JP2016031245A - Physical quantity data correction 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 the plurality of axial directions, a generation unit for correcting the detection data acquired by the detection data acquisition unit by using each of the correction parameters acquired by the parameter acquisition unit, and for generating each distribution of correction data corresponding to each of the plurality of correction parameters, and a data selection unit for selecting a correction parameter used for correction of the detection data on the basis of the distribution of the corrected detection data corresponding to each of the plurality of correction parameters; and an orientation angle detection device and a program thereof.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a physical quantity data correction 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 detection data of physical quantities in a plurality of axes, a parameter acquisition unit that acquires a plurality of correction parameters for correcting physical quantities in a plurality of axes, and a parameter acquisition unit Each of the plurality of correction parameters acquired by the detection data acquisition unit for correcting the detection data acquired, and generating a corrected detection data distribution corresponding to each of the plurality of correction parameters, A physical quantity data correction device, an azimuth angle detection device, and a program comprising: a data selection unit that selects a correction parameter used for correction of detection data based on a distribution of detection data after correction corresponding to each of a plurality of correction parameters I will provide a.

  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. The modification of the physical quantity data correction apparatus 100 which concerns on this embodiment is shown. The operation | movement flow of the modification 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 152 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 152 according to the present embodiment applies the distribution of detected data values to a three-dimensional ellipsoid is shown. An example when the calculation part 152 which concerns on this embodiment correct | amends the offset of a three-dimensional ellipsoid is shown. An example in which the calculation unit 152 according to the present embodiment converts a three-dimensional ellipsoid into a standard format by rotating the three-dimensional ellipsoid is shown. An example in which the calculation unit 152 according to the present embodiment converts a three-dimensional ellipsoid into a sphere is shown. The structural example of the azimuth angle 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 corrects the acquired physical quantity detection result using a plurality of correction parameters calculated in advance, and calculates a spatial distribution of the plurality of detection results after correction and a predetermined distribution. According to the degree of similarity, a correction parameter to be used for correction is selected and a detection result after correction is acquired.

  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 generation unit 130, and a data selection 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 such as the magnetic detection unit 10. 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 the plurality of environmental forms of the magnetic detection unit 10. 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 and a plurality of environment forms of the magnetic detection unit 10. Here, for example, one detection data x _meas has m data vectors, and each of the data vectors is a data vector on an n-dimensional space having n elements. Each of the _k correction parameters C _k is an n × n matrix for converting n elements of each data vector.

The generation unit 130 corrects the detection data acquired by the detection data acquisition unit 110 using each of the plurality of correction parameters acquired by the parameter acquisition unit 120, and the corrected detection data corresponding to each of the plurality of correction parameters. Each distribution is generated. That is, the generation unit 130 is connected to the detection data acquisition unit 110 and the parameter acquisition unit 120, and uses the plurality of correction parameters C _k received from the parameter acquisition unit 120 for the detection data x _meas received from the detection data acquisition unit 110. A plurality of corrected detection data _xc are generated.

For example, the generation unit 130 corrects each of the _k correction parameters C _k by multiplying each of the m correction data C _k by the m detection data x _meas as shown in the following equation, and a plurality (k sets) of corrected detection data x _c is generated.
(Equation 1)
x _c — _k = C _k · x _meas

The generation unit 130 generates a set of detection data x _c after correction for one correction parameter, and the set of detection data x _c represents a data vector in an n-dimensional space having n elements. Includes m. Then, the m data vectors x _c forms a distribution of data values in the n-dimensional space. That is, the generation unit 130 generates k sets of corrected detection data distributions corresponding to each of the _k correction parameters C _k . In this embodiment, the k sets of corrected detection data and the distribution of k data values are represented as _{xc_k} .

Data selector 140 is connected to the generator 130, based on the distribution x _{c_k} detection data after correction corresponding to each of the plurality of correction parameters C _k, it selects a correction parameter used for correction of the detection data. Data selection unit 140, based on the distribution x _{c_k} detection data after correction corresponding to each of the plurality of correction parameters C _k, selects the detected data after the correction to be output. That is, the data selection unit 140 selects one set of corrected detection data as detection data corrected by the correction parameter to be used for correction among the k sets of corrected detection data. In this case, the data selection unit 140 has selected a correction parameter corresponding to the selected set of corrected detection data as a correction parameter to be used for correction.

  The data selection unit 140 selects a correction parameter to be used for correcting the detection data in accordance with the similarity between the corrected detection data distribution and a predetermined distribution. For example, the data selection unit 140 detects the detection data according to the degree of similarity between the corrected detection data distribution and the n-dimensional sphere in the n-dimensional coordinate space (n is an integer of 2 or more) expressed by a plurality of axis directions. The correction parameter used for the correction is selected. For example, the data selection unit 140 selects, as correction detection data to be output, a distribution having the highest similarity to the distribution of the n-dimensional sphere among the distributions in the n-dimensional coordinate space of the k sets of detection data after correction. select. The data selection unit 140 outputs the selected detection data after correction as detection data corrected with a correction parameter to be used for correction.

  As described above, the physical quantity data correction apparatus 100 according to the present embodiment corrects the acquired detection data using the acquired plurality of correction parameters, and the degree of similarity with a predetermined distribution from the corrected detection data. In response to this, detection data appropriately corrected is selected and output. The operation in which the physical quantity data correction apparatus 100 selects and outputs 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 an appropriate correction parameter that reduces the interference component of the detection data from among a plurality of correction parameters, and corrects the detection data with the appropriate correction parameter. Output later detection data.

First, the detection data acquisition unit 110 acquires detection data x _meas from the magnetic detection unit 10 (S210). Here, an example will be described in which the detection data x _meas is a three-dimensional vector, and the detection data acquisition unit 110 acquires detection data x _meas having m data vectors. The detection data acquisition unit 110 supplies the acquired detection data to the generation 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 generation 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 generation 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 generation unit 130 reads the plurality of correction parameters stored in the storage unit. It's okay. 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 generation unit 130 generates a plurality of corrected detection data (S230). That is, the generation unit 130 corrects each set of detection data x _meas using _k correction parameters C _k , and generates k sets of corrected detection data x _{c_k} . Generator 130, as in the example shown in equation (1) may generate the detection data x _{c_k} corrected by multiplying a correction parameter C _k and the detected data x _meas, alternatively, predetermined The corrected detection data _{xc_k} may be generated by performing the calculated operation.

The calculation executed by the generation unit 130 to generate detection data after correction is predetermined according to the relationship between the correction parameter C _k and the detection data x _meas . The calculation (that is, multiplication of the correction parameter C _k and the detection data x _meas ) executed by the generation unit 130 of the present embodiment is based on derivation of the correction parameter C _k described later.

  Next, the data selection unit 140 selects corrected detection data to be output among the plurality of corrected detection data generated by the generation unit 130 (S240). 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 correction parameter for reducing the interference caused by the material that distorts the direction of the geomagnetism is a parameter for correcting the distribution of the three-dimensional ellipsoid of the detection data into the original three-dimensional sphere. That is, the parameter acquisition unit 120 acquires a correction parameter for converting an n-dimensional ellipsoid approximating the distribution of detection data in an n-dimensional coordinate space expressed by a plurality of axis directions into an n-dimensional sphere.

  In addition, the degree to which the geomagnetism is distorted varies depending on the size of the soft magnetic material, the distance from the magnetic detection unit 10, the material, and the like. For example, when a protective cover including a magnetic shield is attached to or detached from a device on which the magnetic detection unit 10 is mounted, when the device is stood and fixed to the protective cover or the like, a magnetic card or the like is inserted into or removed from the device In this case, the distribution of the three-dimensional ellipsoid of the detection data changes depending on the environment of the magnetic detection unit 10 such as the attachment and detachment of the power cable and the attachment and detachment of the battery.

  In addition, the distortion caused in the detection data by the magnetic material inside the apparatus on which the magnetic detection unit 10 is mounted also changes due to mounting deviation that occurs when the magnetic detection unit 10 is mounted on the apparatus or the like. Therefore, the physical quantity data correction apparatus 100 must select an appropriate correction parameter (that is, correct to the original three-dimensional sphere) according to a situation in which distortion is generated in the geomagnetic detection data.

  On the other hand, the magnetic detection unit 10 determines whether or not it is a situation in which distortion is generated with respect to geomagnetic detection data, and in which of the above-described situations that cause distortion. Have difficulty. In addition to the magnetic detection unit 10, a sensor for detecting such a situation may be provided in a device on which the magnetic detection unit 10 is mounted. In this case, the scale of the entire system increases, and the cost of the sensor is increased. It will increase.

  In view of this, when the physical quantity data correction apparatus 100 according to the present embodiment can presume a distortion with respect to the detection data of geomagnetism, a distribution due to the distortion of the detection data is accurately measured in advance, and a plurality of corresponding correction parameters are acquired. 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.

Then, the physical quantity data correction apparatus 100 corrects the detection data for each acquired correction parameter, and converts the correction parameter for converting the distribution into the distribution most similar to a predetermined distribution (that is, a three-dimensional sphere) to correct the detection data. Select as a correction parameter to be used. For example, the data selection unit 140 outputs the corrected detection data whose distribution in the n-dimensional coordinate space has the highest similarity to the n-dimensional sphere among the plurality of corrected detection data x _{c_k} after the correction to be output. Select as detection data.

That is, the data selection unit 140, as an example, among the detected data x _{c_k} corrected, selecting the best matches (the smallest error) detection data x _{c_k} the following equation. Here, ^T (f) indicates the transpose of f, and R is the radius of the n-dimensional sphere.
(Equation 2)
^T (x _{c — k} ) · x _c — _k = R ²

In order to select such detection data, the data selection unit 140 corrects the minimum square error when the distribution in the n-dimensional coordinate space is approximated by an n-dimensional sphere among the corrected detection data _{xc_k.} These detection data may be selected as corrected detection data to be output. Thereby, the physical quantity data correction apparatus 100 of the present embodiment can select a correction parameter that can correct the distribution of the data value of the detection data x _meas to the distribution closest to the sphere among the acquired correction parameters C _k , Detection data corrected to a distribution closest to a sphere can be output.

Instead, the data selection unit 140 approximates the distribution of the corrected detection data _{xc_k} with an ellipsoid in the n-dimensional space, and the ratio of the major axis to the minor axis of the ellipsoid is closest to the n-dimensional sphere ( As an example, corrected detection data (closest to 1) may be selected as corrected detection data to be output. Here, a specific method for approximating the distribution of the corrected detection data _{xc_k} with an ellipsoid in the n-dimensional space will be described later.

  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 accurate correction coefficient can be acquired in advance. In addition, the physical quantity data correction apparatus 100 can accurately detect a plurality of correction parameters in advance corresponding to a plurality of presumed mounting forms of the magnetic detection unit 10 and a plurality of environmental forms of the magnetic detection unit 10 in advance. Can be obtained based on. Therefore, the physical quantity data correction apparatus 100 can correct detection data more accurately in correspondence with a plurality of assumed mounting forms of the magnetic detection unit 10 and a plurality of environmental forms of the magnetic detection unit 10. .

  Then, the physical quantity data correction apparatus 100, for example, even if the number of acquired detection data is reduced and the data value distribution cannot be accurately acquired, the corrected data distribution is the distribution closest to a sphere. Since a correction parameter that can be corrected is selected, an appropriate correction parameter can be selected and corrected from the acquired correction parameters. The physical quantity data correction apparatus 100 selects a correction parameter that can correct the corrected data distribution to a distribution that is closest to a sphere even if noise or the like is superimposed on the acquired detection data. Appropriate correction parameters can be selected and corrected.

  Further, since the physical quantity data correction apparatus 100 selects a correction parameter according to the distribution of detection data after correction, without using other sensors or the like that detect the status of the magnetic detection unit 10 other than the magnetic detection unit 10. 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.

  Further, for example, when the detection data acquisition unit 110 cannot acquire a sufficient number of data points to acquire the data distribution, the amount of movement of the device in which the physical quantity data correction device 100 is mounted is insufficient and the distribution of the detection data Cannot be detected accurately, when the device passes through the affected area of the soft magnetic material and hard magnetic material, and the distortion of the geomagnetic measurement changes dynamically, and the soft magnetic material and hard magnetic material When a 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.

  As described above, 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 detection data corrected corresponding to the detection data is unrealistic and extreme May result in a random distribution. However, the physical quantity data correction apparatus 100 according to the present embodiment selects a correction parameter corresponding to the degree of similarity between the corrected detection data distribution and the spherical distribution from the realistic correction parameters calculated in advance. The correction parameter can be selected to continue the operation.

  As described above, the physical quantity data correction apparatus 100 according to the present embodiment generates corrected detection data based on the acquired detection data and the acquired correction parameter, and performs appropriate correction from the generated detection data after correction. It has been described that detection data corrected by parameters is selected. Instead, the physical quantity data correction device 100 generates detection data based on partial correction parameters among a plurality of acquired correction parameters, and selects detection data corrected with appropriate correction parameters. Also good.

  For example, the generation unit 130 generates a corrected detection data distribution for at least some of the plurality of correction parameters. The data selection unit 140 selects or generates a correction parameter from at least a part of the plurality of correction parameters based on the distribution of the corrected detection data generated for at least a part of the plurality of correction parameters. The unit determines whether to generate a distribution of corrected detection data for other correction parameters.

  For example, the data selection unit 140 may select another of the corrected detection data when the similarity between the distribution of one detection data and the distribution of the spheres is within a predetermined similarity range. The generation of detection data after correction by the correction parameter is stopped, and the one detection data is output as corrected detection data to be output. Thereby, the data selection unit 140 can reduce the possibility of calculating corrected detection data corresponding to all correction parameters, and can shorten the execution time until the detection data is output.

  Further, the generation unit 130 may arrange a plurality of correction parameters in a predetermined order, sequentially generate corrected detection data in an order corresponding to the arrangement, and sequentially supply the detection data to the data selection unit 140. It's okay. The data selection unit 140 sequentially determines the similarity between the supplied corrected detection data distribution and the distribution of the sphere, and when the similarity is within a predetermined similarity range, the similarity This determination may be stopped.

  Furthermore, the generation unit 130 may arrange the plurality of correction parameters in an order corresponding to the degree of correction, such as the magnitude of change in the distribution shape before and after correction. For example, the generation unit 130 arranges the plurality of correction parameters in an order in which the difference between the distribution before correction and the distribution after correction is greatly different. That is, the generation unit 130 corrects the distribution of the elliptical shape before correction to an elliptical shape with almost no change (for example, the change in the ratio of the short axis to the long axis is smaller), and arranges the correction parameter at the top of the array. The correction parameter that increases the change in the elliptical shape by correction (for example, increases the change in the ratio between the short axis and the long axis) is arranged at the end of the array.

  Instead, the generation unit 130 may arrange the correction parameters according to the degree of changing the ratio of the short axis to the long axis. For example, the generation unit 130 arranges a correction parameter that corrects the short axis the longest (shortest long axis) at the head, and arranges a correction parameter that corrects the short axis the shortest (longest longest) at the tail. Let In this case, the generation unit 130 may arrange correction parameters for correcting the uncorrected distribution into a corrected distribution shape with almost no change at substantially the center of the array.

  Then, the generation unit 130 sequentially generates corrected detection data in the order corresponding to the arrangement (that is, in order from the head or tail). Thereby, the data selection part 140 can receive the detection data after correction | amendment in order of the predetermined correction degree. That is, since the data selection unit 140 sequentially receives the detection data after correction so as to converge to an appropriate correction parameter, the selection of the correction parameter may be stopped when the similarity determination result can be determined to be maximum.

  The physical quantity data correction apparatus 100 may sequentially generate corrected detection data in an order based on an algorithm or the like after arranging such correction parameters in a predetermined order. For example, the generation unit 130 generates a corrected detection data distribution corresponding to one correction parameter among the plurality of correction parameters. Then, the data selection unit 140 determines the similarity between the corrected detection data distribution and the sphere distribution, and selects the corrected detection data to be output or continues the determination according to the determination result. Decide what to do.

  For example, the data selection unit 140 compares a predetermined threshold value with the similarity, and selects whether or not the corrected detection data to be output is the corrected detection data distribution. Instead, the data selection unit 140 stores the sequentially determined similarities, continues the determination so that the next determined similarity is further increased, and the next similarity determination result decreases. The corrected detection data distribution after correction may be output as corrected detection data to be output. In this case, the data selection unit 140 designates a guideline for searching for a correction parameter to be used for the next detection data in the data selection unit 140 according to the determination result of the current similarity.

  For example, in the distribution of detected data after correction, when the minor axis is longer than the major axis, the data selection unit 140 provides a guideline for correcting the minor axis to be shorter (longer axis is longer). 140. Instead, the data selection unit 140 determines a correction parameter to be searched next by a binary search based on the distribution of detection data after correction, and after correction corresponding to the correction parameter determined by the generation unit 130 The distribution of the detected data may be generated.

  In this case, the generation unit 130 generates a distribution of corrected detection data corresponding to the correction parameter to be used next based on the designation of the data selection unit 140. For example, when the correction unit arranges the correction parameters according to the degree of changing the ratio of the short axis to the long axis, the generation unit 130 generates detection data after the first correction using the correction parameters near the center of the array, From the next time, detection data after the next correction is generated using correction parameters shifted one by one to the head (or tail) side of the array in accordance with the pointer of the data selection unit 140.

  When the data selection unit 140 uses a binary search algorithm, for example, the generation unit 130 may calculate L / L when the number of correction parameters arranged according to the degree of change in the ratio of the short axis to the long axis is L. Detection data after the first correction is generated using the correction parameter arranged second. Then, in accordance with an instruction from the data selection unit 140, the generation unit 130 generates detection data after the next correction using the correction parameters arranged in the L / 4 or 3L / 4th.

  As described above, the physical quantity data correction apparatus 100 sequentially generates the next corrected detection data based on a predetermined algorithm or the like based on one corrected detection data, and is most similar to the sphere distribution. The corrected detection data can be selected and output at high speed. In the physical quantity data correction device 100 described above, it has been described that the generation unit 130 arranges the correction parameters based on the degree of correction. Instead, the correction parameter acquisition unit 120 is arranged in a predetermined order. A plurality of correction parameters may be acquired.

  FIG. 3 shows a modification of the physical quantity data correction apparatus 100 according to this embodiment. In the physical quantity data correction apparatus 100 of the present modification, the same reference numerals are given to substantially the same operations as those of the physical quantity data correction apparatus 100 according to the present embodiment shown in FIG. The physical quantity data correction apparatus 100 according to this modification further includes a parameter selection unit 150.

  The parameter selection unit 150 is connected to each of the detection data acquisition unit 110 and the parameter acquisition unit 120, and selects a correction parameter candidate based on the acquired detection data and correction parameters. The parameter selection unit 150 selects a correction parameter candidate 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 150 is connected to the generation unit 130 and supplies the selected candidate to the generation unit 130.

  Selection of correction parameter candidates by the parameter selection unit 150 will be described later. The parameter selection unit 150 includes a calculation unit 152, a determination unit 154, and a specification unit 156.

The calculation unit 152 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 calculation unit 152 converts a distribution obtained by mapping the detection data value 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 152 obtains 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 3)
x _ideal = Z · x _meas

The determination unit 154 is connected to the parameter acquisition unit 120 and the calculation unit 152, and determines the similarity between the conversion coefficient calculated by the calculation unit 152 and each of the plurality of correction parameters acquired by the parameter acquisition unit 120. For example, the determination unit 154 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 154 may determine the similarity by calculating a norm or the like of the difference between the matrices. The determination unit 154 supplies the similarity determined for each correction parameter to the specifying unit 156.

  The specifying unit 156 is connected to the determination unit 154 and specifies a correction parameter candidate used for correction among a plurality of correction parameters based on the similarity. The specifying unit 156 may use one or a plurality of correction parameters as correction parameter candidates. For example, the specifying unit 156 specifies correction parameter candidates based on a predetermined threshold. The specifying unit 156 supplies the specified correction parameter candidates to the generation unit 130.

  The generation unit 130 of the present modification corrects the detection data acquired by each of the correction parameter candidates, and generates a corrected detection data distribution corresponding to each of the correction parameter candidates. Then, the data selection unit 140 selects a correction parameter to be used for correcting the detection data based on the distribution of the corrected detection data corresponding to each correction parameter candidate. The operation of the modified example of the physical quantity data correction apparatus 100 according to this embodiment will be described with reference to FIG.

  FIG. 4 shows an operation flow of a modification of the physical quantity data correction apparatus 100 according to the present embodiment. In the operation flow of the physical quantity data correction apparatus 100 according to this modification, the description of the operation flow that is substantially the same as the operation flow of the physical quantity data correction apparatus 100 according to the present embodiment shown in FIG.

First, the detection data acquisition unit 110 acquires the detection data x _meas from the magnetic detection unit 10 (S410). 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 150.

Next, the parameter acquisition unit 120 acquires a plurality of correction parameters (S420). 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 150.

Next, the calculation unit 152 calculates the distribution of the detection data x _meas to calculate the conversion coefficient Z according to the distribution of the detection data (S430). For example, the calculation unit 152 calculates an n-dimensional ellipsoid that approximates the distribution of the detection data on 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 the case of this example, the calculation unit 152 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 152 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 152 uses the following expression that is a general expression of an ellipsoid.
(Equation 4)
ax ² + by ² + cz ² + 2dxy + 2eyz + 2fzx + 2gx + 2hy + 2iz + j
= 0

The calculation unit 152 calculates an expression approximated to a three-dimensional ellipsoid based on the distribution of the values of the detection data x _meas . The calculation unit 152 may calculate the coefficient vector using, for example, a least square method. Accordingly, the calculation unit 152 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 152 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, even when the data selection unit 140 of the present embodiment illustrated in FIG. 1 approximates the distribution of the corrected detection data _{xc_k} with an ellipsoid in an n-dimensional space, the same procedure can be performed.

In addition, the calculation unit 152 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 152 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. 5 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. 6 shows an example of detection data after the calculation unit 152 according to the present embodiment filters and thins out the detection data. In this way, the calculation unit 152 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. 7 shows an example when the calculation unit 152 according to the present embodiment applies the distribution of the value of the detection data x _meas to a three-dimensional ellipsoid. In the physical quantity data correction apparatus 100, ideally, detection data distributed in a spherical shape is distorted into an ellipsoidal distribution as shown in FIG. 7 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 152 corrects the calculated offset of the three-dimensional ellipsoid (S440). 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 152 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 5)
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 6)
^T (x _ideal ) · x _ideal = R ²

In Equation 5, D indicates a strain coefficient for distorting a spherical distribution into an elliptical shape by the 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 152 corrects the offset so that the calculated ellipsoidal expression is centered on the origin. That is, the calculation unit 152 subtracts the vector o from the detection data x _meas .

Here, from the equations (5) and (6), when the inverse matrix D ^{−1 of the} matrix D exists, the following equation is obtained.
(Equation 7)
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 152 can calculate the data w with the offset corrected by subtracting the vector o from the detection data x _{meas in} Equation 5.
(Equation 8)
w = x _meas −o = D · x _ideal

  FIG. 8 shows an example when the calculation unit 152 according to the present embodiment corrects the offset of the three-dimensional ellipsoid. Note that the calculation unit 152 does not have to perform offset correction when the calculated offset of the ellipsoidal expression is approximately zero. For example, when the calculation unit 152 is smaller than a predetermined offset value, the calculation unit 152 omits offset correction on the assumption that there is no influence of the hard magnetic material.

Next, the calculation unit 152 performs coordinate conversion by rotating the three-dimensional ellipsoid (S450). From equation (8), 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 obtained, the calculation unit 152 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 calculation unit 152 performs coordinate conversion by multiplying the corrected data w by the matrix Q to calculate data v.
(Equation 9)
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 calculation unit 152 calculates such a matrix Q using a known method such as a Householder transformation and a Shift-QR method, for example. FIG. 9 shows an example when the calculation unit 152 according to the present embodiment rotates a three-dimensional ellipsoid and converts it into a standard format.

Next, the calculation unit 152 converts the three-dimensional ellipsoid into a sphere (S460). As an example, the calculation unit 152 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 10)
s = κ− ¹ · Λ ^1/2 · v

Here, the distribution of the vector s in Expression 10 satisfies the following relational expression, and indicates a sphere in the coordinate system of s. The calculating unit 152 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. 10 shows an example when the calculation unit 152 according to the present embodiment converts a three-dimensional ellipsoid into a sphere.
(Equation 11)
^T s · s = (R / κ) ²

Here, since the ellipsoid is rotated using the matrix Q, the calculation unit 152 may restore the rotated angle. That is, the calculation unit 152 converts the detection data into a data vector t expressed by the following equation.
(Equation 12)
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 152 calculates the conversion coefficient Z as follows: To calculate.
(Equation 13)
Z = Q ^-1 · κ ^-1 · Λ ^1/2 · Q

  As described above, the calculation unit 152 of 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 n-dimensional physical quantity detection data, the calculation unit 152 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 154 receives the conversion coefficient Z from the calculation unit 152, 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 (S470). Determination unit 154, 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 154 determines that the correction parameter having the smallest norm among the plurality of correction parameters has the highest similarity.

Alternatively, the determination unit 154, 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 154 determines the similarity of the correction parameter having the smallest sum of squares or absolute values of the elements of the difference as the highest similarity among the plurality of correction parameters.

  Next, the specifying unit 156 specifies correction parameter candidates used for correction based on the similarity (S480). For example, the specifying unit 156 specifies a correction parameter corresponding to a similarity having a value smaller than a predetermined threshold as a candidate for a correction parameter used for correction.

  Next, the generation unit 130 and the data selection unit 140 select and output corrected detection data to be output based on the detection data and correction parameter candidates acquired by the detection data acquisition unit 110 (S490). Selection and output of corrected detection data to be output by the generation unit 130 and the data selection unit 140 are substantially the same as the operations described in steps S230 and S240 in FIG.

  As described above, the parameter selection unit 150 selects a correction parameter candidate that can be selected as a correction parameter from among a plurality of correction parameters. Therefore, the generation unit 130 includes a plurality of corrections acquired by the parameter acquisition unit 120. The data selection unit 140 can select corrected detection data to be output efficiently without generating corrected detection data using all of the parameters.

  Further, the parameter selection unit 150 calculates a 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, a correction parameter similar to the conversion coefficient Select. As described above, the parameter selection unit 150 calculates a conversion coefficient for correcting the detection data based on the acquired detection data. Therefore, when the elliptical distribution based on the detection data can be acquired with high accuracy, the parameter selection unit 150 is abbreviated as a corresponding correction parameter. The same conversion coefficient is calculated. Since the parameter selection unit 150 selects a parameter in comparison with such a conversion coefficient, a correction parameter candidate that can be selected as a correction parameter among a plurality of correction parameters can be accurately selected.

  Further, since the parameter selection unit 150 selects correction parameter candidates based on the acquired detection data, the number of correction parameters can be reduced without adding hardware such as other sensors. That is, the physical quantity data correction apparatus 100 can select correction data at high speed without increasing the circuit scale of the entire sensor.

  Further, as described in the physical quantity data correction apparatus 100 shown in FIG. 1, the physical quantity data correction apparatus 100 uses a plurality of mounting forms of the magnetic detection unit 10 and magnetic detection units that are assumed in advance using Equation 13 and the like. Corresponding to a plurality of environmental forms, a plurality of correction parameters are acquired in advance based on accurate detection results. 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.

  The physical quantity data correction apparatus 100 according to the present modification 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 154 determines the similarity between the conversion coefficient calculated by the calculation unit 152 and each of the plurality of determination parameters. Here, the calculation unit 152 calculates a coefficient corresponding to the determination parameter as a conversion coefficient. For example, when the parameter obtaining unit 120 obtains the data vector t of Formula 12, the data vector s of Formula 10, the data vector v of Formula 9, or the data vector w of Formula 8 as a determination parameter, the calculation unit 152 calculates a corresponding data vector as a conversion coefficient instead of the conversion coefficient Z.

Further, the parameter acquisition unit 120 acquires a vector, a matrix, and the like calculated corresponding to the detection data, such as a matrix A of Formula 7 or a matrix Q of Formula 9 or a matrix κ of Formula 10 as a determination parameter. In this case, the calculation unit 152 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 generation unit 130 generates a distribution of detection data using a correction parameter candidate corresponding to a determination parameter determined to have high similarity among a plurality of determination parameters. As a result, the parameter selection unit 150 can determine the degree of similarity using the data vector and matrix in the process of calculating the conversion coefficient Z, so that the calculation unit 152 does not calculate up to the conversion coefficient Z, and the correction parameter Candidates can be selected, and the burden of calculation operations can be reduced.

  Instead of this, the physical quantity data correction apparatus 100 may select correction parameter candidates in accordance with the distribution of the detected 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 152 calculates an expression when approximated to an n-dimensional ellipsoid based on the detection data. Then, the determination unit 154 determines the similarity between the n-dimensional ellipsoid calculated by the calculation unit 152 and each of the plurality of n-dimensional ellipsoids acquired by the parameter acquisition unit 120. As described above, the parameter selection unit 150 selects, as a correction parameter candidate, 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 152 can be further reduced.

  FIG. 11 shows a configuration example of the azimuth angle detection apparatus 200 according to this embodiment. The azimuth angle detection apparatus 200 includes the physical quantity data correction apparatus 100 described in this embodiment and a magnetic offset vector estimation unit 210.

The azimuth angle 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 8. That is, the correction parameter acquired by the parameter acquisition unit 120 is a correction parameter that reduces the influence of the soft magnetic material. For example, the data vector t of Formula 12 is calculated in advance as follows.
(Equation 14)
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

  In addition, when the modification of the physical quantity data correction apparatus 100 illustrated in FIG. 3 calculates the conversion coefficient Z, the same coefficient as the equation 13 is calculated. That is, in the physical quantity data correction apparatus 100 shown in FIG. 11, 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 12 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 azimuth angle detection device 200 can correct and reduce the influence of the interference components of the soft magnetic material and the hard magnetic material on the geomagnetism measurement based on the output of the magnetic detection unit 10. As a result, the azimuth angle 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 azimuth angle detection device 200 outputs the magnetic detection result in which the interference component is reduced, the magnitude and direction of geomagnetism with respect to the azimuth angle detection device 200 can be more accurately output. That is, the azimuth angle detection apparatus 200 can detect the azimuth angle of the azimuth angle detection apparatus 200 according to the magnetic detection result.

  The azimuth angle detection device 200 may output an azimuth angle according to a difference between a predetermined direction and a detected direction of geomagnetism. For example, such an azimuth angle detection device 200 is mounted with a mobile device or the like, thereby reducing the installation area and capacity, and outputs the azimuth angle of the mobile device based on the output of the magnetic detection unit 10. be able to.

  Note that the azimuth angle detection apparatus 200 of the present embodiment has been described that the physical quantity data correction apparatus 100 corrects the offset after converting the distribution of data values into a spherical shape. Instead, when the physical quantity data correction apparatus 100 executes offset correction and data value distribution conversion, the offset correction need not be executed.

  FIG. 12 shows an example of a 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 generation unit 130, the data selection unit 140, and the like.

  The information processing described in the program is read by the computer 1900, whereby the detection data acquisition unit 110, the parameter acquisition unit 120, and the generation unit, which are specific means in which the software and the various hardware resources described above cooperate. 130 and the data selection unit 140 and the like. The specific physical quantity data correction device 100 and the azimuth angle detection device 200 according to the purpose of use are realized by calculating or processing information according to the purpose of use of the computer 1900 in this embodiment by this specific means. Built.

  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 Generation part, 140 Data selection part, 150 Parameter selection part, 152 Calculation part, 154 Determination part, 156 Identification part, 200 Direction Angle detection device, 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 (18)

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;
Using each of the plurality of correction parameters acquired by the parameter acquisition unit, the detection data acquired by the detection data acquisition unit is corrected, and a distribution of corrected detection data corresponding to each of the plurality of correction parameters is obtained. A generation unit for generating each;
A data selection unit that selects correction parameters used for correction of detection data based on the distribution of detection data after correction corresponding to each of the plurality of correction parameters;
A physical quantity data correction apparatus comprising:   The physical quantity data correction apparatus according to claim 1, wherein the data selection unit selects corrected detection data to be output based on a distribution of the corrected detection data corresponding to each of the plurality of correction parameters.   3. The physical quantity data correction according to claim 1, wherein the data selection unit selects a correction parameter to be used for correcting the detection data in accordance with the similarity between the corrected detection data distribution and a predetermined distribution. apparatus.   The data selection unit is configured to detect detection data according to a degree of similarity between the corrected detection data distribution and an n-dimensional sphere in an n-dimensional coordinate space (n is an integer of 2 or more) expressed by the plurality of axis directions. The physical quantity data correction apparatus according to claim 3, wherein a correction parameter used for correcting the physical quantity is selected.   The parameter acquisition unit acquires a correction parameter for converting an n-dimensional ellipsoid approximating the distribution of the detection data in the n-dimensional coordinate space expressed by the plurality of axis directions into the n-dimensional sphere. The physical quantity data correction device described.   The data selection unit uses, as corrected detection data to be output, corrected detection data whose distribution in the n-dimensional coordinate space has the highest similarity to the n-dimensional sphere among the corrected detection data. The physical quantity data correction device according to claim 4 or 5 to be selected.   The data selection unit corrects the detection data after correction that minimizes the least square error when the distribution in the n-dimensional coordinate space is approximated by the n-dimensional sphere among the detection data after correction. The physical quantity data correction device according to any one of claims 4 to 6, which is selected as subsequent detection data. The generation unit generates a distribution of detection data after correction for at least a part of the plurality of correction parameters,
The data selection unit selects a correction parameter from at least some of the plurality of correction parameters based on a distribution of the corrected detection data generated for at least some of the plurality of correction parameters; The physical quantity data correction apparatus according to claim 1, wherein the generation unit determines whether to generate a distribution of the corrected detection data for other correction parameters. The generation unit generates a distribution of the detection data after correction corresponding to one correction parameter of the plurality of correction parameters,
The data selection unit determines a correction parameter to be searched next by a binary search based on the distribution of the detection data, and calculates the corrected detection data distribution corresponding to the correction parameter determined by the generation unit. The physical quantity data correction device according to claim 1, wherein the physical quantity data correction device is generated. A parameter selection unit that selects a correction parameter candidate to be used for correction from among the plurality of correction parameters based on the distribution of detection data in the plurality of axis directions and supplies the correction parameter candidate to the generation unit;
The generation unit corrects the detection data acquired by each of the correction parameter candidates, and generates a corrected detection data distribution corresponding to each of the correction parameter candidates,
The said data selection part selects the correction parameter used for correction | amendment of detection data based on distribution of the detection data after the correction | amendment corresponding to each of the said correction parameter candidate. The physical quantity data correction device described. The parameter selection unit
A calculation unit that calculates a conversion coefficient according to the detection data based on 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 a candidate for 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 10, comprising:   The physical quantity data correction device according to any one of claims 1 to 11, 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 apparatus according to claim 12, 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 13, 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, respectively. 14. The physical quantity data correction device according to 14. The physical quantity data correction device according to any one of claims 12 to 15,
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;
An azimuth angle detection device comprising:   A program that causes a computer to function as the physical quantity data correction device according to any one of claims 1 to 15.   A program that causes a computer to function as the azimuth angle detection device according to claim 16.

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