JP2011163861A - Portable terminal for determining travel direction of walker using geomagnetic sensor and acceleration sensor, program and method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a portable terminal held in a nearly fixed posture of the terminal, and correctly determining the travel direction of a walker using an acceleration sensor and a geomagnetic sensor. <P>SOLUTION: The portable terminal comprises: a vertical direction acceleration calculating means for calculating vertical direction acceleration from acceleration data; a walk timing detecting means for detecting walk timing as a local maximal point of vertical direction/upward acceleration; a horizontal direction acceleration calculating means for calculating horizontal direction acceleration orthogonal to the vertical direction acceleration by using the acceleration data and geomagnetic data; an acceleration-per-step segmenting means for segmenting the horizontal direction acceleration per step based on the walk timing; a direction-per-step calculating means for calculating the direction per step from the horizontal direction acceleration per step by using a principal component analysis; a direction-per-step classifying means for alternately classifying the direction per step into an odd step and an even step; and a travel direction calculating means for calculating the travel direction as the direction of a bisector between the direction per step of the odd step and the direction per step of the even step. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a technique for determining a traveling direction of a pedestrian using a geomagnetic sensor and an acceleration sensor. In particular, the present invention relates to an autonomous navigation technique for deriving a traveling direction in real time.

  Conventionally, there is an autonomous navigation technique that derives a traveling direction and a current position in real time using an acceleration sensor and a direction sensor. Autonomous navigation technology is combined with GPS (Global Positioning System) technology and is mainly used for a car navigation system. The car navigation system displays, on a display, an accurate traveling direction and current position, and a travel route guide to a destination for a driver of a car.

  The car navigation system corrects the current position information measured by the GPS by an autonomous navigation technique such as a vehicle speed pulse or a gyro. Further, the road map information is read out as necessary, and the traveling direction and the current position are corrected so that the current travel route coincides with the road (refer to map matching technology based on a projection method, for example, Patent Document 1). As a result, it is possible to prevent the current position from being a position not on the road due to a sensor error.

  On the other hand, there is a system in which such navigation technology is applied to a portable terminal possessed by a pedestrian. Specifically, a cumulative current position from the starting point is derived using the detected “number of steps” of the pedestrian and the “step length” of the pedestrian (see, for example, Patent Document 2). When the autonomous navigation technology is applied to a pedestrian, acceleration components other than horizontal movement are also detected. Thus, the measured distance is derived from the number of steps and the step length, rather than simply integrating the output of the acceleration sensor.

The “number of steps” is detected by taking the acceleration for each axis detected by the acceleration sensor in the mobile terminal as the square root of the sum of squares (√ (x ² + y ² + z ² )) and taking the peak-to-peak as one step (for example, (See Patent Document 3). The “step length” is preset by the user or estimated from the height of the user. Alternatively, according to another technique, there is a technique of calibrating the stride by causing a pedestrian to walk a specified distance (see, for example, Non-Patent Document 1).

  The “traveling direction” is detected by the “direction sensor”. As the direction sensor, a geomagnetic sensor is generally used. There is also a technique for determining a traveling direction based on a horizontal acceleration distribution (see, for example, Patent Documents 8 and 9). There is also a technique for determining the direction of travel of a pedestrian using the relationship between the acceleration in the vertical direction and the acceleration in the travel direction after determining the vertical direction in order to derive the posture of the terminal (see, for example, Patent Document 4). Furthermore, there is a technique for determining the traveling direction from the characteristics of a pedestrian's arm swing (see, for example, Non-Patent Document 2). Further, there is a technique for determining the traveling direction from the attitude of the terminal at a specific time (see, for example, Patent Document 5). Furthermore, when there are a plurality of roads through an intersection in the traveling direction, there is a technique for setting the intersection as the current position (see, for example, Patent Document 6).

  A technology to determine the current position using autonomous navigation technology, in order to prevent the influence of the cumulative error of sensor data, when the right turn or left turn at the intersection is detected, the intersection is the starting point for specifying the current position (See, for example, Patent Document 7). That is, every time a turn is detected, the cumulative error of the sensor data is reset, and the previous cumulative error does not affect the subsequent specification of the current position.

JP-A-5-061408 Japanese Patent Laid-Open No. 9-089584 Japanese Patent Laying-Open No. 2005-038018 JP 2008-039619 A WO2006 / 104140 JP-A-3-099399 JP 63-011813 A Japanese Patent No. 4126388 JP 2008-116315 A

"Nike + iPod User's Guide", page 27, "online", [Search February 3, 2009], Internet <URL: http://manuals.info.apple.com/en/nikeipod_users_guide.pdf> Daisuke Uesaka, Kengo Iwamoto, Shigeki Muramatsu, Satoshi Nishiyama, “Position acquisition system using acceleration and geomagnetic sensors in mobile phones”, Multimedia, Distributed, Cooperation and Mobile Symposium, Proceedings, pp.761-767, July 2008 Moon Shigeki Muramatsu, Daisuke Uesaka, Hiroyuki Yokoyama, “A Study on Estimating Terminal Posture During Walking”, KDDI R & D Laboratories, Inc., FIT2009 (8th Information Science and Technology Forum), Proceedings, September 2, 2009 , [Online], [Search February 3, 2010], Internet <URL: http://www.sofken.com/FIT2009/pdf/M/M_037.pdf>

  In the technique described in Patent Document 4, a direction in which an acceleration exceeding a predetermined threshold is detected is set as a traveling direction candidate. However, when the acceleration distribution is not linear but has a width, it is necessary to evaluate a large number of candidates in the traveling direction, and the amount of calculation is enormous.

  Further, according to the techniques described in Patent Documents 5, 8, and 9, if the posture of the mobile terminal worn by the pedestrian is roughly constant, the horizontal acceleration detected during walking is Utilizing the distribution in the direction of travel. However, when moving with the terminal held in one hand, the horizontal acceleration may not be distributed in the traveling direction even if the terminal posture is roughly constant.

  FIG. 1 is an explanatory diagram illustrating an aspect of a mobile terminal held by a pedestrian.

  According to FIG. 1, the pedestrian is holding the mobile terminal and viewing the screen. For example, it is assumed that a map is displayed on the mobile terminal and the pedestrian is walking while browsing the display. This is the posture when the pedestrian wants to know the traveling direction most accurately. At this time, the posture of the mobile terminal while walking is approximately constant. If the attitude of the mobile terminal is roughly constant, the traveling direction can be estimated using an acceleration sensor and a geomagnetic sensor mounted on the mobile terminal. Since the sensor is fixedly incorporated in the mobile terminal, if the orientation of the mobile terminal is determined, the orientation of the sensor axis is also determined. For example, according to FIG. 1, the x-axis is assigned from the top to the bottom of the key surface, the y-axis is directed from the left to the right of the key surface, and the z-axis is assigned from the back of the key surface to the front. Yes. Of course, the assignment of the coordinate system of the sensor is not limited to this.

  However, according to FIG. 1, although the attitude of the mobile terminal is almost constant, it swings in the horizontal direction and the vertical direction with walking. Further, the acceleration detected by the handheld portable terminal is absorbed by the arm. In such a state, when the technique described in Patent Document 4 is used, it is necessary to evaluate a large number of traveling direction candidates, and the amount of calculation is enormous.

  Therefore, the present invention uses the acceleration sensor and the geomagnetic sensor mounted on the portable terminal as much as possible for the portable terminal held by the user so that the posture of the terminal is approximately constant. It is an object of the present invention to provide a portable terminal, a program, and a method for accurately determining.

According to the present invention, the acceleration sensor that outputs the triaxial acceleration data, the geomagnetic sensor that outputs the triaxial geomagnetic data, and the traveling direction determination means that determines the traveling direction of the pedestrian from the acceleration data and the geomagnetic data. A portable terminal possessed by a pedestrian,
The direction of travel determination means is
Vertical acceleration calculating means for calculating vertical acceleration from acceleration data;
Walking timing detection means for detecting the maximum point of vertical upward acceleration as walking timing;
Horizontal acceleration calculation means for calculating horizontal acceleration orthogonal to vertical acceleration using acceleration data and geomagnetic data;
Step-by-step acceleration classification means for dividing the horizontal acceleration into one step based on the walking timing;
A step-by-step direction calculating means for calculating a step-by-step direction from a horizontal acceleration for one step;
Step-by-step direction classifying means for alternately classifying the step-by-step directions into odd-numbered steps or even-numbered steps;
It has a traveling direction calculation means for calculating the direction of a bisector between the odd-numbered step-by-step direction and the even-numbered step-by-step direction as the traveling direction.

According to another embodiment of the portable terminal of the present invention, the horizontal acceleration calculating means is
Based on the acceleration for each axis output from the acceleration sensor, the gravity vector G is calculated,
Using the gravity vector G and the geomagnetic vector M, the northward acceleration A _North and the eastward acceleration A _East are calculated,
It is also preferable that the horizontal acceleration is constituted by a north acceleration A _North and an east acceleration A _East .

According to another embodiment of the portable terminal of the present invention, the horizontal acceleration calculating means is
Using the gravity vector G and the geomagnetic vector M, the eastward unit vector e _East is calculated by G × M / | G × M |
The eastward acceleration A _East is calculated by taking the inner product of the acceleration data for the eastward unit vector e _East ,
Using the gravity vector G and the geomagnetic vector M, calculate the north-facing unit vector e _North by G × M × G / | G × M × G |
It is also preferable to calculate the northward acceleration A _North by taking the inner product of the acceleration data with respect to the northward unit vector e _North .

  According to another embodiment of the portable terminal of the present invention, the step-by-step direction calculating means plots a large number of horizontal accelerations for one step on a horizontal plane, and uses principal component analysis to calculate the step-by-step directions for the multiple plots. It is also preferable to calculate.

According to another embodiment of the portable terminal of the present invention, the stepwise direction calculating means is
Calculate variances Vxx, Vyy and covariance Vxy for northward and eastward horizontal acceleration for each step,
Based on the variance and covariance, calculate the eigenvalue λ,
The eigenvector [e ₁ , e ₂ ] is calculated using the eigenvalue λ,
It is also preferable to calculate the angle Tan ⁻¹ (e ₁ / e ₂ ) as a step-by-step direction using the eigenvector [e ₁ , e ₂ ].

  According to another embodiment of the portable terminal of the present invention, it is also preferable to calculate an average value of the odd-numbered steps and the even-numbered steps as the traveling direction.

  According to another embodiment of the portable terminal of the present invention, it is also preferable that the vertical acceleration calculation means and the horizontal acceleration calculation means function as a low-pass filter that blocks high frequency components with respect to acceleration data.

According to the present invention, a computer mounted on a portable terminal having an acceleration sensor that outputs triaxial acceleration data and a geomagnetic sensor that outputs triaxial geomagnetic data can be used as a pedestrian's progression from acceleration data and geomagnetic data. A program that functions as a traveling direction determination means for determining a direction,
The direction of travel determination means is
Vertical acceleration calculating means for calculating vertical acceleration from acceleration data;
Walking timing detection means for detecting the maximum point of vertical upward acceleration as walking timing;
Horizontal acceleration calculation means for calculating horizontal acceleration orthogonal to vertical acceleration using acceleration data and geomagnetic data;
Step-by-step acceleration classification means for dividing the horizontal acceleration into one step based on the walking timing;
A step-by-step direction calculating means for calculating a step-by-step direction from a horizontal acceleration for one step;
Step-by-step direction classifying means for alternately classifying the step-by-step directions into odd-numbered steps or even-numbered steps;
The computer is caused to function as a traveling direction calculation unit that calculates the direction of the bisector of the odd-numbered step-by-step and even-numbered step-by-step directions as the traveling direction.

According to the present invention, a portable terminal having an acceleration sensor that outputs triaxial acceleration data and a geomagnetic sensor that outputs triaxial geomagnetic data is used to determine a pedestrian's direction of travel from acceleration data and geomagnetic data. A direction determination method,
A first step of calculating vertical acceleration from acceleration data;
A second step of detecting a maximum point of vertical upward acceleration as a walking timing;
A third step of calculating a horizontal acceleration perpendicular to the vertical acceleration using the acceleration data and the geomagnetic data;
A fourth step of dividing the horizontal acceleration into one step based on the walking timing;
A fifth step of calculating the direction for each step from the horizontal acceleration for one step;
A sixth step of alternately classifying the direction of each step into odd or even steps;
And a seventh step of calculating the direction of the bisector between the odd-numbered step-by-step direction and the even-numbered step-by-step direction as the traveling direction.

  According to the portable terminal, the program, and the method of the present invention, the user walks using the acceleration sensor and the geomagnetic sensor mounted on the portable terminal held by the user so that the attitude of the terminal is approximately constant. It is possible to determine a person's traveling direction as accurately as possible.

It is explanatory drawing showing the aspect of the portable terminal hand-held by the pedestrian. It is a functional block diagram of the portable terminal in this invention. It is a graph of the acceleration for every axis | shaft according to elapsed time. It is a graph of the vertical direction acceleration according to elapsed time. It is explanatory drawing showing the change of a horizontal direction acceleration. It is explanatory drawing showing the response | compatibility of the change of a horizontal direction acceleration and a vertical direction acceleration. It is explanatory drawing showing the relationship of the direction with respect to gravity G and geomagnetism M. FIG. It is explanatory drawing showing the direction for every step.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

  FIG. 2 is a functional configuration diagram of the mobile terminal according to the present invention.

  According to FIG. 2, the mobile terminal 1 is a terminal that can be held by a user, for example, a mobile phone. The portable terminal 1 includes a traveling direction determination unit 10, an acceleration sensor 11, a geomagnetic sensor 12, a positioning unit 13, a map information storage unit 14, a display control unit 15, and a display 16. The traveling direction determination unit 10, the map information storage unit 14, and the display control unit 15 are realized by executing a program that causes a computer mounted on the portable terminal to function.

  The acceleration sensor 11 detects acceleration for each of the x axis, the y axis, and the z axis. In the case of existing general mobile phones, there are many cases in which an acceleration sensor is mounted in advance. The detected acceleration data is output to the traveling direction determination unit 10.

  FIG. 3 is a graph of acceleration for each axis according to elapsed time.

  According to FIG. 3, when a pedestrian holds a mobile terminal and walks while viewing the display, acceleration data for each axis obtained by the acceleration sensor is shown.

  The geomagnetic sensor 12 detects geomagnetism, which is the magnetic field lines of the earth from south to north. The direction of the orthogonal projection of the detected geomagnetism with respect to the horizontal plane is “north”. In the case of a triaxial geomagnetic sensor, the orientation can be detected by detecting the tilt even if it is not horizontal. The detected geomagnetic data is output to the traveling direction determination unit 10.

  The positioning unit 13 receives a positioning radio wave from a GPS (Global Positioning System) satellite and acquires latitude and longitude data of the current position. The latitude / longitude data is output to the display control unit 15.

  The map information storage unit 14 accumulates map information. Based on the current position instructed from the display control unit 15, the map information is output to the display control unit 15.

  The display control unit 15 receives the traveling direction data from the traveling direction determination unit 10 and the current position information from the positioning unit 13. Further, the display control unit 15 outputs the current position information to the map information storage unit 14 and acquires the map information of the current position. And the display control part 15 produces | generates the image which displayed the present position on the map, and displayed the advancing direction with the arrow. The image is output to the display unit 16. For example, it is used for a navigation system for pedestrians.

  The display 14 displays an image from the display control unit 15 so that the walking user can visually recognize the image.

  The traveling direction unit 10 includes a vertical direction acceleration calculation unit 101, a horizontal direction acceleration calculation unit 102, a walking timing detection unit 103, a step-by-step acceleration classification unit 104, a step-by-step direction calculation unit 105, and a step-by-step direction classification unit. 106 and a traveling direction calculation unit 107. Hereinafter, these functional components will be described in detail.

[Vertical acceleration calculation unit / Horizontal acceleration calculation unit]
The vertical acceleration calculation unit 101 calculates vertical acceleration using acceleration data. Further, the horizontal acceleration calculation unit 102 calculates horizontal acceleration using acceleration data and geomagnetic data. The vertical acceleration and the horizontal acceleration are orthogonal to each other.

  FIG. 4 is a graph of vertical acceleration according to elapsed time.

  According to FIG. 4, the upper side of the vertical acceleration represents the downward direction in the vertical direction, and the lower side represents the upward direction in the vertical direction. In addition, the change in vertical acceleration has a periodicity that coincides with walking. Here, the maximum point of the downward acceleration in the vertical direction represents a time point when the body is lowered, that is, a time point when the foot that has left the ground touches the ground. On the other hand, the maximum point of vertical upward acceleration represents the time when the body is raised, that is, the time when the foot is raised. Further, the interval between the minimum points in the vertical downward acceleration, that is, the interval between the maximum points in the vertical upward acceleration represents one step of the pedestrian.

  FIG. 5 is an explanatory diagram showing changes in horizontal acceleration.

  According to FIG. 5, the horizontal acceleration actually obtained by the pedestrian gripping the portable terminal with the right hand and walking in the manner shown in FIG. 1 is plotted. As described above, the forward acceleration repeats acceleration / deceleration, and at the same time, repeats forward / backward / up / down. The point that became clear here is that the distribution of horizontal acceleration does not coincide with the traveling direction. According to FIG. 5, odd-numbered steps and even-numbered steps (right foot and left foot) are distributed in different directions. In addition, as a clear point, the directions of the bisectors in the directions of the odd and even steps correspond to the traveling direction. Thereby, the traveling direction can be calculated.

Furthermore, the acceleration of a one-step walking cycle is observed in the following order.
Vertical maxima-> Maximum backward direction->
Vertical maximum downward-> forward maximum forward direction This allows the forward direction to be sorted according to the direction of acceleration distribution.

  FIG. 6 is an explanatory diagram showing correspondence between changes in horizontal acceleration and vertical acceleration.

FIG. 6 shows an acceleration locus for two steps. The vertical acceleration and the horizontal acceleration are orthogonal to each other.
[t0] For the first step, when the vertical downward acceleration is at a maximum, the horizontal acceleration has shifted to the left in the traveling direction.
[t1] For the first step, when the vertical upward acceleration is maximum, the horizontal acceleration has shifted to the right in the traveling direction.
[t2] For the second step, when the vertical downward acceleration is maximum, the horizontal acceleration has shifted to the right in the traveling direction.
[t3] With respect to the second step, when the vertical upward acceleration is at a maximum, the horizontal acceleration has shifted to the left in the traveling direction.

  FIG. 7 is an explanatory diagram showing the relationship of the orientation with respect to gravity G and geomagnetism M.

The gravity vector G and the geomagnetic vector M are expressed as follows for each of the x-axis, the y-axis, and the z-axis. In addition, since the posture of the portable terminal while walking is roughly constant, the geomagnetic data observed in a short time is almost constant.
Gravity vector G: G = (g _x , g _y , g _z )
Geomagnetic vector _{M: M = (m x,} m y, m z)

  First, the gravity vector G is calculated. It is difficult to accurately determine the gravitational direction of the mobile terminal during walking even when using acceleration data. Therefore, the direction of the vector of the sum of the accelerations of each axis is regarded as the direction of gravity using a large number of x-axis, y-axis and z-axis acceleration data detected in a predetermined time range.

The acceleration of each i-th axis is expressed as follows.
x-axis acceleration: ACC _x [i]
y-axis acceleration: ACC _y [i]
z-axis acceleration: ACC _z [i]
The sum of n pieces of acceleration data is expressed as follows.
ACCS _x = Σ _{i = 1} ^N ACC _x [i]
ACCS _y = Σ _{i = 1} ^N ACC _y [i]
ACCS _z = Σ _{i = 1} ^N ACC _z [i]
The gravity vector G is expressed as follows.
G = (g _x , g _y , g _z ) = (ACCS _x , ACCS _y , ACCS _z )

Next, assuming that the x-axis, y-axis, and z-axis are right-handed as in FIG. 1, the unit vectors in each direction are expressed as follows.
Northward unit vector e _North : e _North = (e _Nx , e _Ny , e _Nz )
Eastward unit vector e _East : e _East = (e _Ex , e _Ey , e _Ez )
Downward unit vector e _Down : e _Down = (e _Dx , e _Dy , e _Dz )
Further, the acceleration data is expressed as follows.
A = (A _x , A _y , A _z )

According to FIG. 7, when the gravity vector G and the geomagnetic vector M are used, each unit vector is expressed as follows.
North-facing unit vector e _North : e _North = G × M × G / | G × M × G |
East unit vector e _East : e _East = G × M / | G × M |
Downward unit vector e _Down : e _Down = G / | G |
×: Cross product (vector product, outer product)

  “G × M” (outer product) creates a vector in a direction perpendicular to the plane formed by the gravity vector G and the geomagnetic vector M. When viewed in the direction of the gravity vector G, G × M extends in a clockwise direction as viewed from the geomagnetic vector M. Since the geomagnetic vector M is directed from the south to the north, the direction of 90 degrees clockwise from the axis, that is, G × M is directed to the “east” direction.

  Also, “(G × M) × G” creates a vector in a direction perpendicular to the plane created by the east vector G × M and the gravity vector G. When looking toward the east vector G × M, (G × M) × G extends in the clockwise direction as viewed from the gravity vector. Since the gravity vector is directed from the top to the bottom, the direction of 90 degrees clockwise from the axis, that is, (G × M) × G is directed to the “north” direction.

Then, the acceleration vector in each direction is calculated by taking the inner product of the acceleration vector A with respect to the unit vector e in each direction.
Northward acceleration: A _N = e _Nx × A _x + e _Ny × A _y + e _Nz × A _z
East acceleration: A _E = e _Ex × A _x + e _Ey × A _y + e _Ez × A _z
Vertical downward acceleration: A _D = e _Dx × A _x + e _Dy × A _y + e _Dz × A _z

  As described above, the vertical direction acceleration calculation unit 101 calculates the gravity vector G and outputs the vertical direction downward acceleration to the walking timing detection unit 103.

Further, the horizontal acceleration calculation unit 102 calculates the gravity vector G, and calculates the northward acceleration A _North and the eastward acceleration A _East using the gravity vector G and the geomagnetic vector M. Then, the horizontal acceleration constituted by the northward acceleration A _North and the eastward acceleration A _East is output to the step-by-step acceleration classification unit 104.

  Note that the vertical direction acceleration calculation unit 101 and the horizontal direction acceleration calculation unit 102 preferably also function as a low-pass filter that blocks high frequency components from acceleration data. As a result, acceleration data as an abnormal value can be removed, and an accurate traveling direction can be calculated.

[Walking timing detector]
The walking timing detection unit 103 detects the walking timing generated by the walking motion of the pedestrian from the vertical acceleration output from the vertical acceleration calculation unit 101. As described above with reference to FIG. 4, the walking timing extracts the maximum point of the vertical upward acceleration. For example, as described in FIG. 6, each time the vertical downward acceleration becomes the minimum point, the walking timing is output to the step-by-step acceleration classification unit 104.

[Step-by-step acceleration section]
The step-by-step acceleration classifying unit 104 classifies the step-by-step acceleration into a horizontal acceleration data group according to the walking timing output from the walking timing detecting unit 103. Then, the horizontal acceleration data group for each step is output to the direction calculation unit 105 for each step.

[Stepwise direction calculation unit]
The step-by-step direction calculation unit 105 detects a direction from a horizontal acceleration data group (a group of northward acceleration and eastward acceleration) for each step. The detected direction for each step is output to the direction classification unit 106 for each step.

  FIG. 8 is an explanatory diagram showing the direction of each step.

  As shown in FIG. 8, the direction for each step is determined using principal component analysis, for example. “Principal component analysis” is a method of calculating one or more principal components having a correlation from a large number of component distributions. The principal component having the largest correlation among them represents the direction for each step in the present invention.

(Ｖxx−λ)・(Ｖyy−λ)−Ｖxy・Ｖxy＝０
Ｖxx・Ｖyy−Ｖxx・λ−λ・Ｖyy＋λ²−Ｖxy²＝０ （２つの固有値λが算出） Let the i-th data of the two variables x and y in the horizontal acceleration be x _i and y _i , respectively. At this time, the eigenvalue λ of the n pieces of data is calculated by the following determinant.

(Vxx−λ) · (Vyy−λ) −Vxy · Vxy = 0
Vxx ・ Vyy−Vxx ・ λ−λ ・ Vyy + λ ² −Vxy ² = 0 (Two eigenvalues λ are calculated)

Here, Vxx, Vyy, and Vxy are variance and covariance.
Vxx = 1 / n · Σ _{i = 1} ⁿ (x _i -x ^￣ ) ²
_{Vyy = 1 / n · Σ i} = 1 n (y i -y ¯) 2
_{Vxy = 1 / n · Σ i} = 1 n (x i -x ¯) (y i -y ¯)

Of the two eigenvalues calculated lambda, when larger one with lambda _1, eigenvector is calculated by the following equation.

The direction in the horizontal acceleration data group for each step is calculated by the following equation.
Angle = Tan ^-1 (e ₂ / e ₁ )

  In addition, when the step-by-step acceleration is divided into the acceleration data group for each step for each minimum point of the acceleration in the downward direction in the vertical direction, the acceleration is observed in the order of the maximum of the backward acceleration-> the maximum of the forward acceleration.

As described above, the step-by-step direction calculation unit 105 calculates the variances Vxx and Vyy and the covariance Vxy for the northward and eastward horizontal accelerations for each step. Then, the eigenvalue λ is calculated based on the variance and the covariance, the eigenvector [e ₁ , e ₂ ] is calculated, and the angle Tan ⁻¹ (e ₁ / e ₂ ) is calculated as the stepwise direction.

[Stepwise direction classification unit]
The step direction classification unit 106 inputs the step direction from the step direction calculation unit 105. Then, the step-by-step direction classification unit 106 classifies the step-by-step directions alternately into odd-numbered steps or even-numbered steps. Here, odd / even does not mean odd / even steps from the reference point, but simply stores and outputs the direction of each step alternately. The odd-numbered steps and the even-numbered steps are output to the traveling direction calculation unit 107.

[Advancing direction calculation unit]
The traveling direction calculation unit 107 determines the direction of the bisector in both directions as the traveling direction, using the odd-numbered step-by-step direction and the even-numbered step-by-step direction. For example, as described in FIG. 8, the step direction of odd steps and the step direction of even steps may be averaged. Further, smoothing is also preferable. “Smoothing” refers to a method of rationally averaging continuous values by removing data that is significantly different from other values. Then, the calculated traveling direction is output to the display control unit 15.

Finally, specific calculation examples in the step-by-step direction calculation unit 105, the step-by-step direction classification unit 106, and the traveling direction calculation unit 107 will be described.
[First step]
It is assumed that northward x and eastward y are assumed, and the horizontal acceleration variance and covariance for one step are as follows.
Vxx = 7241.633
Vyy = 569.402
Vxy = 1798.564
Here, the eigenvalue λ is calculated.
Vxx ·· 75y−Vxx · λ−Vyy · λ + λ ² −Vxy ² = 0
7241.633 ・ 569.402−7241.633 ・ λ−569.402 ・ λ + λ ² −1798.564 ² = 0
The larger eigenvalue λ ₁ = 7695.5570 is calculated.
The eigenvector [e ₁ , e ₂ ] is calculated by the following equation.
-453.937 ・ e ₁ +1798.564 ・ e ₂ = 0
[E ₁ , e ₂ ] = k [3.962144, 1] (k: arbitrary)
The angle is calculated by the following formula.
Tan ⁻¹ (e ₂ / e ₁ ) = 0.247 rad [radian]

[Second step]
Vxx = 10693.206
Vyy = 2633.204
Vxy = -4448.360
Here, the eigenvalue λ is calculated.
Vxx · · '75yy-Vyy · λ-' 7c Vxx · λ + λ ^2- Vxy ² = 0
10693.206 ・ 2633.204−10693.206 ・ λ−2633.204 ・ λ + λ ² − (-4448.360) ² = 0
The larger eigenvalue λ ₁ = 12665.606 is calculated.
The eigenvector [e ₁ , e ₂ ] is calculated by the following equation.
-1972.400 ・ e ₁ + (-4448.360) ・ e ₂ = 0
[E ₁ , e ₂ ] = k [−2.2553, 1] (k: arbitrary)
The angle is calculated by the following formula.
Tan ⁻¹ (e ₂ / e ₁ ) = − 0.417 rad [radians]

[Direction]
Since the first step is 0.247 rad and the second step is -0.417 rad, the traveling direction is an average value as follows.
(0.247 + (-0.417)) / 2 = -0.085rad [radians]
Thus, in the above-described calculation example, the traveling direction is −0.085 rad.

  As described above in detail, according to the mobile terminal, the program, and the method of the present invention, the acceleration mounted on the mobile terminal held by the user so that the attitude of the terminal is approximately constant. Using the sensor and the geomagnetic sensor, the direction of travel of the pedestrian can be determined as accurately as possible.

  Various changes, modifications, and omissions of the above-described various embodiments of the present invention can be easily made by those skilled in the art. The above description is merely an example, and is not intended to be restrictive. The invention is limited only as defined in the following claims and the equivalents thereto.

DESCRIPTION OF SYMBOLS 1 Portable terminal 10 Travel direction determination part 101 Vertical direction acceleration calculation part 102 Horizontal direction acceleration calculation part 103 Walking timing detection part 104 Step acceleration classification part 105 Step direction calculation part 106 Step direction classification part 107 Travel direction calculation part 11 Acceleration Sensor 12 Geomagnetic sensor 13 Positioning unit 14 Map information storage unit 15 Display control unit 16 Display

Claims (9)

An acceleration sensor that outputs triaxial acceleration data; a geomagnetic sensor that outputs triaxial geomagnetic data; and a traveling direction determination means that determines a traveling direction of a pedestrian from the acceleration data and the geomagnetic data. A portable terminal owned by a person,
The traveling direction determination means includes
Vertical acceleration calculation means for calculating vertical acceleration from the acceleration data;
Walking timing detection means for detecting the maximum point of vertical upward acceleration as walking timing;
Horizontal acceleration calculation means for calculating horizontal acceleration orthogonal to the vertical acceleration using the acceleration data and the geomagnetic data;
Based on the walking timing, step-by-step acceleration dividing means for dividing into horizontal acceleration for one step;
A step-by-step direction calculating means for calculating a step-by-step direction from the horizontal acceleration for one step;
Step-by-step direction classification means for alternately classifying the step-by-step directions into odd-numbered steps or even-numbered steps;
A portable terminal, comprising: a traveling direction calculation means for calculating a direction of a bisector between the odd-numbered step-by-step direction and the even-numbered step-by-step direction as a traveling direction. The horizontal acceleration calculating means includes
Based on the acceleration for each axis output from the acceleration sensor, the gravity vector G is calculated,
Using the gravity vector G and the geomagnetic vector M, the northward acceleration A _North and the eastward acceleration A _East are calculated,
The mobile terminal according to claim 1, wherein the horizontal acceleration is configured by the north acceleration A _North and the east acceleration A _East . The horizontal acceleration calculating means includes
Using the gravity vector G and the geomagnetic vector M, an eastward unit vector e _East is calculated by G × M / | G × M |
The eastward acceleration A _East is calculated by taking the inner product of acceleration data with respect to the eastward unit vector e _East ,
Using the gravity vector G and the geomagnetic vector M, a north-facing unit vector e _North is calculated by G × M × G / | G × M × G |
Wherein by taking the inner product of the acceleration data to the north unit vector e _North, portable terminal according to claim 2, characterized in that to calculate the northward acceleration A _North.   4. The step-by-step direction calculating means plots a number of horizontal accelerations for one step on a horizontal plane, and calculates a step-by-step direction for the number of plots using principal component analysis. The mobile terminal according to any one of the above. The stepwise direction calculating means includes
Calculate variances Vxx, Vyy and covariance Vxy for northward and eastward horizontal acceleration for each step,
Based on the variance and covariance, calculate the eigenvalue λ,
The eigenvector [e ₁ , e ₂ ] is calculated using the eigenvalue λ,
5. The angle Tan ⁻¹ (e ₁ / e ₂ ) is calculated as a step-by-step direction using the eigenvector [e ₁ , e ₂ ], according to any one of claims 1 to 4. Mobile device.   6. The mobile terminal according to claim 1, wherein an average value of the odd-numbered steps and the even-numbered steps is calculated as a traveling direction.   The said vertical direction acceleration calculation means and a horizontal direction acceleration calculation means function as a low-pass filter which interrupts | blocks a high frequency component with respect to the said acceleration data, The any one of Claim 1 to 6 characterized by the above-mentioned. Mobile devices. A computer mounted on a portable terminal having an acceleration sensor that outputs triaxial acceleration data and a geomagnetic sensor that outputs triaxial geomagnetic data is used to determine the direction of travel of a pedestrian from the acceleration data and the geomagnetic data. A program that functions as a direction of travel determination means,
The traveling direction determination means includes
Vertical acceleration calculation means for calculating vertical acceleration from the acceleration data;
Walking timing detection means for detecting the maximum point of vertical upward acceleration as walking timing;
Horizontal acceleration calculation means for calculating horizontal acceleration orthogonal to the vertical acceleration using the acceleration data and the geomagnetic data;
Based on the walking timing, step-by-step acceleration dividing means for dividing into horizontal acceleration for one step;
A step-by-step direction calculating means for calculating a step-by-step direction from the horizontal acceleration for one step;
Step-by-step direction classification means for alternately classifying the step-by-step directions into odd-numbered steps or even-numbered steps;
A function of a computer as a traveling direction calculating means for calculating a direction of a bisector between a stepwise direction of the odd steps and a stepwise direction of the even steps as a traveling direction. program. A traveling direction determining method for determining a traveling direction of a pedestrian from the acceleration data and the geomagnetic data by a portable terminal having an acceleration sensor that outputs triaxial acceleration data and a geomagnetic sensor that outputs triaxial geomagnetic data. There,
A first step of calculating vertical acceleration from the acceleration data;
A second step of detecting a maximum point of vertical upward acceleration as a walking timing;
A third step of calculating a horizontal acceleration orthogonal to the vertical acceleration using the acceleration data and the geomagnetic data;
A fourth step of dividing the horizontal acceleration into one step based on the walking timing;
A fifth step of calculating a step-by-step direction from the horizontal acceleration of the one step;
A sixth step of alternately classifying the step-by-step directions into odd-numbered steps or even-numbered steps;
And a seventh step of calculating a direction of a bisector between the odd-numbered step-by-step direction and the even-numbered step-by-step direction as a traveling direction. Method.

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