Methods, devices and systems for determining the zero rate output of a sensor
First Claim
Patent Images
1. A device comprising:
- at least one sensor configured to sense rotation of said device about at least one axis and to generate at least one output associated therewith; and
a zero-rate output (ZRO) tracking filter configured to receive said at least one output and to compensate said at least one output for a bias associated with said at least one sensor,wherein said ZRO filter is implemented as a Kalman filter having at least one constraint enforced on at least one parameter associated therewith,further wherein said at least one constraint is selected based on whether said ZRO filter has converged on an estimate of said bias, such that a first constraint is applied before said ZRO filter has converged on said estimate of said bias and that a second constraint, different from said first constraint, is applied after said ZRO filter has converged on said estimate of said bias,wherein said first constraint ensures a minimum convergence speed by using a minimum Kalman gain before convergence (K1) and said second constraint, different from said first constraint, limits a convergence speed by using a maximum Kalman gain after convergence (K2), andwherein K1 and K2 are calculated to determine a total Kalman gain.
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Abstract
A bias value associated with a sensor, e.g., a time-varying, non-zero value which is output from a sensor when it is motionless, is estimated using a ZRO-tracking filter which is a combination of a moving-average filter and a Kalman filter having at least one constraint enforced against at least one operating parameter of the Kalman filter. It achieves faster convergence on an estimated bias value and produces less estimate error after convergence. A resultant bias estimate may then be used to compensate the biased output of the sensor in, e.g., a 3D pointing device.
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Citations
24 Claims
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1. A device comprising:
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at least one sensor configured to sense rotation of said device about at least one axis and to generate at least one output associated therewith; and a zero-rate output (ZRO) tracking filter configured to receive said at least one output and to compensate said at least one output for a bias associated with said at least one sensor, wherein said ZRO filter is implemented as a Kalman filter having at least one constraint enforced on at least one parameter associated therewith, further wherein said at least one constraint is selected based on whether said ZRO filter has converged on an estimate of said bias, such that a first constraint is applied before said ZRO filter has converged on said estimate of said bias and that a second constraint, different from said first constraint, is applied after said ZRO filter has converged on said estimate of said bias, wherein said first constraint ensures a minimum convergence speed by using a minimum Kalman gain before convergence (K1) and said second constraint, different from said first constraint, limits a convergence speed by using a maximum Kalman gain after convergence (K2), and wherein K1 and K2 are calculated to determine a total Kalman gain. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A device comprising:
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at least one sensor configured to sense rotation of said device about at least one axis and to generate at least one output associated therewith; and a zero rate output (ZRO) filter configured to receive said at least one output and to compensate said at least one output for a bias associated with said at least one sensor, wherein said ZRO filter is implemented as a combination of a Kalman filter and a moving-average filter, wherein said Kalman filter has at least one constraint enforced on at least one parameter associated therewith, further wherein said at least one constraint is selected based on whether said Kalman filter has converged on an estimate of said bias, such that a first constraint is applied before said Kalman filter has converged on said estimate of said bias and that a second constraint, different from said first constraint, is applied after said Kalman filter has converged on said estimate of said bias, wherein said first constraint ensures a minimum convergence speed by using a minimum Kalman gain before convergence (K1) and said second constraint, different from said first constraint, limits a convergence speed by using a maximum Kalman gain after convergence (K2), and wherein K1 and K2 are calculated to determine a total Kalman gain. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20)
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21. A method for filtering an output of a sensor to compensate for bias error, the method comprising:
filtering said output of said sensor using a shared recursive computation architecture of a standard Kalman filter, a cumulative moving-average filter, and an exponential moving-average filter, wherein a filter gain is adaptively modified as a function of Kalman gain, a cumulative moving-average coefficient, and an exponential moving-average coefficient. - View Dependent Claims (22, 23, 24)
Specification