JP2016031244A - Physical quantity data correction device, magnetic detection device, orientation angle detection device, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To correct an interference component of a sensor or the like by using appropriate correction parameters even when an environment condition changes.SOLUTION: There are provided a physical quantity data correction device having a detection data acquisition unit for acquiring detection data of physical quantities in a plurality of axial directions, a parameter acquisition unit for acquiring a plurality of correction parameters for correcting the physical quantities in a plurality of axial directions, a parameter selection unit for selecting a correction parameter used for correction among the plurality of correction parameters on the basis of a distribution of the detection data in the plurality of axial directions, and a correction unit for correcting the detection data by using the selected correction parameter; and a program thereof.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a physical quantity data correction device, a magnetic detection device, an azimuth angle detection device, and a program.

When geomagnetism is detected by a magnetic sensor or the like, an interference component of a local magnetic field around the magnetic sensor may be superimposed. In such a case, the detection result, which is an elliptic function acquired while rotating the magnetic sensor, is corrected to reduce the influence of the interference component by using a correction parameter or the like for converting to a circular function (for example, Patent Document 1).
[Patent Document 1] Japanese Patent Application Laid-Open No. 2008-76397

  Such a magnetic sensor must use an appropriate correction parameter in accordance with the change of the state when the state of the surrounding environment changes. Therefore, when the environmental state or the like of the magnetic sensor cannot be determined, it is difficult to select an appropriate correction parameter.

  In the first aspect of the present invention, a detection data acquisition unit that acquires physical quantity detection data in a plurality of axial directions, a parameter acquisition unit that acquires a plurality of correction parameters for correcting physical quantities in a plurality of axial directions, and a plurality of axial directions A physical quantity data correction apparatus comprising: a parameter selection unit that selects a correction parameter to be used for correction among a plurality of correction parameters based on a distribution of detection data in the method; and a correction unit that corrects detection data using the selected correction parameter And provide programs.

  According to a second aspect of the present invention, there is provided a magnetic comprising: the physical quantity data correction device according to the first aspect; and a magnetic offset vector estimation unit that estimates and cancels the magnetic offset vector from the magnetic data corrected by the physical quantity data correction device. A detection device, an azimuth angle detection device, and a program are provided.

  It should be noted that the above summary of the invention does not enumerate all the necessary features of the present invention. In addition, a sub-combination of these feature groups can also be an invention.

2 shows a configuration example of a physical quantity data correction apparatus 100 according to the present embodiment. The operation | movement flow of the physical quantity data correction apparatus 100 which concerns on this embodiment is shown. An example of the detection data of the magnetic detection unit 10 acquired by the detection data acquisition unit 110 according to the present embodiment is shown. The calculation part 132 which concerns on this embodiment shows an example of the detection data after filtering and thinning out detection data. An example in which the calculation unit 132 according to the present embodiment applies the distribution of the value of the detection data x _meas to a three-dimensional ellipsoid is shown. An example when the calculation part 132 which concerns on this embodiment correct | amends the offset of a three-dimensional ellipsoid is shown. An example in which the calculation unit 132 according to the present embodiment rotates a three-dimensional ellipsoid and converts it into a standard format is shown. An example in which the calculation unit 132 according to the present embodiment converts a three-dimensional ellipsoid into a sphere is shown. The structural example of the magnetic detection apparatus 200 which concerns on this embodiment is shown. An example of the hardware configuration of a computer 1900 functioning as the physical quantity data correction apparatus 100 according to the present embodiment will be shown.

  Hereinafter, the present invention will be described through embodiments of the invention, but the following embodiments do not limit the invention according to the claims. In addition, not all the combinations of features described in the embodiments are essential for the solving means of the invention.

  FIG. 1 shows a configuration example of a physical quantity data correction apparatus 100 according to the present embodiment. The physical quantity data correction apparatus 100 is used for correction in accordance with the similarity between a conversion coefficient for returning the spatial distribution of the acquired physical quantity detection result to a predetermined distribution and a plurality of correction parameters calculated in advance. A power correction parameter is selected to correct the physical quantity.

  The physical quantity data correction apparatus 100 may acquire physical quantities such as geomagnetism, acceleration, angular acceleration, and electric field. In the present embodiment, as an example, the physical quantity data correction apparatus 100 will explain a geomagnetic detection result as a physical quantity detection result. The physical quantity data correction apparatus 100 includes a detection data acquisition unit 110, a parameter acquisition unit 120, a parameter selection unit 130, and a correction unit 140.

  The detection data acquisition unit 110 acquires physical quantity detection data in a plurality of axial directions detected by a physical quantity detection device or the like. The detection data acquisition unit 110 may be connected to a physical quantity detection device or the like, and may acquire detection data supplied by the physical quantity detection device or the like. Instead, a detection supplied by an external device connected to the physical quantity detection device or the like Data may be acquired. The detection data acquisition unit 110 may acquire detection data stored in an internal or external storage device of the physical quantity data correction apparatus 100.

  When acquiring detection data from an external device or the like, the detection data acquisition unit 110 may be connected to a network or the like and acquire detection data via the network. FIG. 1 shows an example in which the detection data acquisition unit 110 is connected to a magnetic detection unit 10 that detects geomagnetism in the triaxial directions of the XYZ axes. In this case, the detection data acquisition unit 110 acquires magnetic data output from the magnetic detection unit 10 in a plurality of axial directions.

  Here, the magnetic detection unit 10 may be a sensor that detects the magnitude and direction of a magnetic field, such as a magnetoresistive effect element and a Hall element. In this case, as an example, the three magnetic detection units 10 respectively detect geomagnetism corresponding to the three axial directions.

  The parameter acquisition unit 120 acquires a plurality of correction parameters for correcting physical quantities in a plurality of axis directions. The parameter acquisition unit 120 acquires a plurality of correction parameters that are corrected so as to reduce interference components and / or noise included in the detection result of the physical quantity detected by the physical quantity detection device or the like. The parameter acquisition unit 120 may acquire a plurality of correction parameters stored in an internal or external storage device of the physical quantity data correction apparatus 100. In FIG. 1, the parameter acquisition unit 120 shows an example of acquiring a plurality of correction parameters from an external device or the like. In this case, the parameter acquisition unit 120 may be connected to a network or the like and acquire a plurality of correction parameters via the network.

  Here, at least some of the plurality of correction parameters acquired by the parameter acquisition unit 120 correspond to the plurality of mounting forms of the magnetic detection unit 10, respectively. In addition, at least some of the plurality of correction parameters respectively correspond to a plurality of environmental forms of the magnetic detection unit. For example, when the magnetic detection unit 10 is incorporated in an apparatus or the like, the direction of geomagnetism is bent by a soft magnetic material such as a magnetic flux concentrating plate, a magnetic shield, a coil, and a transformer core existing in the apparatus. In addition, even when the apparatus is close to or attached to / detached from an input device such as a magnetic shield or digitizer, a wireless charger, etc., the direction of geomagnetism is bent, so that the detection result of the magnetic detection unit 10 May have an effect.

That is, the detection result of the magnetic detection unit 10 is corrected using an appropriate correction parameter according to the mounting configuration such as the arrangement of the magnetic detection unit 10 and the environmental configuration such as the situation around the magnetic detection unit 10. There must be. Therefore, the parameter acquisition unit 120 acquires a plurality of correction parameters respectively corresponding to a plurality of mounting forms of the magnetic detection unit 10 and a plurality of environmental mobile phones. Here, for example, each of the m detection data x _meas is a data vector on an n-dimensional space having n elements, and each of the _k correction parameters C _k is n data of the detection data x _meas . It is an n × n matrix for converting each element.

  The parameter selection unit 130 is connected to the detection data acquisition unit 110 and the parameter acquisition unit 120, and selects a correction parameter to be used for correction from among a plurality of correction parameters based on the distribution of detection data in a plurality of axis directions. The parameter selection unit 130 selects an appropriate correction parameter according to the mounting form of the magnetic detection unit 10 and the environment carrying using the distribution of detection data. The distribution of detection data and selection of correction parameters will be described later. The parameter selection unit 130 includes a calculation unit 132, a determination unit 134, and a specification unit 136.

The calculation unit 132 receives the detection data from the detection data acquisition unit 110, and calculates a conversion coefficient corresponding to the distribution of the detection data. The calculating unit 132 converts a distribution obtained by mapping the detection data values into a space (n-dimensional space) formed in a plurality of (n) axial directions into a distribution having a predetermined shape in the space. calculate. For example, the calculation unit 132 acquires m pieces of detection data x _meas on an n-dimensional space having n elements, and a distribution formed by the m pieces of detection data is determined in advance on the n-dimensional space. A conversion coefficient Z to be converted into the shape distribution x _ideal is calculated.

In this case, the conversion coefficient Z is an n × n matrix, and the following equation is established. In addition, when the following formula is satisfied, it is assumed that uncertain noise or the like is not superimposed on the detection data. As an example, when the three magnetic detection units 10 detect geomagnetism in a three-dimensional space, the conversion coefficient Z is a 3 × 3 matrix.
(Equation 1)
x _ideal = Z · x _meas

The determination unit 134 is connected to the parameter acquisition unit 120 and the calculation unit 132, and determines the similarity between the conversion coefficient calculated by the calculation unit 132 and each of the plurality of correction parameters acquired by the parameter acquisition unit 120. For example, the determination unit 134 determines the degree of similarity between the conversion coefficient Z of the n × n matrix and the plurality of correction parameters C _k that are the n × n matrix. The determination unit 134 may determine the similarity by calculating a norm or the like of the difference between the matrices. The determination unit 134 supplies the similarity determined for each correction parameter to the specifying unit 136.

  The specifying unit 136 is connected to the determination unit 134 and specifies a correction parameter used for correction among a plurality of correction parameters based on the similarity. For example, the specifying unit 136 sets the correction parameter having the highest similarity as the correction parameter used for correction. The specifying unit 136 supplies the specified correction parameter to the correction unit 140.

  The correction unit 140 is connected to the detection data acquisition unit 110 and the specification unit 136, and corrects the detection data using the correction parameter selected by the parameter selection unit 130. As described above, the physical quantity data correction apparatus 100 according to the present embodiment calculates a conversion coefficient for converting the distribution of detected data values into a predetermined distribution, and is determined to have the highest degree of similarity with the conversion coefficient. The detected data is corrected using the correction parameters. The operation in which the physical quantity data correction apparatus 100 corrects the detection data will be described with reference to FIG.

  FIG. 2 shows an operation flow of the physical quantity data correction apparatus 100 according to the present embodiment. The physical quantity data correction apparatus 100 executes the operation flow, selects a correction parameter for reducing the interference component of the detection data from the plurality of correction parameters, and corrects the detection data.

First, the detection data acquisition unit 110 acquires detection data x _meas from the magnetic detection unit 10 (S210). Here, an example in which the detection data x _meas is a three-dimensional vector and the detection data acquisition unit 110 acquires m detection data x _meas will be described. The detection data acquisition unit 110 supplies the acquired detection data to the parameter selection unit 130.

  Moreover, the detection data acquisition part 110 may memorize | store the acquired detection data in the said memory | storage part, when a memory | storage part etc. are provided in the inside of the physical quantity data correction apparatus 100. FIG. In this case, the parameter selection unit 130 may read the detection data stored in the storage unit.

Next, the parameter acquisition unit 120 acquires a plurality of correction parameters (S220). The parameter acquisition unit 120 of this example acquires k correction parameters C _k that are 3 × 3 matrices for correcting the three elements of the detection data x _meas . The parameter acquisition unit 120 supplies the acquired plurality of correction parameters to the parameter selection unit 130.

  Similar to the detection data acquisition unit 110, the parameter acquisition unit 120 may store the acquired plurality of correction parameters in the storage unit. In this case, the parameter selection unit 130 stores the plurality of correction parameters stored in the storage unit. You may read. In addition, the acquisition of the correction parameter of the parameter acquisition unit 120 may be executed prior to the acquisition of the detection data of the detection data acquisition unit 110, and instead, the acquisition of the detection data of the detection data acquisition unit 110 is performed substantially simultaneously. May be.

Next, the calculation unit 132 calculates the distribution of the detection data x _{meas in} order to calculate the conversion coefficient Z according to the distribution of the detection data (S230). For example, the calculation unit 132 calculates an n-dimensional ellipsoid that approximates the distribution of the detection data in an n-dimensional (n is an integer of 2 or more) coordinate space expressed by a plurality of axis directions based on the detection data. That is, in this example, the calculation unit 132 calculates a three-dimensional ellipsoid that approximates the distribution of the detection data x _meas in the three-dimensional space.

Here, in the case of an ideal mounting form and environment form in which there is no substance that interferes with geomagnetism measurement, such as a soft magnetic material and a hard magnetic material, when the magnetic detection unit 10 measures the geomagnetism, substantially the same size corresponding to the geomagnetism. The direction corresponding to the magnetic field and the direction of the magnetic detection unit 10 is detected. For example, when the magnetic detection unit 10 is mounted on a portable device or the like held by the user and the user moves the portable device to rotate, the magnetic detection unit 10 has a radius R corresponding to the magnitude of geomagnetism. Data plotted on the surface of the sphere is output as detection data x _meas . That is, the magnetic detection unit 10 outputs detection data that is a distribution of a three-dimensional sphere centered on the origin as the distribution of the detection data x _meas in the three-dimensional space.

When there is a soft magnetic material that distorts the direction of geomagnetism, the magnetic detection unit 10 distorts the distribution of the three-dimensional sphere of the detection data into the distribution of the three-dimensional ellipsoid according to the influence of the soft magnetic material. End up. Therefore, the calculation unit 132 calculates a three-dimensional ellipsoid that approximates the distribution of the detection data x _{meas in} the three-dimensional space based on the detection result of the magnetic detection unit 10.

More specifically, the calculation unit 132 uses the following expression that is a general expression of an ellipsoid.
(Equation 2)
ax ² + by ² + cz ² + 2dxy + 2eyz + 2fzx + 2gx + 2hy + 2iz + j
= 0

The calculation unit 132 obtains an equation that approximates the coefficient vector a = (a, b, c, d, e, f, g, h, i) to a three-dimensional ellipsoid based on the distribution of the values of the detection data x _meas. calculate. The calculation unit 132 may calculate the coefficient vector using, for example, a least square method. Thereby, the calculation unit 132 can approximate and derive the expression of the three-dimensional ellipsoid even if the detection data x _meas includes a detection error. Further, the calculation unit 132 can approximate and derive the expression of the three-dimensional ellipsoid even if the number m of the detection data x _meas is insufficient to draw a complete ellipsoid.

In addition, the calculation unit 132 is substantially the same when the number of detection data is too large to calculate the three-dimensional ellipsoidal expression, or when the magnetic detection unit 10 detects the state in substantially the same position and direction. If there is a lot of data, the number of detected data may be thinned out. In this case, as an example, the calculation unit 132 executes a known digital filtering process, thins out the number M of detection data to obtain m (m <M) detection data x _meas , and then performs a three-dimensional ellipsoid. Is approximated and derived.

  FIG. 3 shows an example of detection data of the magnetic detection unit 10 acquired by the detection data acquisition unit 110 according to the present embodiment. FIG. 4 shows an example of detection data after the calculation unit 132 according to the present embodiment filters and thins out the detection data. Thus, the calculation unit 132 may calculate the ellipsoidal expression after reducing the number of detection data to a predetermined number or less, thereby improving the calculation speed and reducing the processing load. Can be reduced.

FIG. 5 shows an example when the calculation unit 132 according to the present embodiment applies the distribution of the values of the detection data x _meas to a three-dimensional ellipsoid. In the physical quantity data correction apparatus 100, it is assumed that the detection data ideally distributed in a spherical shape is distorted into an ellipsoidal distribution as illustrated in FIG. 5 depending on the mounting state and the environmental state of the magnetic detection unit 10. Then, the physical quantity data correction apparatus 100 corrects the ellipsoid shape to a spherical shape.

  Next, the calculation unit 132 corrects the calculated offset of the three-dimensional ellipsoid (S240). It has been described that the distribution of spherical detection data is distorted into an ellipsoidal shape when the soft magnetic material interferes with the detection of geomagnetism in the mounting state and the environmental state of the magnetic detection unit 10. Further, when a hard magnetic material such as a magnet exists around the magnetic detection unit 10 and interferes with the detection of geomagnetism, the distribution of detection data is shifted from the origin to have an offset.

  That is, in the geomagnetic detection of the magnetic detection unit 10, when the hard magnetic material has an influence, the detection data has a spherical distribution having an offset from the origin. Further, in the geomagnetic detection of the magnetic detection unit 10, when the hard magnetic body and the soft magnetic body have an influence, the detection data has an elliptical distribution having an offset from the origin.

Therefore, when the ellipsoidal expression calculated by the calculation unit 132 has an offset from the origin, the detection data acquired by the detection data acquisition unit 110 may be affected by not only the soft magnetic material but also the hard magnetic material. Recognize. When such an offset is a vector o, the detection data x _meas can be expressed by the following equation using the detection value x _{ideal in an ideal} state.
(Equation 3)
x _meas = D · x _ideal + o

Here, since the detection data x _meas indicates a spherical distribution with the origin as the center, if the radius of the sphere is R, the following equation is established. Here, ^T (f) indicates transposition of f.
(Equation 4)
^T (x _ideal ) · x _ideal = R ²

In Equation 3, D represents a strain coefficient that distorts a spherical distribution into an elliptical shape by a soft magnetic material, and is a 3 × 3 matrix in this example. Here, the distortion coefficient D may be normalized so that the determinant is 1. The calculation unit 132 corrects the offset so that the calculated ellipsoidal expression is centered on the origin. That is, the calculation unit 132 subtracts the vector o from the detection data x _meas .

Here, from Equation 3 and Equation 4, when the inverse matrix D ^{−1 of the} matrix D exists, the following equation is obtained.
(Equation 5)
R ² = ^T (x _ideal ) · x _ideal
= ^T {D ^-1 · (x _meas -o)} · D ^-1 · (x _meas -o)
_{^{= T (x meas -o) ·}} T D -1 · D -1 · (x meas -o)
= ^T x _meas · A · x _meas - ^T o · A · x _meas - ^T x _meas · A · o + ^T o · A · o
０ 0 = ^T x _meas · A · x _meas + 2g · x _meas + j
here,
A = ^T D ⁻¹ · D ⁻¹
g = −A · o
j = ^T o, A, o-R ²

The calculation unit 132 can calculate the data w with the offset corrected by subtracting the vector o from the detection data x _{meas in} Equation 3.
(Equation 6)
w = x _meas −o = D · x _ideal

  FIG. 6 shows an example when the calculation unit 132 according to the present embodiment corrects the offset of the three-dimensional ellipsoid. Note that the calculation unit 132 does not have to execute offset correction when the calculated offset of the ellipsoidal expression is substantially zero. For example, when the calculation unit 132 is smaller than a predetermined offset value, it is assumed that there is no influence of the hard magnetic material, and the offset correction is omitted.

Next, the calculation unit 132 rotates and coordinates the three-dimensional ellipsoid (S250). From equation (6), x _ideal can be obtained by multiplying the corrected data w by the inverse matrix D ⁻¹ of D. Therefore, if D ⁻¹ can be easily obtained, D ⁻¹ may be used as a conversion coefficient. . If D ⁻¹ cannot be easily acquired, the calculation unit 132 performs coordinate conversion by rotating the ellipsoid so that the short axis and the long axis of the ellipsoid coincide with the coordinate axis in order to facilitate calculation.

The calculating unit 132 calculates the data v by multiplying the corrected data w by the matrix Q and performing coordinate conversion.
(Equation 7)
v = Q · w

  That is, by multiplying the data Q by the matrix Q, the ellipsoid, which is the distribution of the data w, is rotated so that the short axis and the long axis thereof coincide with the coordinate axis, and converted into the standard form of the ellipsoid. The calculating unit 132 calculates such a matrix Q by using a known method such as a Householder transformation and a Shift-QR method, for example. FIG. 7 shows an example when the calculation unit 132 according to the present embodiment rotates a three-dimensional ellipsoid and converts it into a standard format.

Next, the calculation unit 132 converts the three-dimensional ellipsoid into a sphere (S260). For example, the calculation unit 132 performs correction for conversion into a sphere by adjusting the axial length while preserving the volume of the ellipsoid. Such correction may be calculated as follows:
(Equation 8)
s = κ− ¹ · Λ ^1/2 · v

Here, the distribution of the vector s in Expression 8 satisfies the following relational expression and indicates a sphere in the coordinate system of s. The calculation unit 132 calculates the matrix κ and the eigenvalue matrix Λ so as to obtain such a vector s, and converts the three-dimensional ellipsoid into a sphere. FIG. 8 shows an example when the calculation unit 132 according to the present embodiment converts a three-dimensional ellipsoid into a sphere.
(Equation 9)
^T s · s = (R / κ) ²

Here, since the calculator 132 has rotated the ellipsoid using the matrix Q, the rotated angle may be restored. That is, the calculation unit 132 converts the detection data into a data vector t expressed by the following equation.
(Equation 10)
t = Q ⁻¹ · s = Q ⁻¹ · κ ⁻¹ · Λ ^1/2 · v = Q ⁻¹ · κ ⁻¹ · Λ ^1/2 · Q · w
= Q ⁻¹ · κ ⁻¹ · Λ ^1/2 · Q · (x _meas −o)
= Q ^-1 · κ ^-1 · Λ ^1/2 · Q · x _meas '

That is, when the detection data w after the offset correction is replaced with the detection data x _meas ′, or when the offset is detection data that does not require offset correction, the calculation unit 132 sets the conversion coefficient Z as follows: To calculate.
(Equation 11)
Z = Q ^-1 · κ ^-1 · Λ ^1/2 · Q

  As described above, the calculation unit 132 according to the present embodiment calculates the conversion coefficient Z having the conversion coefficient for converting a three-dimensional ellipsoid into a three-dimensional sphere as an element. Note that when the detection data acquisition unit 110 acquires detection data of an n-dimensional physical quantity, the calculation unit 132 may calculate a conversion coefficient for converting an n-dimensional ellipsoid into an n-dimensional sphere corresponding to the detection data. .

Next, the determination unit 134 receives the conversion coefficient Z from the calculation unit 132 and determines the degree of similarity between the conversion coefficient Z and the plurality of correction parameters C _k received from the parameter acquisition unit 120. (S270). Determination unit 134, a conversion coefficient Z, based on the norm, such as between the respective plurality of correction parameters C _k, may determine the similarity. In this case, for example, the determination unit 134 determines that the correction parameter having the smallest norm among the plurality of correction parameters has the highest similarity.

Alternatively, the determination unit 134, based on the sum or the like of the square sum or the absolute value of each element of the difference between the transform coefficients Z and a plurality of correction parameters C _k, may determine similarity. In this case, as an example, the determination unit 134 determines the similarity of the correction parameter that minimizes the sum of squares of the elements of the difference among the plurality of correction parameters as the highest similarity.

  Next, the determination unit 134 specifies a correction parameter to be used for correction based on the similarity (S280). For example, the determination unit 134 identifies the correction parameter determined to have the highest similarity as the correction parameter used for correction.

Next, the correction unit 140 corrects the detection data using the specified correction parameter (S290). That is, the correction unit 140 corrects the detection data using the correction parameter determined to have the highest similarity among the plurality of correction parameters C _k . For example, when the specified correction parameter is C _k1 , the correction unit 140 calculates the corrected data as C _k1 · x _meas (or C _k1 · x _meas ').

  As described above, the physical quantity data correction apparatus 100 according to the present embodiment calculates the conversion coefficient for correcting the detection data based on the detection data of the magnetic detection unit 10, and among the plurality of correction parameters acquired by the parameter acquisition unit, The detection data is corrected using the correction parameter most similar to the conversion coefficient. Since the physical quantity data correction apparatus 100 calculates a conversion coefficient for correcting the detection data based on the acquired detection data, if the elliptical distribution based on the detection data can be acquired with high accuracy, the detection data is calculated using the calculated conversion coefficient. It may be corrected.

  However, for example, when a protective cover including a magnetic shield is attached to and detached from a device in which the physical quantity data correction device 100 is mounted, when the device is stood and fixed to the protective cover or the like, a magnetic card or the like is attached to the device. In the case of insertion and removal, it may be possible to assume in advance a situation in which distortion is generated with respect to detection data of geomagnetism, such as attachment and detachment of the power cable and attachment and detachment of the battery. Further, the distortion caused in the detection data by the magnetic material inside the apparatus or the like changes due to mounting deviation when the physical quantity data correction apparatus 100 is mounted on the apparatus or the like. The amount of such deviation and the distortion generated in the detection data can be detected in advance.

  In this way, when the physical quantity data correction apparatus 100 can detect and calculate the conversion coefficient in advance, it is not necessary to repeat calculation of substantially the same conversion coefficient by calculating the correction coefficient in advance. Further, since the physical quantity data correction apparatus 100 can acquire more detection data in advance and acquire an accurate distribution of data values, the corresponding correction coefficient is accurately calculated and the detection data is reused. Thus, accurate correction can be reproduced. Accordingly, when the physical quantity data correction apparatus 100 according to the present embodiment can presuppose distortion with respect to the detection data of geomagnetism, the distribution due to the distortion of the detection data is accurately measured in advance to calculate a conversion coefficient, and a plurality of correction parameters are obtained. To do.

  As described above, the physical quantity data correction apparatus 100 corresponds to a plurality of mounting forms of the magnetic detection unit 10 and a plurality of environmental forms of the magnetic detection unit that are assumed in advance, and sets a plurality of correction parameters based on accurate detection results in advance. Get. That is, for example, at least a part of the plurality of correction parameters is a conversion coefficient for converting an n-dimensional ellipsoid in the n-dimensional coordinate space calculated from the detection data in the plurality of mounting forms into an n-dimensional sphere. At least some of the plurality of correction parameters are conversion coefficients for converting an n-dimensional ellipsoid in the n-dimensional coordinate space calculated from detection data in a plurality of environment forms into an n-dimensional sphere.

  Therefore, the physical quantity data correction apparatus 100 is substantially the same as the corresponding correction parameter when an accurate data value distribution can be acquired without noise or the like being superimposed on the detection data acquired from the apparatus on which the magnetic detection unit 10 is mounted. Therefore, the conversion coefficient is calculated. Therefore, the physical quantity data correction apparatus 100 can select and correct an accurate correction parameter substantially the same as the calculated conversion coefficient by selecting a correction parameter having the highest similarity.

  For example, the physical quantity data correction apparatus 100 corresponds to a conversion coefficient when the distribution is approximated to an elliptical shape even if the distribution of data values becomes inaccurate due to a reduction in the number of acquired detection data. As long as the distribution is similar to the distribution, the correct correction parameter can be selected and corrected by using the correction parameter having the highest similarity with the conversion coefficient calculated from the detection data. In addition, even if noise or the like is superimposed on the acquired detection data, the physical quantity data correction apparatus 100 similarly has a distribution similar to the correct conversion coefficient when the distribution is approximated to an elliptical shape. Correct correction parameters can be selected and corrected.

  Further, since the physical quantity data correction apparatus 100 selects the correction parameter according to the conversion coefficient calculated from the detection data, it does not use other sensors or the like that detect the status of the magnetic detection unit 10 other than the magnetic detection unit 10. The detection data can be corrected. That is, the physical quantity data correction apparatus 100 can execute an accurate correction operation without increasing the circuit scale of the entire sensor.

  For example, when the detection data acquisition unit 110 cannot acquire a sufficient number of data points to acquire an elliptical distribution as the data distribution, the amount of movement of the device in which the physical quantity data correction device 100 is mounted is insufficient. If the distribution of the detected data cannot be detected accurately, if the device passes through the area affected by the soft magnetic material and hard magnetic material, and the distortion of the geomagnetic measurement changes dynamically, and the soft magnetic material When a material, a hard magnetic material, or the like moves around the apparatus, various noise components or the like are superimposed on the detection data, and the distribution of the detection data may not be obtained accurately.

  Thus, in the case of detection data with insufficient data distribution, or when extremely large noise or the like is superimposed on the acquired detection data, the conversion coefficient calculated corresponding to the detection data is unrealistic and extreme May result in a negative value. However, the physical quantity data correction apparatus 100 according to the present embodiment selects a correction parameter having a high similarity to the calculated conversion coefficient from the previously calculated realistic correction parameters. The operation can continue.

  The physical quantity data correction apparatus 100 according to the present embodiment described above has described that the conversion coefficient is calculated from the acquired detection data and compared with the correction parameter calculated in advance. Instead, the physical quantity data correction apparatus 100 may calculate a determination parameter based on the detection data, which is different from the conversion coefficient, and compare it with a determination parameter acquired corresponding to the correction parameter calculated in advance.

  In this case, for example, the parameter acquisition unit 120 further acquires a plurality of determination parameters used for similarity determination corresponding to each of the plurality of correction parameters. The determination unit 134 determines the similarity between the conversion coefficient calculated by the calculation unit 132 and each of the plurality of determination parameters. Here, the calculation unit 132 calculates a coefficient corresponding to the determination parameter as a conversion coefficient. For example, when the parameter acquisition unit 120 acquires the data vector t of Formula 10, the data vector s of Formula 8, the data vector v of Formula 7, or the data vector w of Formula 6 as a determination parameter, the calculation unit In step 132, instead of the conversion coefficient Z, a corresponding data vector is calculated as the conversion coefficient.

In addition, the parameter acquisition unit 120 acquires, as a determination parameter, a vector, a matrix, or the like calculated corresponding to the detection data, such as the matrix A or the matrix Q in Formula 5 or the matrix κ or the eigenvalue matrix Λ in Formula 8. In this case, the calculation unit 132 calculates a corresponding matrix, vector, and the like as a conversion coefficient. The parameter acquisition unit 120 may calculate an inverse matrix of these matrices. For example, the parameter acquisition unit 120 may calculate an inverse matrix Z ⁻¹ of the matrix Z. In this way, the parameter acquisition unit 120 acquires the vector, matrix, inverse matrix, and the like obtained in the process of calculating a plurality of correction parameters in association with the correction parameter as a determination parameter together with the correction parameter.

  The correction unit 140 corrects the detection data using a correction parameter corresponding to the determination parameter determined to have the highest similarity among the plurality of determination parameters. As a result, the parameter selection unit 130 can determine the degree of similarity using the data vector and matrix in the process of calculating the conversion coefficient Z. Therefore, the calculation unit 132 can calculate the correction parameter without calculating up to the conversion coefficient Z. It can be selected and the burden of calculation operation can be reduced.

  Instead of this, the physical quantity data correction apparatus 100 may correct the detection data by selecting a correction parameter according to the distribution of the detection data. In this case, the parameter acquisition unit 120 acquires the distribution shape of the detection data corrected by the correction parameter in association with each of the plurality of correction parameters. That is, the parameter acquisition unit 120 associates the distribution shape (that is, the n-dimensional ellipsoid in the n-dimensional coordinate space) that should be the distribution of the data values of the detection data before being corrected by the correction parameter with the correction parameter. To obtain the correction parameter.

  The calculation unit 132 calculates an expression when approximated to an n-dimensional ellipsoid based on the detection data. Then, the determination unit 134 determines the degree of similarity between the n-dimensional ellipsoid calculated by the calculation unit 132 and each of the plurality of n-dimensional ellipsoids acquired by the parameter acquisition unit 120. As described above, the parameter selection unit 130 selects a correction parameter associated with a distribution shape closer to the distribution of the detection data among the plurality of distribution shapes. Thereby, the calculation operation of the calculation unit 132 can be further reduced.

  FIG. 9 shows a configuration example of the magnetic detection device 200 according to the present embodiment. The magnetic detection device 200 includes the physical quantity data correction device 100 described in the present embodiment and a magnetic offset vector estimation unit 210.

The magnetic detection apparatus 200 according to the present embodiment is an example of an apparatus in which the physical quantity data correction apparatus 100 does not execute the correction of the offset vector o shown in Equation 6. For example, the physical quantity data correction apparatus 100 calculates the data vector t of Formula 10 as the following formula.
(Equation 12)
t = Q ⁻¹ · s = Q ⁻¹ · κ ⁻¹ · Λ ^1/2 · v = Q ⁻¹ · κ ⁻¹ · Λ ^1/2 · Q · x _meas
= Q ^-1 · κ ^-1 · Λ ^1/2 · Q · x _meas

  Therefore, when calculating the conversion coefficient Z, the physical quantity data correction apparatus 100 calculates the same coefficient as the equation (11). That is, in the physical quantity data correction apparatus 100 shown in FIG. 9, the operations other than the correction of the offset vector o are substantially the same as those already described, and thus the description thereof is omitted here.

  The magnetic offset vector estimation unit 210 is connected to the physical quantity data correction apparatus 100, and estimates and cancels the magnetic offset vector from the magnetic data corrected by the physical quantity data correction apparatus 100. As described above, the magnetic offset vector estimation unit 210 according to the present embodiment corrects the influence of the physical quantity data correction apparatus 100 distorting the elliptical shape generated by the soft magnetic material (by converting the data value distribution into a spherical shape). From the above, the offset caused by the hard magnetic material is corrected.

The magnetic offset vector estimation unit 210 corrects the offset using, for example, Equation 6 below. Instead, the magnetic offset vector estimation unit 210 uses a spherical formula (for example, (x−a) ² + (y−b) ² + (z−c) ² ) that applies to the data converted by the physical quantity data correction apparatus 100. = R ² ) may be derived and offset (a, b, c) may be calculated and corrected.

  As described above, the magnetic detection device 200 can correct and reduce the influence of the interference component of the soft magnetic material and the hard magnetic material on the geomagnetic measurement based on the output of the magnetic detection unit 10. Thus, the magnetic detection device 200 can output a magnetic detection result with reduced interference components without increasing the circuit scale of the entire sensor.

  Here, since the magnetic detection device 200 outputs the magnetic detection result with reduced interference components, the magnitude and direction of the geomagnetism with respect to the magnetic detection device 200 can be output more accurately. That is, by providing the magnetic detection device 200, it is possible to provide an azimuth angle detection device that detects the azimuth angle of the magnetic detection device 200 according to the magnetic detection result of the magnetic detection device 200.

  The azimuth angle detection device may output an azimuth angle according to a difference between a predetermined direction of the magnetic detection device 200 and the detected geomagnetism direction. Such an azimuth angle detection device, for example, reduces the installation area and capacity by mounting a portable device or the like, and outputs the azimuth angle of the portable device based on the output of the magnetic detection unit 10. Can do.

  In addition, the magnetic detection apparatus 200 of this embodiment demonstrated correcting the offset, after the physical quantity data correction apparatus 100 converted distribution of a data value into a spherical shape. Instead, when the physical quantity data correction apparatus 100 performs offset correction and data value distribution conversion, the magnetic detection apparatus 200 does not have to execute offset correction.

  FIG. 10 shows an example of the hardware configuration of a computer 1900 that functions as the physical quantity data correction apparatus 100 according to the present embodiment. A computer 1900 according to the present embodiment is mounted inside a device such as a portable device, for example. Alternatively, the computer 1900 may be provided outside a device such as a portable device, receive an output from a magnetic detection unit or the like from the portable device, and transmit the corrected magnetic detection result to the portable device. . In this case, for example, the computer 1900 transmits and receives wirelessly to and from the portable device.

  A computer 1900 according to this embodiment is connected to a CPU peripheral unit having a CPU 2000, a RAM 2020, a graphic controller 2075, and a display device 2080 that are connected to each other by a host controller 2082, and to the host controller 2082 by an input / output controller 2084. A communication interface 2030, a storage unit 2040, an input / output unit 2060, a ROM 2010, a card slot 2050, and an input / output chip 2070.

  The host controller 2082 connects the RAM 2020 to the CPU 2000 and the graphic controller 2075 that access the RAM 2020 at a high transfer rate. The CPU 2000 operates based on programs stored in the ROM 2010 and the RAM 2020 and controls each unit. The graphic controller 2075 acquires image data generated by the CPU 2000 or the like on a frame buffer provided in the RAM 2020 and displays it on the display device 2080. Instead of this, the graphic controller 2075 may include a frame buffer for storing image data generated by the CPU 2000 or the like.

  The input / output controller 2084 connects the host controller 2082 to the communication interface 2030, the storage unit 2040, and the input / output unit 2060, which are relatively high-speed input / output devices. The communication interface 2030 communicates with other devices via a network. Storage unit 2040 stores programs and data used by CPU 2000 in computer 1900. The storage unit 2040 is a nonvolatile memory, such as a flash memory or a hard disk.

  The input / output unit 2060 is connected to the connector 2095, transmits / receives a program or data to / from the outside, and provides the storage unit 2040 via the RAM 2020. The input / output unit 2060 may transmit and receive externally using a standardized connector and communication method. In this case, the input / output unit 2060 is a standard such as USB, IEEE 1394, HDMI (registered trademark), or Thunderbolt (registered trademark). May be used. Further, the input / output unit 2060 may transmit and receive with the outside using a wireless communication standard such as Bluetooth (registered trademark).

  The input / output controller 2084 is connected to the ROM 2010, the card slot 2050, and the input / output chip 2070, which are relatively low-speed input / output devices. The ROM 2010 stores a boot program that the computer 1900 executes at startup and / or a program that depends on the hardware of the computer 1900. The card slot 2050 reads a program or data from the memory card 2090 and provides it to the storage unit 2040 via the RAM 2020. The input / output chip 2070 connects the card slot 2050 to the input / output controller 2084 and, for example, various input / output devices via the parallel port, serial port, keyboard port, mouse port, etc. You may connect to.

  A program provided to the storage unit 2040 via the RAM 2020 is stored by a user via the input / output unit 2060 or stored in a recording medium such as the memory card 2090. The program is read from the recording medium, installed in the storage unit 2040 in the computer 1900 via the RAM 2020, and executed by the CPU 2000.

  The program is installed in the computer 1900, and causes the computer 1900 to function as the detection data acquisition unit 110, the parameter acquisition unit 120, the parameter selection unit 130, the correction unit 140, and the like.

  Information processing described in the program is read into the computer 1900, and the detection data acquisition unit 110, parameter acquisition unit 120, parameter selection, which are specific means in which the software and the various hardware resources described above cooperate. Functions as the unit 130, the correction unit 140, and the like. Then, by realizing the calculation or processing of information according to the purpose of use of the computer 1900 in the present embodiment by this specific means, the specific physical quantity data correction device 100, the magnetic detection device 200 according to the purpose of use, and An azimuth angle detection device is constructed.

  As an example, when communication is performed between the computer 1900 and an external device or the like, the CPU 2000 executes a communication program loaded on the RAM 2020 and executes a communication interface based on the processing content described in the communication program. A communication process is instructed to 2030. The communication interface 2030 receives transmission data stored in a transmission buffer area provided on a storage device connected via the RAM 2020, the storage unit 2040, the memory card 2090, or the input / output unit 2060 under the control of the CPU 2000. The data is read and transmitted to the network, or the received data received from the network is written into a reception buffer area or the like provided on the storage device. As described above, the communication interface 2030 may transfer transmission / reception data to / from the storage device by the DMA (Direct Memory Access) method. Instead, the CPU 2000 transfers the storage device or the communication interface 2030 as the transfer source. The transmission / reception data may be transferred by reading the data from the data and writing the data to the communication interface 2030 or the storage device of the transfer destination.

  In addition, the CPU 2000 uses the RAM 2020 to transfer all or necessary portions from among files or databases stored in the storage unit 2040, the memory card 2090, or a storage device connected via the input / output unit 2060 by DMA transfer or the like. And various processes are performed on the data on the RAM 2020. Then, CPU 2000 writes the processed data back to the storage device by DMA transfer or the like. In such processing, since the RAM 2020 can be regarded as temporarily holding the contents of the storage device, in the present embodiment, the RAM 2020 and the storage device are collectively referred to as a memory, a storage unit, or a storage device. Various types of information such as various programs, data, tables, and databases in the present embodiment are stored on such a storage device and are subjected to information processing. Note that the CPU 2000 can also store a part of the RAM 2020 in the cache memory and perform reading and writing on the cache memory. Even in such a form, the cache memory bears a part of the function of the RAM 2020. Therefore, in the present embodiment, the cache memory is also included in the RAM 2020, the memory, and / or the storage device unless otherwise indicated. To do.

  In addition, the CPU 2000 performs various operations, such as various operations, information processing, condition determination, information search / replacement, etc., described in the present embodiment, specified for the data read from the RAM 2020 by the instruction sequence of the program. Is written back to the RAM 2020. For example, when performing the condition determination, the CPU 2000 determines whether the various variables shown in the present embodiment satisfy the conditions such as large, small, above, below, equal, etc., compared to other variables or constants. When the condition is satisfied (or not satisfied), the program branches to a different instruction sequence or calls a subroutine.

  Further, the CPU 2000 can search for information stored in a file or database in the storage device. For example, in the case where a plurality of entries in which the attribute value of the second attribute is associated with the attribute value of the first attribute are stored in the storage device, the CPU 2000 displays the plurality of entries stored in the storage device. The entry that matches the condition in which the attribute value of the first attribute is specified is retrieved, and the attribute value of the second attribute that is stored in the entry is read, thereby associating with the first attribute that satisfies the predetermined condition The attribute value of the specified second attribute can be obtained.

  The program or module shown above may be stored in an external recording medium. As the recording medium, in addition to the memory card 2090, an optical recording medium such as a DVD, Blu-ray (registered trademark) or CD, a magneto-optical recording medium such as an MO, a tape medium, a semiconductor memory such as an IC card, or the like is used. be able to. Further, a storage device such as a hard disk or a RAM provided in a server system connected to a dedicated communication network or the Internet may be used as a recording medium, and the program may be provided to the computer 1900 via the network.

  As mentioned above, although this invention was demonstrated using embodiment, the technical scope of this invention is not limited to the range as described in the said embodiment. It will be apparent to those skilled in the art that various modifications or improvements can be added to the above-described embodiment. It is apparent from the scope of the claims that the embodiments added with such changes or improvements can be included in the technical scope of the present invention.

  The order of execution of each process such as operations, procedures, steps, and stages in the apparatus, system, program, and method shown in the claims, the description, and the drawings is particularly “before” or “prior to”. It should be noted that the output can be realized in any order unless the output of the previous process is used in the subsequent process. Regarding the operation flow in the claims, the description, and the drawings, even if it is described using “first”, “next”, etc. for convenience, it means that it is essential to carry out in this order. It is not a thing.

DESCRIPTION OF SYMBOLS 10 Magnetic detection part, 100 Physical quantity data correction apparatus, 110 Detection data acquisition part, 120 Parameter acquisition part, 130 Parameter selection part, 132 Calculation part, 134 Judgment part, 136 Identification part, 140 Correction part, 200 Magnetic detection apparatus, 210 Magnetic Offset vector estimation unit, 1900 computer, 2000 CPU, 2010 ROM, 2020 RAM, 2030 communication interface, 2040 storage unit, 2050 card slot, 2060 input / output unit, 2070 input / output chip, 2075 graphic controller, 2080 display device, 2082 host・ Controller, 2084 I / O controller, 2090 Memory card, 2095 connector

Claims (17)

A detection data acquisition unit for acquiring detection data of physical quantities in a plurality of axial directions;
A parameter acquisition unit for acquiring a plurality of correction parameters for correcting the physical quantities in the plurality of axis directions;
A parameter selection unit that selects a correction parameter used for correction out of the plurality of correction parameters based on the distribution of detection data in the plurality of axis directions;
A correction unit for correcting the detection data using the selected correction parameter;
A physical quantity data correction apparatus comprising: The parameter selection unit
A calculation unit that calculates a conversion coefficient according to the distribution of the detection data;
A determination unit that determines the degree of similarity between the conversion coefficient calculated by the calculation unit and each of the plurality of correction parameters acquired by the parameter acquisition unit;
A specifying unit for specifying the correction parameter used for correction among the plurality of correction parameters based on the similarity;
The physical quantity data correction device according to claim 1, comprising:   The calculation unit calculates an n-dimensional ellipsoid that approximates a distribution of the detection data in an n-dimensional (n is an integer of 2 or more) coordinate space expressed by the plurality of axis directions, and converts the n-dimensional ellipsoid to n The physical quantity data correction apparatus according to claim 2, wherein a conversion coefficient to be converted into a dimension sphere is calculated.   The physical quantity data correction apparatus according to claim 2, wherein the determination unit determines the similarity based on a norm between the conversion coefficient and each of the plurality of correction parameters.   The physical quantity data correction apparatus according to claim 4, wherein the determination unit determines that a correction parameter that minimizes the norm among the plurality of correction parameters has the highest similarity.   The physical quantity data correction according to any one of claims 2 to 5, wherein the correction unit corrects detection data using a correction parameter determined to have the highest similarity among the plurality of correction parameters. apparatus. The parameter acquisition unit acquires a determination parameter used for determination of the degree of similarity corresponding to each of the plurality of correction parameters,
The determination unit determines the similarity between the conversion coefficient calculated by the calculation unit and each of the plurality of determination parameters;
The physical quantity data correction according to claim 2, wherein the correction unit corrects detection data using a correction parameter corresponding to a determination parameter determined to have the highest similarity among the plurality of determination parameters. apparatus. The parameter acquisition unit acquires a plurality of distribution shapes of detection data that are respectively corrected by the correction parameters in association with the plurality of correction parameters,
The physical quantity data correction apparatus according to claim 1, wherein the parameter selection unit selects a correction parameter associated with a distribution shape closer to the distribution of the detection data among the plurality of distribution shapes.   The physical quantity data correction device according to claim 1, wherein the detection data acquisition unit acquires magnetic data output from the magnetic detection units in the plurality of axial directions.   The physical quantity data correction device according to claim 9, wherein at least some of the plurality of correction parameters respectively correspond to a plurality of mounting forms of the magnetic detection unit.   The physical quantity data correction apparatus according to claim 10, wherein at least some of the plurality of correction parameters respectively correspond to a plurality of environmental forms of the magnetic detection unit.   The at least part of the plurality of correction parameters is a conversion coefficient for converting an n-dimensional ellipsoid in an n-dimensional coordinate space calculated from detection data in the plurality of implementations into an n-dimensional sphere. Or the physical quantity data correction device according to 11; The physical quantity data correction device according to any one of claims 9 to 12,
A magnetic offset vector estimation unit that estimates and cancels a magnetic offset vector from the magnetic data corrected by the physical quantity data correction device;
A magnetic detection device comprising: A magnetic detection device according to claim 13,
An azimuth angle detection device that detects an azimuth angle of the magnetic detection device according to a magnetic detection result of the magnetic detection device.   A program that causes a computer to function as the physical quantity data correction device according to any one of claims 1 to 12.   A program causing a computer to function as the magnetic detection device according to claim 13.   The program which makes a computer function as an azimuth angle detection apparatus of Claim 14.

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