In 2009 we learned that Apple began researching new sophisticated in-vehicle navigation systems. Then in 2011 we further learned that they were working on ways to advance their "Maps + Compass" iOS application with augmented reality. And before 2011 closed out, Apple acquired C3 Technologies which is likely to bring photo-realistic mapping to iOS devices in the not-too-distant future. Adding to this momentum we learn today that Apple has invented an advanced magnetometer application and related system. It's designed specifically to provide iOS devices with greater mapping and navigation accuracy. And to be absolutely clear about their market focus, Apple specifically lists navigation systems for vehicles, aircraft and watercraft.
The Problem with Today's Magnetometers
Modern mobile devices may include a variety of applications that depend on an accurate estimate of device location, such as a map application or location-based services (LBS) application. An integrated Global Positioning System (GPS) receiver and onboard sensors (e.g., accelerometers, gyroscopes) can be used to determine location and orientation of the device, and even provide a rough estimate of heading.
To improve heading accuracy, a magnetometer can be included on the device. Conventional magnetometer calibration procedures may require the user to maneuver the device in a defined pattern to generate data that can be used to calibrate the magnetometer. Such manual calibration procedures are required to be performed each time the magnetometer error exceeds a threshold value. Additionally, the user may have to repeat the calibration procedure if performed incorrectly.
Apple is about to change all of that with a new real-time calibration system and method for iOS devices that have an onboard magnetometer. The new system will use an estimator to estimate magnetometer calibration parameters and a magnetic field external to the mobile device (e.g., the earth magnetic field).
Technically, the calibration parameters can be used to calibrate uncalibrated magnetometer readings output from the onboard magnetometer. The external magnetic field can be modeled as a weighted combination of a past estimate of the external magnetic field and the asymptotic mean of that magnetic field, perturbed by a random noise (e.g., Gaussian random noise). The weight can be adjusted based on a measure of the statistical uncertainty of the estimated calibration parameters and the estimated external magnetic field. The asymptotic mean of the external magnetic field can be modeled as a time average of the estimated external magnetic field.
Utilizing Different Calculators
In some implementations, a differential statistics calculator can be used to determine differences between the calibrated magnetometer readings (i.e., raw magnetometer readings corrected by estimated calibration parameters) and the estimated external magnetic field projected into device coordinates. This enables possible detection as well as resolution of magnetic interference that can adversely affect heading calculations.
In some implementations, a compass heading calculator can use the estimated external magnetic field and a three-dimensional attitude estimate of the device to provide a responsive heading vector. A calibration level can be used with a World Magnetic Model (WMM) to determine compass heading accuracy.
In some implementations, the attitude of the mobile device may not be available or accurate enough to estimate magnetometer calibration parameters. In such situations, an attitude-independent estimator can use an algebraic linearization formulation of a canonical calibration equation to estimate the bias vector based on an assumption that calibrated magnetometer readings lie on the surface of a sphere.
Apple Sees Two Advantages
Various implementations of the subject matter described here may provide one or more of the following advantages. In one or more implementations, the usage of the mobile device attitude information enables a more stable and more accurate estimation of magnetometer calibration parameters. More importantly, accurate calibration can be achieved with less user motion (e.g., less data required) resulting in a speed-up of the calibration process. Thus the magnetometer can be calibrated using motion data generated from a user's normal use of the mobile device without explicit user intervention.
Another advantage is provided by using the estimated external magnetic field (projected into the device coordinate frame) to provide smooth, responsive, calibrated magnetometer output that results in a more accurate and lag-free heading vector for navigation applications running on the mobile device. Without the estimated external magnetic field, calibrated magnetometer readings are obtained from raw (uncalibrated) readings corrected by the estimated calibration parameters. Since the raw readings are usually noisy, the resulting magnetometer heading vectors have to be smoothed by a low-pass filter which introduces noticeable lag.
Apple's Exemplary Compass Application
In Apple's patent FIG. 1 below we see a block diagram of an exemplary compass application (#100) including an attitude-dependent calibrator. In some implementations, the compass application can include an attitude-dependent calculator (#102), a compass heading calculator (#104), a compass heading accuracy calculator (#106) and a calibration database (#108).
The compass application can be a software program running on a mobile device having a magnetometer, including but not limited to: a smart phone, vehicle navigation system, e-mail device, game device, laptop computer, electronic tablet, media player or any other device that includes a magnetometer. The mobile device can include one or more onboard sensors for determining the attitude (e.g., a gyro sensor) and acceleration (e.g., an accelerometer) of the mobile device.
Beyond iOS Devices, the Advanced Magnetometer Could be used in Vehicles, Aircraft and Watercraft
In some implementations, raw or uncalibrated magnetometer readings are input to the attitude-dependent calibrator. The readings can be read from a magnetometer onboard the mobile device. A magnetometer is an instrument that can sense the strength and direction of the magnetic field in its vicinity. Magnetometers are useful for applications that require dead reckoning or headings, such as navigation applications for vehicles, aircraft and watercraft.
Detailed Overview of Apple's Exemplary Attitude-Dependent Calculator
Apple's patent FIG. 2 presented below is a detailed overview of their exemplary attitude-dependent calculator of FIG. 1.
Patent Credits and Some Closing Thoughts
Apple's patent application was originally filed in Q4 2010 by sole inventor Xiaoyuan Tu.
When Apple launched their 2012 iPad, one of the factoids that quickly emerged was that they had switched from Google Mapping services to that of OpenStreetMap for iPhoto. While Apple's recent pull-away from Google mapping services may have marked their first step in abandoning Google Maps altogether, the growing evidence is clearly indicating that it won't be their last.
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