System and method for estimating velocity using reliability indexed sensor fusion
First Claim
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1. A system for dynamically estimating longitudinal and lateral velocities of a vehicle comprising:
- a vehicle sensor producing a signal indicative of a vehicle state; and
a processor communicating with said vehicle sensor and configured to receive said signal, said processor further configured to;
calculate an approximated velocity of the vehicle;
determine a noise covariance associated with said signal and said approximated velocity; and
estimate the velocity of said vehicle using said signal, said approximated velocity and said noise covariance.
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Abstract
A method and system for vehicle velocity estimation. The method and system effectively combine vehicle kinetic and kinematic models to determine the noise covariance or reliability of vehicle sensor signals, and vehicle approximated velocity. The vehicle approximated velocity, sensor signals, and noise covariances are used in conjunction with a Kalman filter to determine the estimated velocity of the vehicle. The noise covariance is calculated from the relationship between various sensor signals and calculated values by determining if the sensor signal and calculated values correspond to a vehicle operating state.
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Citations
20 Claims
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1. A system for dynamically estimating longitudinal and lateral velocities of a vehicle comprising:
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a vehicle sensor producing a signal indicative of a vehicle state; and
a processor communicating with said vehicle sensor and configured to receive said signal, said processor further configured to;
calculate an approximated velocity of the vehicle;
determine a noise covariance associated with said signal and said approximated velocity; and
estimate the velocity of said vehicle using said signal, said approximated velocity and said noise covariance. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A system for dynamically estimating longitudinal and lateral velocities of a vehicle comprising:
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a wheel speed sensor producing an angular wheel speed signal indicative of a vehicle state;
an accelerometer producing a longitudinal acceleration signal and a lateral acceleration signal;
a yaw rate sensor producing a yaw rate signal;
a steering wheel angle sensor producing a steering wheel angle signal;
a brake sensor producing a brake position signal;
a throttle sensor producing a throttle position signal; and
a processor communicating with said wheel speed sensor and said accelerometer and wherein said processor is configured to receive said wheel speed signal, said lateral acceleration signal and said longitudinal acceleration signal, said processor further configured to;
calculate an approximated longitudinal velocity;
calculate an approximated lateral velocity of the vehicle using said yaw rate signal and said steering wheel angle signal;
determine a noise covariance associated with said signal and said approximated velocity using said longitudinal acceleration signal, said lateral acceleration signal, said yaw rate signal, said brake position signal, said throttle position signal and said steering wheel angle signal, said noise covariance including a longitudinal system noise covariance, a lateral system noise covariance, a longitudinal measurement noise covariance, and a lateral measurement noise covariance, and wherein said longitudinal system noise covariance is inversely related to the reliability of said longitudinal acceleration signal, said lateral system noise covariance is inversely related to the reliability of said lateral acceleration signal, said longitudinal measurement noise covariance is inversely related to the reliability of said approximated longitudinal velocity, and said lateral measurement noise covariance is inversely related to the reliability of said approximated lateral velocity; and
estimate the velocity of said vehicle using said signal, said approximated velocity and said noise covariance. - View Dependent Claims (11, 12, 13, 14, 15)
said longitudinal system noise covariance Qx is defined by:
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16. A method of estimating a velocity of a vehicle comprising:
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receiving sensor signals indicative of a vehicle travel state;
calculating an approximated velocity using said sensor signals;
determining a noise covariance associated with said sensor signals and said approximated velocity;
estimating a velocity of the vehicle with a Kalman filter framework, said Kalman filter framework using said noise covariance, said approximated velocity, and said sensor signals. - View Dependent Claims (17)
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18. A method of estimating a velocity of a vehicle comprising:
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receiving sensor signals indicative of a vehicle travel state, including a wheel speed sensor signal, a lateral acceleration signal and a longitudinal acceleration signal;
calculating an approximated lateral velocity and an approximated longitudinal velocity using said sensor signals;
determining a noise covariance associated with said sensor signals, said longitudinal acceleration signal, said lateral acceleration signal said lateral approximated velocity and said longitudinal approximated velocity; and
estimating a velocity of the vehicle with a Kalman filter framework, said Kalman filter framework using said noise covariance, said approximated velocity, and said sensor signals. - View Dependent Claims (19)
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20. A system for estimating a velocity of a vehicle, said vehicle having a driven wheel, a throttle, a brake pedal, and a steering wheel, wherein each of said throttle, said brake pedal, and said steering wheel have a rest position, said system comprising:
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an accelerometer producing an acceleration signal;
a wheel speed sensor producing a wheel speed signal;
a yaw rate sensor producing a yaw rate signal;
a steering wheel angle sensor producing a steering wheel angle signal;
a brake position sensor producing a brake pedal position signal;
a throttle position sensor producing a throttle position signal;
a processor communicating with said sensors and configured to receive said signals;
a velocity calculation module receiving said wheel speed sensor signal and calculating an approximated velocity of the vehicle;
a noise covariance module receiving said acceleration signal and at least one other of said signals, said noise covariance module calculating a noise covariance associated with said approximated velocity and said acceleration signal, said acceleration signal and said approximated velocity each having an associated reliability, wherein said noise covariance is inversely related to said reliability; and
a Kalman filter module estimating a velocity of the vehicle, said Kalman filter module including a Kalman filter framework configured to receive said noise covariance, said approximated velocity and said acceleration signal.
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Specification