LORD 6253-4220, Руководство пользователя

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3DM
®
-GX5-25
User Manual
The 3DM-GX5-25 runs an Auto-Adaptive Extended Kalman Filter as a full-state dynamics model. The
state propagation utilizes Newton’s and Euler’s equations of motion with the acceleration and angular
rate treated as control inputs.
The Kalman filter estimates the full state of attitude for a total of 16 states: 4 attitude (quaternion), 3
gyro bias, 3 magnetometer bias, and 6 magnetometer scale-factor states. The gyro bias states are
estimated to compensate for the time-varying biases inherent in MEMS gyros, which are the largest
error sources for these devices. The magnetometer bias and scale- factor states are estimated to
compensate for magnetic field distortions (hard- and soft-iron errors). Note that only distortions that are
fixed with respect to the sensor body coordinate frame of reference can be tracked. Tracking these
errors automatically enhances the overall accuracy of the sensor and makes it easier to deploy.
The Kalman filter also provides statistical information about the quality of the estimated states
described in a covariance matrix. The diagonal terms of the matrix are the variance of each state, thus
the square root of these values are 1- sigma standard deviations. These values give the filter’s
estimation of how well it knows the individual states, given what it knows about the statistical properties
of the noise sources of the various sensors and also provide feedback to the user as uncertainty values.
5.11 Estimation Filter Convergence
5.11.1 Initial Convergence
After a successful initialization, a period of convergence for the Kalman filter states occurs. Roll and
pitch angles typically converge very quickly. Heading, accelerometermagnetometer bias, and gyro
bias take more time to converge. If the initial attitude estimate provided to the filter is well outside of
the true attitude, the filter may diverge and never recover. This is most likely to occur for the heading
estimate when a poor value is used for initialization and when the vibration environment is strong.
Should this occur, it is recommended that the filter be reset and new attitude estimate provided.
5.11.2 Output Uncertainty
The 3DM-GX5-25 estimation data set includes a filter status field that contains a set of status flags.
These flags pertain to high covariance values for attitude and inertial sensor parameters. These
flags should be monitored and cross-checked against the corresponding uncertainty fields when
they appear. This can assist in determining how trustworthy the solution generated by the Kalman
filter is. When the filter is first initialized, it is likely that some of these values will be beyond limits, and
the flags may be asserted. This fact should be taken into account when developing automated
monitoring systems.
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