System and Method of Improved Kalman Filtering for Estimating the State of a Dynamic System
First Claim
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1. A method of estimating the state of a modeled dynamic system, the method comprising:
- generating an observer in an electronic device for estimating of at least one state variable associated with the system,wherein said observer defines a covariance matrix statistically relating the at least one state variable;
receiving sensor data at a electronic device from a sensor, the sensor data being associated with the at least one state variable;
updating, in a memory of the electronic device, the at least one state variable based on the received sensor data and the generated observer;
updating, in a memory of the electronic device, the covariance matrix based on the updated at least one state variable;
determining whether an element of the main diagonal of the updated covariance matrix has a value that is less than zero; and
storing a specified value to the covariance matrix in the memory of the electronic device based on the determining.
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Abstract
Embodiments include systems and methods of estimating at least one state of a modeled dynamic system. In particular, in one embodiment, an observer such as an extended Kalman filter is used to estimate the state of a modeled dynamic system. A covariance matrix associated with state variables of the observer is periodically checked for compliance with a specified condition, e.g., positive definiteness. If the matrix deviates from the specified condition, the matrix is set to a specified value.
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Citations
22 Claims
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1. A method of estimating the state of a modeled dynamic system, the method comprising:
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generating an observer in an electronic device for estimating of at least one state variable associated with the system, wherein said observer defines a covariance matrix statistically relating the at least one state variable; receiving sensor data at a electronic device from a sensor, the sensor data being associated with the at least one state variable; updating, in a memory of the electronic device, the at least one state variable based on the received sensor data and the generated observer; updating, in a memory of the electronic device, the covariance matrix based on the updated at least one state variable; determining whether an element of the main diagonal of the updated covariance matrix has a value that is less than zero; and storing a specified value to the covariance matrix in the memory of the electronic device based on the determining. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system for estimating at least one state of a modeled dynamic system, the system comprising:
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a processor configured to; provide an observer configured to estimate at least one state variable associated with the modeled dynamic system, wherein said observer defines a covariance matrix statistically relating the at least one state variable; a memory configured to store data associated with the observer, said stored data comprising the at least one state variable and the covariance matrix; wherein the processor is further configured to; receive sensor data in electronic form from a sensor, the sensor data being associated with the at least one state variable; update, in the memory, the at least one state variable of the observer based on the received sensor data; update the covariance matrix in the memory based on the updated at least one state variable; determine whether an element of the main diagonal of the updated covariance matrix has a value that is less than zero; and store a specified value to the covariance matrix in the memory based on the determination. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A computer-program product for estimating the state of a modeled dynamic system, comprising:
a computer-readable medium having stored thereon codes executable by at least one processor to perform the method comprising; generating an observer in an electronic device for estimating of at least one state variable associated with the system, wherein said observer defines a covariance matrix statistically relating the at least one state variable; receiving sensor data at a electronic device from a sensor, the sensor data being associated with the at least one state variable; updating, in a memory of the electronic device, the at least one state variable based on the received sensor data and the generated observer; updating, in a memory of the electronic device, the covariance matrix based on the updated at least one state variable; determining whether an element of the main diagonal of the updated covariance matrix has a value that is less than zero; and storing a specified value to the covariance matrix in the memory of the electronic device based on the determining. - View Dependent Claims (16, 17, 18, 19, 20, 21)
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22. A system for estimating at least one state of a modeled dynamic system, the system comprising:
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means for processing configured to; provide an observer configured to estimate the at least one state variable associated with the modeled dynamic system, wherein said observer defines a covariance matrix statistically relating the at least one state variable; means for storing data associated with the observer, said stored data comprising the at least one state variable and the covariance matrix; wherein the processing means is further configured to; receive sensor data in electronic form from a sensor, the sensor data being associated with the at least one state variable; update, in the memory, the at least one state variable of the observer based on the received sensor data; update the covariance matrix in the storing means based on the updated at least one state variable; determine whether an element of the main diagonal of the updated covariance matrix has a value that is less than zero; and store a specified value to the covariance matrix in the storing means based on the determination.
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Specification