PATENT DOCUMENT

Publication Number: US-8677640-B2
Application Number: US-201213669403-A
Country: US
Kind Code: B2

Title: Magnetometer accuracy and use

Abstract:
A parameter related to the Earth&#39;s magnetic field can be used to determine accuracy of a magnetometer of a mobile device. In one aspect, a first instance of a parameter related to Earth&#39;s magnetic field is determined using data generated by the magnetometer. The magnetometer data can be based in part on a position of the mobile device with respect to the Earth. A second instance of the parameter can be determined using data generated by a model of Earth&#39;s magnetic field. The model data can also be based in part on the position of the mobile device with respect to the Earth. The first instance of the parameter can be compared with the second instance of the parameter. An accuracy metric for the magnetometer can be determined based on a result of the comparison. An indication of the accuracy metric can be presented by the mobile device.

Claims:
What is claimed is: 
     
       1. A method performed by a processor of a mobile device having a magnetometer, the method comprising:
 determining an accuracy metric based on magnetometer measurements output by the magnetometer during a calibration or recalibration procedure; and 
 presenting an indication of the accuracy metric on the mobile device using tactile feedback. 
 
     
     
       2. The method of  claim 1 , where the calibration or recalibration procedure includes obtaining historical magnetometer data and calibrating or recalibrating the magnetometer using the historical magnetometer data. 
     
     
       3. The method of  claim 2 , where the historical magnetometer data includes an inclination or declination angle of Earth&#39;s magnetic vector. 
     
     
       4. The method of  claim 2 , where the historical magnetometer data includes calibration offsets. 
     
     
       5. The method of  claim 2 , where the historical magnetometer data includes the magnitude of Earth&#39;s magnetic vector. 
     
     
       6. The method of  claim 2 , where determining an accuracy metric based on magnetometer measurements output by the magnetometer during a calibration or recalibration procedure further comprises:
 determining magnetometer data from magnetometer readings; 
 comparing the determined magnetometer data with the historical magnetometer data; and 
 determining the accuracy metric based on results of the comparing. 
 
     
     
       7. The method of  claim 6 , where the historical magnetometer data is obtained using a current position of the mobile device. 
     
     
       8. The method of  claim 7 , where the calibration or recalibration trigger event is docking of the mobile device in a car. 
     
     
       9. The method of  claim 7 , where the calibration or recalibration trigger event is invalid calibration offsets. 
     
     
       10. The method of  claim 1 , further comprising:
 detecting a calibration or recalibration trigger event; and 
 initiating the calibration or recalibration procedure. 
 
     
     
       11. A mobile device comprising:
 a magnetometer; 
 one or more processors configured to perform operations including:
 determining an accuracy metric based on magnetometer measurements output by the magnetometer during a calibration or recalibration procedure; and 
 presenting an indication of the accuracy metric on the mobile device using tactile feedback. 
 
 
     
     
       12. The mobile device of  claim 11 , where the calibration or recalibration procedure includes obtaining historical magnetometer data and calibrating or recalibrating the magnetometer using the historical magnetometer data. 
     
     
       13. The mobile device of  claim 12 , where the historical magnetometer data includes an inclination or declination angle of Earth&#39;s magnetic vector. 
     
     
       14. The mobile device of  claim 12 , where the historical magnetometer data includes calibration offsets. 
     
     
       15. The mobile device of  claim 12 , where the historical magnetometer data includes the magnitude of Earth&#39;s magnetic vector. 
     
     
       16. The mobile device of  claim 12 , where determining an accuracy metric based on magnetometer measurements output by the magnetometer during a calibration or recalibration procedure further comprises:
 determining magnetometer data from magnetometer readings; 
 comparing the determined magnetometer data with the historical magnetometer data; and 
 determining the accuracy metric based on results of the comparing. 
 
     
     
       17. The mobile device of  claim 16 , where the historical magnetometer data is obtained using a current position of the mobile device. 
     
     
       18. The mobile device of  claim 11 , where the operations further comprise:
 detecting a calibration or recalibration trigger event; and 
 initiating the calibration or recalibration procedure. 
 
     
     
       19. The mobile device of  claim 18 , where the calibration or recalibration trigger event is docking of the mobile device in a car. 
     
     
       20. The mobile device of  claim 18 , where the calibration or recalibration trigger event is invalid calibration offsets. 
     
     
       21. A method performed by a processor of a mobile telephone having a magnetometer, the method comprising:
 determining an accuracy metric based on magnetometer measurements output by the magnetometer during a calibration or recalibration procedure, where the calibration or recalibration procedure includes obtaining historical magnetometer data and calibrating or recalibrating the magnetometer using the historical magnetometer data; and 
 presenting an indication of the accuracy metric on a touch sensitive display of the mobile device using a graphical indicator. 
 
     
     
       22. The method of  claim 21 , where the historical magnetometer data includes an inclination or declination angle of Earth&#39;s magnetic vector. 
     
     
       23. The method of  claim 21 , where the historical magnetometer data includes calibration offsets. 
     
     
       24. The method of  claim 21 , where the historical magnetometer data includes the magnitude of Earth&#39;s magnetic vector. 
     
     
       25. The method of  claim 21 , where determining an accuracy metric based on magnetometer measurements output by the magnetometer during a calibration or recalibration procedure further comprises:
 determining magnetometer data from magnetometer readings; 
 comparing the determined magnetometer data with the historical magnetometer data; and 
 determining the accuracy metric based on results of the comparing. 
 
     
     
       26. The method of  claim 25 , where the historical magnetometer data is obtained using a current position of the mobile device. 
     
     
       27. The method of  claim 21 , further comprising:
 detecting a calibration or recalibration trigger event; and 
 initiating the calibration or recalibration procedure. 
 
     
     
       28. The method of  claim 27 , where the calibration or recalibration trigger event is docking of the mobile device in a car. 
     
     
       29. The method of  claim 27 , where the calibration or recalibration trigger event is invalid calibration offsets. 
     
     
       30. A mobile device comprising:
 a motion sensor; 
 a camera; 
 a magnetometer; 
 one or more processors configured to perform operations including:
 determining an accuracy metric based on magnetometer measurements output by the magnetometer during a calibration or recalibration procedure; and 
 presenting an indication of the accuracy metric on the mobile device using a graphical indicator. 
 
 
     
     
       31. The mobile device of  claim 30 , where the calibration or recalibration procedure includes obtaining historical magnetometer data and calibrating or recalibrating the magnetometer using the historical magnetometer data. 
     
     
       32. The mobile device of  claim 31 , where the historical magnetometer data includes an inclination or declination angle of Earth&#39;s magnetic vector. 
     
     
       33. The mobile device of  claim 31 , where the historical magnetometer data includes calibration offsets. 
     
     
       34. The mobile device of  claim 31 , where the historical magnetometer data includes the magnitude of Earth&#39;s magnetic vector. 
     
     
       35. The mobile device of  claim 31 , where determining an accuracy metric based on magnetometer measurements output by the magnetometer during a calibration or recalibration procedure further comprises:
 determining magnetometer data from magnetometer readings; 
 comparing the determined magnetometer data with the historical magnetometer data; and 
 determining the accuracy metric based on results of the comparing. 
 
     
     
       36. The mobile device of  claim 35 , where the historical magnetometer data is obtained using a current position of the mobile device. 
     
     
       37. The mobile device of  claim 31 , where the operations further comprise:
 detecting a calibration or recalibration trigger event; and 
 initiating the calibration or recalibration procedure. 
 
     
     
       38. The mobile device of  claim 37 , where the calibration or recalibration trigger event is docking of the mobile device in a car. 
     
     
       39. The mobile device of  claim 37 , where the calibration or recalibration trigger event is invalid calibration offsets. 
     
     
       40. The mobile device of  claim 31 , where the accuracy metric is presented on the mobile device using tactile feedback. 
     
     
       41. A method performed by a processor of a mobile device having a magnetometer, the method comprising:
 determining that the mobile device is docked in a car; 
 determining an accuracy metric based on magnetometer measurements output by the magnetometer during a calibration or recalibration procedure; and 
 presenting an indication of the accuracy metric. 
 
     
     
       42. The mobile device of  claim 41 , where the indication of the accuracy metric is presented on the mobile device using tactile feedback.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of and claims priority to U.S. application Ser. No. 13/301,650, entitled “Magnetometer Accuracy and Use,” filed Nov. 21, 2011, now abandoned, which is a continuation of U.S. application Ser. No. 13/030,067, entitled “Magnetometer Accuracy and Use,” filed Feb. 17, 2011, now U.S. Pat. No. 8,061,049, which is a continuation of U.S. application Ser. No. 12/479,717, entitled “Magnetometer Accuracy and Use,” filed Jun. 5, 2009, now U.S. Pat. No. 7,891,103, the entire contents of which are hereby incorporated by reference. 
    
    
     TECHNICAL FIELD 
     This subject matter is related generally to magnetometers. 
     BACKGROUND 
     A mobile device such as a cellular phone or a smart phone, PDA, handheld computer, navigational device, gaming device, netbook, among others can be equipped with a magnetometer. Magnetometer readings can be used to provide its user with a direction, which may be a “heading” (typically given relative to the Earth&#39;s true North), and/or an arrow pointing to true North. The direction information may be provided for the user&#39;s own navigation knowledge, for example, to tell the user which way is north while the user is walking or driving in unfamiliar surroundings. The direction information can also be used by a navigation or map application that may be running on the mobile device. 
     The magnetometer obtains a measure of the magnetic field that is present in the immediate surroundings of the mobile device as a two or three-component vector in a Cartesian coordinate system using 2-axis or 3-axis magnetic sensors. The sensed magnetic field can contain a contribution of the Earth&#39;s magnetic field and a contribution by a local interference field (interference field co-located with the mobile device). The latter is a magnetic field that is created by field sources in the local environment of the mobile device. This may include contributions made by one or more magnetic components that are near the magnetic sensors, such as the magnet of a loudspeaker that is built into the mobile device. The interference field may also have a contribution due to one or more magnetic objects found in the external environment close to the device, such as when the user is driving an automobile, riding in a train or bus, or riding on a bicycle or motorcycle. In most cases, the interference field is not negligible relative to the Earth&#39;s magnetic field. Therefore, a calibration procedure is needed to reduce the adverse impact of the interference field contribution from the sensors&#39; measurements to allow the magnetometer to calculate a more accurate direction. 
     There are several types of 3-axis calibration procedures. In one such technique, the user is instructed to rotate the mobile device (containing the magnetometer) according to a set of geometrically different orientations and azimuth angles, while measurements by the magnetometer and by an orientation sensor are collected and analyzed to isolate or quantify the interference field. The quantified interference field can then be subtracted from the measurement taken by the magnetic sensor to yield the Earth&#39;s geomagnetic field. The Earth&#39;s geomagnetic field can be further corrected to get the true north direction, such as correcting for magnetic variation (declination) due to the variation of the Earth&#39;s magnetic field based on geographic location. 
     In another 3-axis calibration technique, rather than instruct the user to deliberately rotate the mobile device in a predetermined manner, measurements are collected from the magnetometer, continuously over a period of time, while the mobile device is being used or carried by the user. This can lead to random (albeit sufficient) rotations of the mobile device, such that the magnetometer measurements define a desired, generally spherical measurement space. The sphere is offset from the origin of a coordinate system for the Earth&#39;s geomagnetic field vector by an unknown offset vector, which can represent a substantial part (if not all) of the interference field. Mathematical processing of the measurements can be performed to “re-center” the sphere by determining the offset vector. This technique is transparent to the user because the user is not required to go through a calibration procedure where the user deliberately rotates the device through a specified set of orientations. 
     SUMMARY 
     A parameter related to the Earth&#39;s magnetic field can be used to determine accuracy of a magnetometer of a mobile device. In one aspect, a first instance of a parameter related to Earth&#39;s magnetic field is determined using data generated by the magnetometer. The magnetometer data can be based in part on a position of the mobile device with respect to the Earth. A second instance of the parameter can be determined using data generated by a model of Earth&#39;s magnetic field. The model data can also be based in part on the position of the mobile device with respect to the Earth. The first instance of the parameter can be compared with the second instance of the parameter. An accuracy metric for the magnetometer can be determined based on a result of the comparison. An indication of the accuracy metric can be presented by the mobile device. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1A  illustrates an exemplary Cartesian coordinate system describing the Earth&#39;s geomagnetic field in accordance with some implementations. 
         FIG. 1B  illustrates an exemplary 2-axis magnetometer in accordance with some implementations. 
         FIG. 2  is a block diagram of exemplary calibration system in accordance with some implementations. 
         FIG. 3  is a flow diagram of an exemplary process for determining magnetometer accuracy in accordance with some implementations. 
         FIG. 4  is a block diagram of exemplary architecture of a mobile device employing the process of  FIG. 3  in accordance with some implementations. 
         FIGS. 5A-5B  are screenshots of a map user interface of a mobile device having a magnetometer, including a heading error indicator in accordance with some implementations. 
         FIG. 5C  is a screen shot of a map user interface of a mobile device having a magnetometer, and illustrating the presenting of an indication of the accuracy metric on the mobile device telephone using tactile feedback. 
     
    
    
     DETAILED DESCRIPTION 
     The Earth&#39;s Magnetic Field—Overview 
       FIG. 1  illustrates an exemplary Cartesian coordinate system for describing the Earth&#39;s geomagnetic field in accordance with some implementations. The Earth&#39;s geomagnetic field vector, {right arrow over (F)}, can be described by the orthogonal components X (northerly intensity), Y (easterly intensity) and Z (vertical intensity, positive downwards); total intensity F; horizontal intensity H; inclination (or dip) I, and declination (or magnetic variation) D. Declination, inclination and total intensity can be computed from the orthogonal components using the equations 
                     D   =     arctan   ⁡     (     Y   X     )         ,           (   1   )                 I   =     arctan   ⁡     (     Z   H     )         ,           (   2   )                 F =√{square root over ( H   2   +Z   2 )}, and  (3)
 
     where H is given by
 
 H =√{square root over ( X   2   +Y   2 )}.  (4)
 
     An angle Φ can be defined as the angle between the geomagnetic field vector, {right arrow over (F)}, and the Earth&#39;s gravitational acceleration vector ĝ (which is aligned with the Z component of the Earth&#39;s geomagnetic field vector). The angle Φ can be determined from the inclination angle I, or Φ=90°−I. At any given position on Earth, the total intensity F is constant, regardless of magnetometer orientation. Also, at any given position on Earth, the angle Φ is constant, regardless of magnetometer orientation. The International System of Units (SI) unit of magnetic field intensity most commonly used is the Tesla. 
       FIG. 1B  illustrates an exemplary 2-axis magnetometer in accordance with some implementations. Magnetometers can be 2-axis or 3-axis and the processes described here apply to both types of sensors. In the interest of brevity, only a 2-axis magnetometer is described. 
     In some implementations, 2-axis magnetometer sensor configuration  100  can be used to calculate a heading for a variety of applications, including applications running on a mobile device. Sensor configuration  100  can include two magnetic field sensors  102 ,  104  mounted orthogonally on a board, substrate or other mounting surface. Magnetic sensors  120 ,  104  can be included in an integrated circuit (IC) package with or without other sensors, such as accelerometers and gyros. 
     Sensor configuration  100  can be deployed in a host system environment that contains interfering magnetic fields. Since the Earth&#39;s magnetic field is a weak field (−0.5 Gauss), nearby magnetic objects can interfere with the accurate measurements of sensors  102 ,  104 . A calibration procedure can be deployed to isolate and remove the local magnetic interference. One technique is to determine offsets or offset vector which can be subtracted from sensor measurements to get accurate measurements of the Earth&#39;s magnetic field. For 3-axis sensors, a third component, Z, can be adjusted with an offset as well. 
     In one exemplary calibration procedure for a 2-axis magnetometer, each heading computation can be assumed to be made with a number of valid X and Y sensor readings which can be taken with a minimal delay between each reading. For this exemplary sensor configuration, sensors  102 ,  104  are at right angles with respect to each other and lie level with respect to the Earth&#39;s surface. By convention, the positive end of the X-axis points to the North and the positive end of the Y-axis points to the East. For this example, two consecutive sensor readings are made 180 degrees apart during calibration. These measurement pairs can be represented by (X1, Y1) and (X2, Y2). The Earth&#39;s magnetic field in any given direction, as measured with no interfering field can be represented by offset pair (X E , Y E ). Magnetic interference can be represented by (X offset , Y offset ). Using these mathematical conventions, the two sensor readings can be represented by
 
 X 1 =X   E   +X   offset ;
 
 Y 1 =Y   E   +Y   offset ;
 
 X 2 =−X   E   +X   offset ; and
 
 Y 2 =−Y   E   +Y   offset .  (5)
 
     Assuming the magnetometer is fixed with respect to the host system (e.g., a magnetometer installed in a mobile phone), the readings (X1, Y1) and (X2, Y2) taken during calibration will both contain the same interference values (X offset , Y offset ). Since the magnetometer readings taken during calibration are 180 degrees apart the readings are equal but opposite in sign. Solving the equations above for X offset  and Y offset  yields
 
 X   offset =( X 1 +X 2)/2, and
 
 Y   offset =( Y 1 +Y 2)/2.  (6)
 
     A measurement of the sensor readings can be represented by (X E , Y E ). In some implementations, a basic calculation of the heading can be performed using X E  and Y E  and the equation:
 
 A   heading =arctan( Y   E   ,X   E ),  (7)
 
where the resulting heading A heading  can be mapped into the correct quadrant based on the signs of X E  and Y E . The heading A heading , calculated from measurements provided by the magnetometer, is a magnetic heading that can be corrected by combining the declination with the heading A heading  to identify a heading relative to true north.
 
     Other implementations are possible. For example, the heading can also be calibrated based on the orientation of the device obtained from an accelerometer, inclination, and other types of corrections or calibrations. 
     Once the offsets are determined, the offsets can be subtracted from a subsequent sensor reading (X3, Y3).
 
 X   E   =X   3   −X   offset ,
 
 Y   E   =Y 3 −Y   offset .  (8)
 
     Some additional techniques for performing 2-dimensional and 3-dimensional electronic magnetometer calibration are described in co-pending patent application Ser. No. 12/479,182, filed Jun. 5, 2009, for “Calibration Techniques For An Electronic Compass In A Portable Device,” which is incorporated by reference herein in its entirety. 
     If a magnetometer is included in a mobile device, such as a mobile phone, the local magnetic interference can change. For example, if the user docks his mobile device (containing the magnetometer) in his car, magnetic objects in the car could change the local interference. This could result in the calibration offsets becoming invalid. If the offsets are invalid, then the magnetometer can perform a recalibration procedure to generate new offsets. This recalibration procedure can be a tedious process for the user if performed often, and may require the user to manipulate the mobile device through a number of angles. 
     Example Calibration System 
       FIG. 2  is a block diagram of an exemplary calibration system  200  in accordance with some implementations. Calibration system  200  can include location processor  202 , magnetometer  204 , magnetometer calibration module  206  and historical magnetometer data  208 . Calibration system  200  can be implemented in software, firmware, hardware or a combination thereof. Location processor  202  can be a GPS receiver or some other processor or receiver for implementing cell tower positioning technology or a Wi-Fi positioning technology (e.g., Skyhook™). Magnetometer  204  can be a 2-axis or 3-axis magnetometer sensor. Magnetometer calibration module  206  can be software that receives position data and magnetometer data from location processor  202  and magnetometer  204 , respectively. 
     In some implementations, calibration system  200  can respond to a recalibration trigger event. A recalibration trigger event can be any event that triggers a recalibration procedure on the mobile device. The trigger event can be based on time, location, mobile device activity, an application request, magnetometer data, etc. Responsive to the recalibration trigger event, location processor  202  can determine a current position of the mobile device. The position information can provide various parameters related to the Earth&#39;s magnetic field, which can be used with an Earth geomagnetic field model to recalibrate the magnetometer. For example, declination D, inclination I, and total intensity, F, can be determined from the position information. The angle Φ can be determined from the inclination, I, or the dot product of {right arrow over (F)} and the gravitational vector, ĝ, which can be received from location processor  202  and/or taken from an accelerometer reading. Once these parameters are determined, one or more of the parameters (collectively referred to as “historical magnetometer data”) can be stored in a look up table or other repository for subsequent search and retrieval. 
     Example Process For Determining Magnetometer Accuracy 
       FIG. 3  is a flow diagram of an exemplary process  300  for determining magnetometer accuracy in accordance with some implementations. In some implementations, process  300  begins by determining a first instance of a parameter related to Earth&#39;s magnetic field using first data generated by a magnetometer of the mobile device. The first data can be based at least in part on a position of the mobile device with respect to the Earth ( 302 ). For example, a number of samples of the angle Φ can be calculated using magnetometer data and the Earth&#39;s magnetic vector, {right arrow over (F)}, can be determined from X, Y, Z sensor readings, as described in reference to  FIG. 2 . The dot product of the Earth&#39;s magnetic vector, {right arrow over (F)}, and the gravitational vector, ĝ, yields the angle Φ. A second instance of the parameter can be determined using second data generated by a model of the Earth&#39;s geomagnetic field. The second data can be based at least in part on a position of the mobile device with respect to the Earth ( 304 ). For example, based on the position of the magnetometer with respect to the Earth, the geomagnetic field model can be used to generate inclination angle, I′. Then Φ=90°−I′. 
     The first instance and the second instance can be compared ( 306 ). For example, a variation can be computed between sample angles Φ and model angles Φ′ computed from a model of the Earth&#39;s geomagnetic field (e.g., 10 th  Generation IGRF model). A running average of the variation can be determined from a set of N samples (e.g., N=10 samples), where N is a positive integer, as follows: 
     
       
         
           
             
               
                 
                   
                     var 
                     ave 
                   
                   = 
                   
                     
                       1 
                       N 
                     
                     ⁢ 
                     
                       
                         ∑ 
                         
                           n 
                           = 
                           0 
                         
                         N 
                       
                       ⁢ 
                       
                         
                           
                             ( 
                             
                               Φ 
                               - 
                               
                                 Φ 
                                 ′ 
                               
                             
                             ) 
                           
                           2 
                         
                         . 
                       
                     
                   
                 
               
               
                 
                   ( 
                   9 
                   ) 
                 
               
             
           
         
       
     
     If a 2-axis magnetometer is used, then Φ can be a fixed horizontal projection to the 2-axis plane given by H fixed =F cos(I). 
     An accuracy metric can be determined for the magnetometer based on results of the comparison ( 308 ). For example, a queue or other data structure can be used to store the maximum variation, var max  over a given window of time. In this example, var max  is the maximum value of var ave  observed over M samples (e.g., M=30 samples). An approximate standard deviation value can be determined using the formula 
                     val   =         var   max             var   ave       *     f   scale           ,           (   10   )               
where f scale  is a scaling factor for moving the approximate standard deviation value calculated in equation (10) into one of a number of accuracy level “buckets” based on Φ. In equation (10), the maximum average variance, var max , is divided by the average variance to approximate a standard deviation value. In equation (10), f scale =2.0/cos(Φ′).
 
     In some implementations, the approximate standard deviation value can be placed in the following accuracy level “buckets”:
 
If val&lt;Best, then
 
accuracy=10°;
 
If val&lt;Level5, then
 
accuracy=15°;
 
If val&lt;Level4, then
 
accuracy=20′;
 
If val&lt;Level3, then
 
accuracy=25′;
 
If val&lt;Level2, then
 
accuracy=30°;
 
If val&lt;Level1, then
 
accuracy=35°; and
 
If val&lt;Worst, then
 
accuracy=40°.  (11)
 
     Some exemplary accuracy levels for delineating the “buckets” can be: Best=15, Level1=90, Level2=75, Level3=60, Level4=45. Level5=30 and Worst=100. 
     The “accuracy” metric resulting from equations (11) can be used to generate an accuracy indicator for presentation on the mobile device ( 310 ). For example, a user interface displayed on the mobile device can present a graphical indicator that describes the accuracy of the magnetometer. An exemplary accuracy indicator is the heading error indicator described in reference to  FIGS. 5A and 5B . 
     The accuracy calculation described above can be represented with the following pseudocode. 
     
       
         
           
               
             
               
                   
               
             
            
               
                 // the compass accuracy class is instantiated with the following geomagnetic information and parameters 
               
               
                 // 10 and 30 are buffer sizes selected for this example 
               
               
                 // geomagneticModel, is an instance of the model that calculates all the static truth geomagnetic information for 
               
               
                 the location of the device 
               
               
                 init(geomagneticModel.inclination,(2.0f/cos(CLCommonDegreesToRadians(geomagneticModel.inclination))),10,30) 
               
               
                 // within the accuracy component there is a function to handle the addition of calculated inclination values from 
               
               
                 the chip 
               
               
                 // raw magnetic data is read and the inclination is then calculated... then passed here 
               
               
                 void accuracy::addSample(float sample){ 
               
               
                 // calculate the variance of the sample from the model 
               
               
                 float varSam = sample − geomagneticModel.inclination; 
               
               
                 varSam*=varSam; 
               
               
                 // add the samples to two running instances 
               
               
                 fVariance.addSample(varSam); // this keeps a running average of 10 samples 
               
               
                 fMaxQueue.addSample(fVariance.getValue( )); // this keeps the running maximum value of 30 samples 
               
               
                 } 
               
               
                 // when the heading is ready to be reported outside of this class, the accuracy value is collected from here 
               
               
                 float accuracy::getAccuracy( ) { 
               
               
                 float accuracy = 40.0f; // default to the worst accuracy value 
               
               
                 // compute the relative accuracy and scale appropriately 
               
               
                 // value = ( max{circumflex over ( )}2 / average{circumflex over ( )}2 ) * scale 
               
               
                 float val = (sqrt(fMaxQueue.getValue( ))/sqrt(fVariance.getSize( ))*fScale); 
               
               
                 // bucket the value by our accuracy settings 
               
               
                 if (val &lt; kCompassAccuracyBest) { 
               
               
                 accuracy = 10.0f; 
               
               
                 } else if (val &lt; kCompassAccuracyLevel5) { 
               
               
                 accuracy = 15.0f; 
               
               
                 } else if (val &lt; kCompassAccuracyLevel4) { 
               
               
                 accuracy = 20.0f; 
               
               
                 } else if (val &lt; kCompassAccuracyLevel3) { 
               
               
                 accuracy = 25.0f; 
               
               
                 } else if (val &lt; kCompassAccuracyLevel2) { 
               
               
                 accuracy = 30.0f; 
               
               
                 } else if (val &lt; kCompassAccuracyLevel1) { 
               
               
                 accuracy = 35.0f; 
               
               
                 } else if (val &lt; kCompassAccuracyWorst) { 
               
               
                 accuracy = 40.0f; 
               
               
                 } 
               
               
                 // return the accuracy value to be reported to the user 
               
               
                 return accuracy; 
               
               
                 } 
               
               
                   
               
            
           
         
       
     
     Example Mobile Device Architecture 
       FIG. 4  is a block diagram of exemplary architecture  400  of a mobile device including a magnetometer. The mobile device  100  can include memory interface  402 , one or more data processors, image processors and/or central processing units  404 , and peripherals interface  406 . Memory interface  402 , one or more processors  404  and/or peripherals interface  406  can be separate components or can be integrated in one or more integrated circuits. Various components in mobile device architecture  400  can be coupled together by one or more communication buses or signal lines. 
     Sensors, devices, and subsystems can be coupled to peripherals interface  406  to facilitate multiple functionalities. For example, motion sensor  410 , light sensor  412 , and proximity sensor  414  can be coupled to peripherals interface  406  to facilitate orientation, lighting, and proximity functions of the mobile device. Location processor  415  (e.g., GPS receiver) can be connected to peripherals interface  406  to provide geopositioning. Magnetometer  416  (e.g., an integrated circuit chip) can also be connected to peripherals interface  406  to provide data that can be used to determine the direction of magnetic North. 
     Camera subsystem  420  and Optical sensor  422 , e.g., a charged coupled device (CCD) or a complementary metal-oxide semiconductor (CMOS) optical sensor, can be utilized to facilitate camera functions, such as recording photographs and video clips. 
     Communication functions can be facilitated through one or more wireless communication subsystems  424 , which can include radio frequency receivers and transmitters and/or optical (e.g., infrared) receivers and transmitters. The specific design and implementation of communication subsystem  424  can depend on the communication network(s) over which the mobile device is intended to operate. For example, the mobile device may include communication subsystems  424  designed to operate over a GSM network, a GPRS network, an EDGE network, a Wi-Fi or WiMax network, and a Bluetooth™ network. In particular, wireless communication subsystems  424  may include hosting protocols such that the mobile device may be configured as a base station for other wireless devices. 
     Audio subsystem  426  can be coupled to speaker  428  and microphone  430  to facilitate voice-enabled functions, such as voice recognition, voice replication, digital recording, and telephony functions. Note that speaker  428  could introduce magnetic interference to the magnetometer, as described in reference to  FIGS. 1-2 . 
     I/O subsystem  440  can include touch screen controller  442  and/or other input controller(s)  444 . Touch-screen controller  442  can be coupled to touch screen  446 . Touch screen  446  and touch screen controller  442  can, for example, detect contact and movement or break thereof using any of a plurality of touch sensitivity technologies, including but not limited to capacitive, resistive, infrared, and surface acoustic wave technologies, as well as other proximity sensor arrays or other elements for determining one or more points of contact with touch screen  446 . 
     Other input controller(s)  444  can be coupled to other input/control devices  448 , such as one or more buttons, rocker switches, thumb-wheel, infrared port, USB port, docking station and/or a pointer device such as a stylus. The one or more buttons (not shown) can include an up/down button for volume control of speaker  428  and/or microphone  430 . 
     In one implementation, a pressing of the button for a first duration may disengage a lock of touch screen  446 ; and a pressing of the button for a second duration that is longer than the first duration may turn power to the mobile device on or off. The user may be able to customize a functionality of one or more of the buttons. Touch screen  446  can, for example, also be used to implement virtual or soft buttons and/or a keyboard. 
     In some implementations, the mobile device can present recorded audio and/or video files, such as MP3, AAC, and MPEG files. In some implementations, the mobile device can include the functionality of an MP3 player, such as an iPod Touch™. 
     Memory interface  402  can be coupled to memory  450 . Memory  450  can include high-speed random access memory and/or non-volatile memory, such as one or more magnetic disk storage devices, one or more optical storage devices, and/or flash memory (e.g., NAND, NOR). Memory  450  can store operating system  452 , such as Darwin, RTXC, LINUX, UNIX, OS X, WINDOWS, or an embedded operating system such as VxWorks. Operating system  452  may include instructions for handling basic system services and for performing hardware dependent tasks. In some implementations, operating system  452  can be a kernel (e.g., UNIX kernel). 
     Memory  450  may also store communication instructions  454  to facilitate communicating with one or more additional devices, one or more computers and/or one or more servers. Memory  450  may include graphical user interface instructions  456  to facilitate graphic user interface processing; sensor processing instructions  458  to facilitate sensor-related processing and functions; phone instructions  460  to facilitate phone-related processes and functions; electronic messaging instructions  462  to facilitate electronic-messaging related processes and functions; web browsing instructions  464  to facilitate web browsing-related processes and functions; media processing instructions  466  to facilitate media processing-related processes and functions; GPS/Navigation instructions  468  to facilitate GPS and navigation-related processes and instructions; camera instructions  470  to facilitate camera-related processes and functions; accuracy data  472  and accuracy calculation instructions  474  to facilitate magnetometer calibration, as described in reference to  FIG. 2 . In some implementations, GUI instructions  456  and/or media processing instructions  466  implement the features and operations described in reference to  FIGS. 1-4 . 
     Memory  450  may also store other software instructions (not shown), such as web video instructions to facilitate web video-related processes and functions; and/or web shopping instructions to facilitate web shopping-related processes and functions. In some implementations, media processing instructions  466  are divided into audio processing instructions and video processing instructions to facilitate audio processing-related processes and functions and video processing-related processes and functions, respectively. An activation record and International Mobile Equipment Identity (IMEI) or similar hardware identifier can also be stored in memory  450 . 
     Each of the above identified instructions and applications can correspond to a set of instructions for performing one or more functions described above. These instructions need not be implemented as separate software programs, procedures, or modules. Memory  450  can include additional instructions or fewer instructions. Furthermore, various functions of the mobile device may be implemented in hardware and/or in software, including in one or more signal processing and/or application specific integrated circuits. 
     Example Error Indicators 
       FIGS. 5A-5B  are screenshots of a map user interface of a mobile device having a magnetometer, including a heading error indicator in accordance with some implementations. Referring to  FIG. 5A , user interface  510  displays a portion of a map including heading error indicator  516 . Marker  514  shows the location of the mobile device on the map. Position error indicator  512  surrounds marker  514  and indicates the position accuracy of the mobile device. The actual location of the mobile device is somewhere within indicator  512 . Heading error indicator  516  indicates heading error. The actual heading is somewhere within the angle δ 1 . 
     Referring to  FIG. 5B , heading error indicator  516  displayed in user interface  510  is indicating a larger heading error than displayed in  FIG. 5B . That is the actual heading is somewhere within the angle δ 2 , where δ 1 &lt;δ 2 . The accuracy metric computed in equations (11) can be presented in other graphical forms or as test. In some implementations, an audio output (e.g., synthesized speech, beep) can be presented to the user. 
       FIG. 5C  is a screen shot of a map user interface of a mobile device having a magnetometer, and illustrating the presenting of an indication of the accuracy metric on the mobile device telephone using tactile feedback (e.g., vibration). 
     The disclosed and other embodiments and the functional operations described in this specification can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them. The disclosed and other embodiments can be implemented as one or more computer program products, i.e., one or more modules of computer program instructions encoded on a computer-readable medium for execution by, or to control the operation of, data processing apparatus. The computer-readable medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, or a combination of one or more them. The term “data processing apparatus” encompasses all apparatus, devices, and machines for processing data, including by way of example a programmable processor, a computer, or multiple processors or computers. The apparatus can include, in addition to hardware, code that creates an execution environment for the computer program in question, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of one or more of them. 
     A computer program (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program does not necessarily correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub-programs, or portions of code). A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network. 
     The processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and generating output. The processes and logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit). 
     Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for performing instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks. However, a computer need not have such devices. Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry. 
     To provide for interaction with a user, the disclosed embodiments can be implemented on a computer having a display device, e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, for displaying information to the user and a keyboard and a pointing device, e.g., a mouse or a trackball, by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback, e.g., visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input. 
     The disclosed embodiments can be implemented in a computing system that includes a back-end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front-end component, e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of what is disclosed here, or any combination of one or more such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (“LAN”) and a wide area network (“WAN”), e.g., the Internet. 
     While this specification contains many specifics, these should not be construed as limitations on the scope of what being claims or of what may be claimed, but rather as descriptions of features specific to particular embodiments. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination. 
     Similarly, while operations are depicted in the drawings in a particular order, this should not be understand as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products. 
     Particular embodiments of the subject matter described in this specification have been described. Other embodiments are within the scope of the following claims. For example, the actions recited in the claims can be performed in a different order and still achieve desirable results. As one example, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In certain implementations, multitasking and parallel processing may be advantageous.

Metadata:
Filing Date: 20121105
Publication Date: 20140325
Grant Date: 20140325
Priority Date: 20090605
Inventors: MAYOR ROBERT
PIEMONTE PATRICK
HUANG RONALD KERYUAN
PATEL PARIN
Assignee: APPLE INC
CPC Classifications: [{"code": "G01V3/087", "inventive": true, "first": false, "tree": "[]"}, {"code": "G01R33/10", "inventive": true, "first": false, "tree": "[]"}, {"code": "G01C17/38", "inventive": true, "first": true, "tree": "[]"}, {"code": "G08B7/06", "inventive": true, "first": false, "tree": "[]"}]
Family ID: 43299691