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Author: Robert Allen Crotteau
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
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Book Description
The object of this study is to find an approximation to the discrete optimal Kalman filter gain schedule by closed-form analytic expressions. In doing so, required table storage and/or on-line computation time can be reduced at little expense in terms of filter performance degradation. The method of least squares was used to determine the closed-form solution which was the best fit to the discrete Kalman filter gain schedule. The criterion for performance degradation was the difference between the values of the diagonal elements of the estimation covariance matrix, obtained by using the Kalman gain schedule, and the corresponding values obtained by using the closed-form analytic expressions for the elements of the gain matrix. Examples are presented to show that near-optimal results were obtained using this method. A comparison of the results of this study with another near-optimal estimation scheme is also included. (Author).
Author: Robert Allen Crotteau
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
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Book Description
The object of this study is to find an approximation to the discrete optimal Kalman filter gain schedule by closed-form analytic expressions. In doing so, required table storage and/or on-line computation time can be reduced at little expense in terms of filter performance degradation. The method of least squares was used to determine the closed-form solution which was the best fit to the discrete Kalman filter gain schedule. The criterion for performance degradation was the difference between the values of the diagonal elements of the estimation covariance matrix, obtained by using the Kalman gain schedule, and the corresponding values obtained by using the closed-form analytic expressions for the elements of the gain matrix. Examples are presented to show that near-optimal results were obtained using this method. A comparison of the results of this study with another near-optimal estimation scheme is also included. (Author).
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
The object of this study is to find an approximation to the discrete optimal Kalman filter gain schedule by closed-form analytic expressions. In doing so, required table storage and/or on-line computation time can be reduced at little expense in terms of filter performance degradation. The method of least squares was used to determine the closed-form solution which was the best fit to the discrete Kalman filter gain schedule. The criterion for performance degradation was the difference between the values of the diagonal elements of the estimation covariance matrix, obtained by using the Kalman gain schedule, and the corresponding values obtained by using the closed-form analytic expressions for the elements of the gain matrix. Examples are presented to show that near-optimal results were obtained using this method. A comparison of the results of this study with another near-optimal estimation scheme is also included. (Author).
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 1028
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Book Description
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Author: Naval Postgraduate School (U.S.)
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 792
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Author: Naval Postgraduate School (U.S.)
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 628
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Book Description
Author: Felix Govaers
Publisher: BoD – Books on Demand
ISBN: 1838805362
Category : Computers
Languages : en
Pages : 130
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Book Description
Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some "awareness" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not.
Author: Guanrong Chen
Publisher: World Scientific
ISBN: 9814504351
Category : Technology & Engineering
Languages : en
Pages : 242
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Book Description
Kalman filtering algorithm gives optimal (linear, unbiased and minimum error-variance) estimates of the unknown state vectors of a linear dynamic-observation system, under the regular conditions such as perfect data information; complete noise statistics; exact linear modeling; ideal well-conditioned matrices in computation and strictly centralized filtering.In practice, however, one or more of the aforementioned conditions may not be satisfied, so that the standard Kalman filtering algorithm cannot be directly used, and hence “approximate Kalman filtering” becomes necessary. In the last decade, a great deal of attention has been focused on modifying and/or extending the standard Kalman filtering technique to handle such irregular cases. It has been realized that approximate Kalman filtering is even more important and useful in applications.This book is a collection of several tutorial and survey articles summarizing recent contributions to the field, along the line of approximate Kalman filtering with emphasis on both its theoretical and practical aspects.
Author: Farshad Rafii
Publisher:
ISBN:
Category : Kalman filtering
Languages : en
Pages : 268
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Book Description
Author: O.L.V. Costa
Publisher: Springer Science & Business Media
ISBN: 1846280826
Category : Mathematics
Languages : en
Pages : 287
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Book Description
This will be the most up-to-date book in the area (the closest competition was published in 1990) This book takes a new slant and is in discrete rather than continuous time
Author: Dennis W. Camp
Publisher:
ISBN:
Category : Aerodynamics
Languages : en
Pages : 272
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Book Description
