observation distance every predetermined time based on the acquired predetermined signal. . The observation distance between each base station and mobile station corresponds to the first distance measured by the distance measurement unit 310.

  The error estimator 320 includes a first error estimator 321, a second error estimator 322, a third error estimator 323, and a fourth error estimator 324. The first error estimation unit 321 to the fourth error estimation unit 324 are distributions of errors estimated from the observation distances measured by the first distance measurement unit 311 to the fourth distance measurement unit 314, past history, and the like. Predict the observation error and estimate the distance.

  Specifically, the first error estimation unit 321 to the fourth error estimation unit 324 are the first base stations 201 to 201 measured by the first distance measurement unit 311 to the fourth distance measurement unit 314 this time. The bias amount indicating the error amount included in the observation distance between one base station of the fourth base stations 204 and the mobile station 100 is set to the first base station 201 to the fourth base station before or before the previous time. The estimation is performed using the bias amount estimated to be included in the observation distance between the plurality of other base stations 204 and the mobile station 100.

The bias amount b is an error value (elongation amount) included in the observation distance with respect to the linear distance D ₁ as shown in the reflection path D ₁ ′ of FIG. For example, if there is an obstacle Ob that does not transmit radio waves between the first base station 201 and the mobile station 100, the radio waves, for example, reflect the wall of the building Br and reach the base station. The observation distance at this time is D ₁ ′, which is longer than the true distance between the first base station 201 and the mobile station 100 by the bias amount b.

  The first error estimator 321 to the fourth error estimator 324 obtain a bias amount based on the density distribution of the state vector, and calculate the error amount between each base station and the mobile station from the obtained bias amount and the observation distance. A probable distance between each removed base station and the mobile station is calculated. More specifically, the first error estimator 321 to the fourth error estimator 324 are density distributions of a plurality of state vectors for estimating a probable distance between each base station and mobile station based on the observation distance. And a probable distance between each base station and the mobile station is calculated based on the estimated density distribution of the state vector. The distance obtained by removing the error amount between each base station and the mobile station from the first distance (probably between each base station and the mobile station) corresponds to the second distance.

  The first error estimator 321 to the fourth error estimator 324 determine that the density distribution of the state vector has converged by comparing the variance value of the density distribution of the state vector with a given threshold value. In this case, the second distance is calculated from the obtained bias amount and the observation distance. On the other hand, the first error estimator 321 to the fourth error estimator 324 compare the distribution value of the density distribution of the state vector with a given threshold value, so that the density distribution of the state vector has not converged. If it is determined, the observation distance is set as the second distance as it is.

  Each time the first distance is measured, the first error estimation unit 321 to the fourth error estimation unit 324 update the state vector density distribution by the above method, and the first error estimation unit 321 to the fourth error estimation unit 324 update the state vector density distribution based on the updated state vector density distribution. The distance of 2 is calculated.

  The error storage unit 330 includes a first error storage unit 331, a second error storage unit 332, a third error storage unit 333, and a fourth error storage unit 334. The first error storage unit 331 to the fourth error storage unit 334 store estimated values of past errors such as bias amounts and state vectors for estimating errors.

  Therefore, this time, the bias amount included in the observation distance between the one base station and the mobile station measured by any one of the first distance measurement unit 311 to the fourth distance measurement unit 314 is the first error storage unit. 331 to the fourth error storage unit 334 stored in the previous time or estimated using the bias amount estimated to be included in the observation distance between the plurality of other base stations and the mobile station before the previous time; Become.

  The position estimation unit 340 calculates the position of the mobile station 100 in consideration of errors estimated by the first error estimation unit 321 to the fourth error estimation unit 324. More specifically, the position estimation unit 340 includes the observation distances between the base stations and the mobile stations calculated by the first ranging unit 311 to the fourth ranging unit 314, and the first error estimation units 321 to 321. The position of the mobile station 100 is estimated using the bias amount estimated this time by any one of the four error estimation units 324. When estimating the position of the mobile station 100, the calculated second distance may be used.

  A command to each part of the position estimation apparatus 300 is executed by a dedicated control device or a CPU (not shown) that executes a program. Each program and the state vector stored in the error storage unit 330 are stored in advance in a ROM or non-volatile memory (not shown). The CPU reads out and executes each program from these memories, thereby realizing the functions of the distance measuring unit 310, the error estimating unit 320, and the position estimating unit 340.

[Operation of position estimation device]
Next, an operation of estimating an error in the position estimation apparatus 300 according to the present embodiment will be described with reference to a flowchart illustrating the estimation process in FIG. Here, the most probable relationship between the first base station 201 and the mobile station 100 using the error (bias amount) estimated by the first error estimating unit 321 from the observation distance measured by the first distance measuring unit 311. The estimated distance is estimated, and the position of the mobile station 100 is estimated.

  The estimation process is executed in the order of a state vector initialization step (S301), a distance measurement step (S302), an error estimation step (likelihood calculation step S303, bias amount estimation step S304), and an output step (S305).

(State vector initialization step)
In the state vector initialization step S301, it is possible to give a pseudo-random value distributed almost uniformly in a range of values that the state vector can take as an initial state, a random number according to a Gaussian distribution with an average a, and a variance σ ² . For example, an example of the initial state of the state vector is shown in FIG. This state vector is stored in the first error storage unit 331.

  For example, the density distribution of the state vector is obtained by using a large number of state vectors shown as particles in FIGS. 7A to 7G, and using the current error from the prediction from the previous error state and the current observation distance. Used to estimate the state. An error (bias amount) estimated to be included in the observation distance between the first base station 201 and the mobile station 100 is expressed by a density distribution of one state vector. The error estimated to be included in the observation distance between the second base station 202 and the mobile station 100 is also expressed by the density distribution of another one state vector. Therefore, errors estimated to be included in the four observation distances between the four base stations and the mobile station are represented by four state vectors, respectively. As will be described later, the error (bias amount) estimated to be included in the observation distance between any one of the base stations and the mobile station this time is the base station of the three stations other than any of the base stations and the mobile station. Are estimated using three state vectors for indicating an error estimated to be included in the observation distance. Specific usage of the state vector will be described later.

(Distance measurement step)
In the distance measurement step S301, the distance measurement unit 310 uses the first base station 201 based on a predetermined signal acquired by transmission or reception between the first base station 201 to the fourth base station 204 and the mobile station 100. The observation distance between the fourth base station 204 and the mobile station 100 is measured for each base station. Below, an example is given and demonstrated about the measuring method of observation distance.

  As described above, the first base station 201 to the fourth base station 204 communicate with the mobile station 100, respectively. The first distance measuring unit 311 to the fourth distance measuring unit 314 calculate the observation distance from the communication result between each of the first base station 201 to the fourth base station 204 and the mobile station 100.

  The first ranging unit 311 obtains the observation distance between the first base station 201 and the mobile station 100 from the communication result between the first base station 201 and the mobile station 100. In the case of the TOA system, for example, an observation distance is obtained by transmitting / receiving a signal between a base station and a mobile station and multiplying the time required for signal propagation by the signal propagation speed.

For example, the transmission time of the signal from the first base station 201 is TS _1. After the signal arrives at the mobile station 100 from the first base station 201, the signal is transmitted from the mobile station 100 and the signal is transmitted to the first base station 201. The first distance measurement unit 311 assumes that the time received by the base station 201 is TR ₁ , the time from when a signal is received by the mobile station 100 to the time when the signal is transmitted is t _m , and the signal propagation speed is c. the observation distance _{D 1} of the mobile station 100 and the first base station 201, determined as follows.

When the mobile station 100 and the first base station 201 to the fourth base station 204 are performing time synchronization, the time when the mobile station 100 transmits a signal is TM ₁ , and the first base station 201 receives the signal. Assuming that the time is TB ₁ , the observation distance D ₁ between the first base station 201 and the mobile station 100 can also be obtained as follows.

(Observation error and error estimation)
The observation distances D _{2 to} D ₄ between the mobile station 100 and the second base station 202 to the fourth base station 204 can be similarly obtained by the second distance measuring unit 312 to the fourth distance measuring unit 314. I can do it. In the case of the RSSI system, for example, the observation distance can be obtained from the relationship between the radio field intensity and the distance by obtaining the radio field intensity when the base station and the mobile station communicate.

The observation distances D _{1 to} D ₄ obtained by the first distance measurement unit 311 to the fourth distance measurement unit 314 are distances as observation values, and are not actual true distances but observation errors based on various factors. Includes e _{1 to} e ₄ . When the true distance is G _{1 to} G ₄ , the following relationship is established.

ただし、ｉ＝１〜４

However, i = 1 to 4

For example, in the case of the TOA system, in addition to the clock resolution when measuring the signal propagation time, fluctuations and errors of the clock itself, up to the part that detects the antenna (such as a microphone in the case of sound waves) and gives the reception time There may be an error factor in the propagation time, detection processing time, etc. in the transmission path. In the case of the TWR method, factors such as an estimation error in processing time necessary for communication return may occur. In addition, because of the use of radio waves and sound waves, the effects of reflected waves due to wall reflections, multiple reflections and direct wave synthesis, direct wave blockage and attenuation due to walls, etc. can occur, Misdetection and false detection due to environmental noise superimposition also occur. Among these, for the purpose of measuring the position and distance, the influence of the reflected wave is very large, and if the reflected wave is caught, it is difficult to estimate the reflected path, so that the direct wave propagation path (for example, D _{1 in} FIG. 1). ), The propagation path of the reflected wave extending further (for example, D ₁ ′ in FIG. 1) is mistakenly observed as the direct wave path, resulting in a large observation error.

Due to the influence of the reflected wave, the reflected wave is always captured in the NLOS environment, and a very large bias error with a fixed amount can occur. Further, although the propagation time of the propagation path from the antenna to the detection circuit is small in amount due to the change of the antenna and the influence of the cable length, a bias error may occur. Such bias specific errors, since the somewhat fixed components in the observation error is defined as the amount of bias b _i, consider the synthesis of this and the true measurement noise e _'i the observation error e _i be able to.

Considering compensation when a very large amount of bias occurs in the NLOS environment, the relationship between the amount of bias and the observation error may be b _i >> e ′ _i . In such a case, the observation error and the bias The relationship of quantity can also be regarded as the following equation.

In addition, errors such as errors due to clock resolution and thermal noise on hardware may occur to some extent, such as random noise and white noise, which can be classified as e ′ _i . As described above, an observation error is generated by combining errors due to a plurality of factors.

As described above, when a very large bias error occurs in the NLOS environment, the bias amount b _i >> e ′ _i may be obtained. In such a case, if the bias amount can be estimated, the distance accuracy or Position accuracy can be improved dramatically. For example, in a TOA / TDOA type position detection device using IR-UWB (Impulse Radio Ultra wideband) radio, it is generally said that the detection accuracy of distance and position is about 50 cm in an LOS environment where the influence of reflected waves is small. . In an NLOS environment, if the base station is set at an interval of 20 m, a bias amount of several m to several tens of m may occur in the observation distance (first distance) between the base station and the mobile station. The position detection accuracy deteriorates due to the amount. Usually, when position detection is performed, a plurality of base stations whose positions are known are used, and the position is estimated from communication results between the mobile station and the plurality of base stations. Further, based on a preset condition, the position estimation is continued by a sequential method such as performing a plurality of times of communication with the passage of time and estimating the position associated therewith and continuing to update the position of the mobile station. For example, an environment in which communication between the base station and the mobile station is continuously performed at intervals of 1 second, and the position of the mobile station is updated every time a communication result is obtained at intervals of 1 second, or communication may fail due to poor radio wave conditions. Then, a method is used in which communication is continuously attempted and the position is updated each time communication is successful. Alternatively, a method may be used in which a vibration detection sensor or the like is attached to the mobile station, communication is performed each time vibration generated during movement is detected, and the position of the mobile station is updated.
For example, if it is assumed that the distances between the plurality of other base stations and the mobile station can be correctly estimated, each base station can be determined from the observation distance (first distance) obtained from the communication result with the plurality of base stations. The amount of bias due to the linear distance between the mobile station and NLOS can be estimated. In general, it is impossible to determine whether a base station is in the LOS state or the NLOS state, but the bias amount included in the observation distance (first distance) of one base station is between the other base station and the mobile station. The estimated distance can be roughly estimated by using the estimated distance based on the estimated bias amount. Although it is difficult to estimate the correct amount of bias with a single estimation process without prior knowledge, each time an observation distance (first distance) is obtained multiple times in succession, it is possible to The bias amount estimated for each base station can be converged to a more accurate bias amount as time passes, and as a result, the final distance and position accuracy can be made closer to the LOS environment. Therefore, the bias amount is estimated in the following error estimation step.

(Error estimation step)
In the error estimation step S303, the error estimation unit 320 sets the observation distance between one base station of the first base station 201 to the fourth base station 204 and the mobile station 100 that has been measured by the distance measurement step this time. The included error amount is estimated as a bias amount. For example, the amount of bias included in the observation distance between the first base station 201 and the mobile station 100 is the second base station 202 to the fourth base station 204 (that is, the first base station 201 before or last time). It is estimated using the bias amount estimated to be included in the observation distance between the mobile station 100 and the other base station).

In the first error estimation unit 321 to the fourth error estimation unit 324, the estimated distances g _{1 to} g from the observation distances D _{1 to} D ₄ obtained from the first distance measurement unit 311 to the fourth distance measurement unit 314. ₄ and the estimated bias amounts b _{1 to} b ₄ are estimated. Although the first error estimator 321 is described here, the second error estimator 322 to the fourth error estimator 324 can also estimate the bias amount by the same process.

The first error estimator 321 estimates the bias amount b ₁ using N state vectors to obtain the correction distance G ₁ . As N increases, the possibility that the observation error can be accurately estimated increases. On the other hand, since the processing amount increases in proportion to N, a value in the range of about 10 to several thousand is often used.

N state vectors are defined as the following equation (6).

ただし、ｉ＝１，…，Ｎ Here, t indicates an observation time, t = 0 is an initial state, and t = 1 is a state vector based on an observation value obtained first after the start of observation. An example of one state vector can be expressed as follows, for example.

However, i = 1, ..., N

As described above, in the state vector initialization step (S301), as an initial state, a pseudo-random value distributed almost uniformly in a range of possible values, a random number according to a Gaussian distribution with an average a, and a variance σ ² , etc. The vector was given (see FIG. 7A). This state vector is stored in the first error storage unit 331.

  In the error estimation step, the state vector at time (t + 1) is predicted from the state vector distribution at time t held in the first error storage unit 331. The state vector at the predicted time (t + 1) is defined as follows (see FIGS. 7B and 7E).

Further, P _{t, xyz} (g, b) can be expressed by the following equation, for example.

As described above, step S302 to step S305 in the estimation process of FIG. 3 are executed every predetermined time. That is, after the position estimation process is executed at time t, when a new observation distance D _{t + 1,1} is obtained at the next time t + 1, the process returns to the distance measurement step S302, and the processes of steps S302 to S305 are repeated.

(Position estimation step)
The position estimation unit 340 estimates the position of the mobile station 100 using the plurality of observation distances calculated by the distance measurement unit 310 and the bias amount currently estimated by the error estimation unit 320.

  Therefore, the position estimation unit 340, for example, combines (1,4), (2,4), (3,4), (2) of two stations out of the first base station 201 to the fourth base station 204. , 3), (1, 3), (1, 2), two intersections of distances from each of the two stations (one if one point intersects, otherwise a straight line between the base stations) (1 point obtained by the ratio of the estimated distances from the respective base stations) on the straight line connecting the two points, and the center of gravity of these points may be estimated as the position of the mobile station 100. In addition, the position estimation unit 340 obtains a line segment passing through two intersections of two stations, and sets a position of the intersection of two line segments obtained by the distance from the base station of the third station to the fourth station ( The position of the mobile station may be estimated by referring to FIG. In addition, the position estimation unit 340 replaces the distribution of the estimated distance g included in the state vector of the state probability model corresponding to each base station, which is the probability distribution of the distance from each base station, with a density function. The position with the highest density may be used as the estimated position of the mobile station 100.

  As the position estimation method, an existing method other than the method described above can be used. For example, as described in Japanese Patent Application Laid-Open No. 2009-47556, a method of estimating a position by a TOA (arrival time) method and an RSS (received signal strength) method may be used. In this method, the root mean square of the difference between the estimated distance and the actual distance from the wave source to each coordinate is calculated for each coordinate, and the position is estimated by selecting the coordinate with the smallest mean square root. .

  Further, as described in JP-T-2004-530358, the position may be estimated by combining TOA (distance) and AOA (angle). Further, as described in Japanese Patent Application Laid-Open No. 2008-249419, a method in which a measurement area is divided in advance with a mesh (the periphery of an obstacle is large) and corresponding coordinates are assigned, or Japanese Patent Application Laid-Open No. 2006-3187 is described. It is also possible to use the estimated position estimation method. Furthermore, it is also possible to use the TOA method described in JP-T-2009-515201.

  Usually, the position detection for one mobile station is performed based on the results of communication with a plurality of base stations, so the communication results with some base stations deteriorate in the NLOS state, and the observation distance is an actual straight line. Even when the distance is different from the distance, in most cases, an error distribution including the amount of observation distance extension (bias amount) by NLOS compared to the linear distance can be estimated by using the communication results with other base stations. In addition, even in the observation distance to the same base station, when looking at the long-term distribution, it is very likely that the linear distance can be estimated under the condition that the moving speed is not high. Therefore, it is possible to estimate a bias amount due to a linear distance between each base station and a mobile station, NLOS, or the like, from an observation distance (first distance) obtained from communication results with a plurality of base stations. Thereby, the position of the mobile station can be estimated with high accuracy using the first distance and the bias amount estimated this time.

  As described above, according to the position estimation system 10 according to the present embodiment, resistance to an NLOS environment where there is no line of sight or an environment where reflected waves are likely to be generated can be obtained. In addition, it is not necessary to set in advance whether or not the NLOS environment, and in the case of the NLOS environment, it is not necessary to model and set the characteristics of the propagation path of the NLOS environment in advance, and positioning is possible even when the propagation path is unknown. In addition to being able to follow the environment dynamically, it is possible to detect the position of the environment change with higher accuracy than the conventional method.

  Usually, if a large number of base stations are arranged, the frequency of collecting highly reliable information is probabilistic and the position accuracy is easily improved, but by applying the present invention, the number of installed base stations is not increased. In addition, it is possible to improve the position accuracy and to reduce the installation cost.

  The position estimation system described above can be applied as follows. For example, normally, there may be a plurality of mobile stations. In such a case, the base station can collect data for each mobile station by transmitting a unique ID between the mobile stations. The communication relationship between the base station and the mobile station may be reversed (the mobile station collects the distance from the base station). Furthermore, the position of the base station does not need to be fixed if there is a method for knowing the position.

  In the above embodiment, the operations of the respective units are related to each other, and can be replaced as a series of operations and a series of processes in consideration of the relationship between each other. Thereby, embodiment of a position estimation system and a position estimation apparatus can be made into embodiment of a position estimation method. Further, the embodiment of the position estimation system and the position estimation apparatus can be an embodiment of a program for causing a computer to realize the functions of these.

  Thus, a position estimation method for estimating the position of a mobile station based on a predetermined signal acquired by one-way or two-way communication between a plurality of base stations whose positions are specified and a mobile station that is a position estimation target. , Based on the acquired predetermined signal, a distance measuring step of measuring each base station as a first distance with a distance between each of the plurality of base stations and the mobile station, and this time, measured by the distance measuring step In addition, a bias amount indicating an error amount included in the first distance between one base station of the plurality of base stations and the mobile station is set to be the other of the plurality of base stations before or before the previous time. An error estimation step using a bias amount estimated to be included in the first distance between the plurality of base stations and the mobile station, the first distance calculated by the distance measurement step, and The error It is possible to provide a position estimating method including the position estimation step of estimating a location of the mobile station using the estimated amount of bias current by a constant step.

  In addition, the computer performs processing for estimating the position of the mobile station based on a predetermined signal obtained by one-way or two-way communication between the plurality of base stations whose positions are specified and the mobile station that is the position estimation target. A distance measurement process for measuring, for each base station, a distance between each of the plurality of base stations and the mobile station as a first distance based on the predetermined signal; A bias amount, which is an error value included in the first distance between one of the plurality of base stations measured by the distance measurement processing and the mobile station, is estimated before or before the previous time. In addition, a position estimation process for estimating using a bias amount estimated to be included in the first distance between the plurality of base stations and the mobile station among the plurality of base stations, and the distance measurement process Before calculated A first distance, and a position estimation process for estimating the position of the mobile station using one or two or more of the bias amounts estimated at or before this time by the position estimation process. A program can be provided.

  The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to such examples. It is obvious that a person having ordinary knowledge in the technical field to which the present invention pertains can come up with various changes or modifications within the scope of the technical idea described in the claims. Of course, it is understood that these also belong to the technical scope of the present invention.

  For example, in the above description, the process of estimating the position of the mobile station is not included in the estimation process of FIG. However, the position estimation process of the mobile station may be repeatedly executed by providing a position estimation step after the output step S305 in the estimation process of FIG.

DESCRIPTION OF SYMBOLS 10 Position estimation system 100 Mobile station 201 1st base station 202 2nd base station 203 3rd base station 204 4th base station 310 Distance measurement part 311 1st ranging part 312 2nd ranging part 313 Third distance measuring section 314 Fourth distance measuring section 320 Error estimating section 321 First error estimating section 322 Second error estimating section 323 Third error estimating section 324 Fourth error estimating section 330 Error storage section 331 First error storage unit 332 Second error storage unit 333 Third error storage unit 334 Fourth error storage unit 340 Position estimation unit

Claims (12)

A position estimation system that estimates a position of a mobile station based on a predetermined signal acquired by one-way or two-way communication between a plurality of base stations whose positions are specified and a mobile station that is a position estimation target,
Based on the acquired predetermined signal, a distance measuring unit that measures the distance between each of the plurality of base stations and the mobile station as a first distance for each base station;
This time, a bias amount indicating an error amount included in the first distance between one of the plurality of base stations measured by the distance measuring unit and the mobile station is set to be the previous time or before the previous time. An error estimation unit that estimates using a bias amount estimated to be included in the first distance between the plurality of base stations and the mobile station among the plurality of base stations;
A position estimation system comprising: a position estimation unit configured to estimate the position of the mobile station using the first distance measured by the distance measurement unit and the bias amount currently estimated by the error estimation unit.   The distance measuring unit measures a propagation time of a signal between each base station and the mobile station from the predetermined signal, and multiplies the measured propagation time by a given propagation speed to obtain the first distance. The position estimation system according to claim 1, wherein the position estimation system calculates each. The error estimation unit estimates a density distribution of a plurality of state vectors for estimating a probable distance between each base station and the mobile station based on the first distance, and the density distribution of the estimated state vectors A second distance as a probable distance between each base station and the mobile station based on
The position estimation system according to claim 1, wherein the position estimation unit estimates the position of the mobile station based on the second distance.   The position estimation system according to claim 3, wherein the state vector is a two-dimensional or more multidimensional vector including an estimated bias amount and an estimated distance.   The distance measurement unit sequentially performs a first distance measurement a plurality of times as time passes, and the error estimation unit estimates a bias amount each time the first distance measurement is performed by the distance measurement unit, The position estimation system according to claim 3 or 4, wherein the position estimation unit estimates the position of the moving body every time the bias estimation is performed by the error estimation unit.   The error estimation unit obtains a bias amount based on the estimated density distribution of the state vector, and calculates the second distance from the obtained bias amount and the first distance. Crab position estimation system.   When the error estimation unit determines that the density distribution of the state vector has converged by comparing the variance value of the density distribution of the state vector with a given threshold value, The position estimation system according to claim 6, wherein the second distance is calculated from the first distance.   When the error estimation unit determines that the density distribution of the state vector is not converged by comparing the variance value of the density distribution of the state vector and a given threshold, the first distance is used as it is. The position estimation system according to claim 6, wherein the second distance is set as the second distance. The distance measuring unit acquires the predetermined signal every predetermined time, measures the first distance every predetermined time based on the acquired predetermined signal,
The error estimation unit updates the state vector density distribution each time the first distance is measured, and calculates the second distance based on the updated state vector density distribution. The position estimation system according to claim 1. A position estimation apparatus that estimates a position of a mobile station based on a predetermined signal acquired by one-way or two-way communication between a plurality of base stations whose positions are specified and a mobile station that is a position estimation target,
Based on the acquired predetermined signal, a distance measuring unit that measures the distance between each of the plurality of base stations and the mobile station as a first distance for each base station;
This time, a bias amount indicating an error amount included in the first distance between one of the plurality of base stations measured by the distance measuring unit and the mobile station is set to be the previous time or before the previous time. An error estimation unit that estimates using a bias amount estimated to be included in the first distance between the plurality of base stations and the mobile station among the plurality of base stations;
A position estimation device comprising: a position estimation unit configured to estimate the position of the mobile station using the first distance measured by the distance measurement unit and the bias amount currently estimated by the error estimation unit. A position estimation method for estimating a position of a mobile station based on a predetermined signal acquired by one-way or two-way communication between a plurality of base stations whose positions are specified and a mobile station that is a position estimation target,
Based on the acquired predetermined signal, a distance measuring step for measuring each of the plurality of base stations and the mobile station as a first distance for each base station;
This time, a bias amount indicating an error amount included in the first distance between one of the plurality of base stations measured in the distance measuring step and the mobile station is set to be the previous time or before the previous time. An error estimation step for estimating using a bias amount estimated to be included in the first distance between the plurality of base stations and the mobile station among the plurality of base stations;
A position estimation method comprising: a position estimation step of estimating the position of the mobile station using the first distance calculated in the distance measurement step and the bias amount currently estimated in the error estimation step. To cause a computer to perform processing for estimating a position of a mobile station based on a predetermined signal obtained by one-way or two-way communication between a plurality of base stations whose positions are specified and a mobile station that is a position estimation target A program,
Based on the predetermined signal, distance measurement processing that measures the distance between each of the plurality of base stations and the mobile station as a first distance for each base station;
This time, a bias amount that is an error value included in the first distance between one of the plurality of base stations measured by the distance measurement process and the mobile station is set to be the previous time or before the previous time. A position estimation process for estimating using a bias amount estimated to be included in the first distance between the plurality of other base stations and the mobile station among the plurality of estimated base stations;
Position estimation processing for estimating the position of the mobile station using the first distance calculated by the distance measurement processing and one or more bias amounts estimated this time or before this time by the position estimation processing. And a program for causing a computer to execute.

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