Characterization of Kalman filter residuals in the presence of mismodeling
The mean and covariance of a Kalman filter residual are computed for specific cases in which the Kalman filter model differs from a linear model that accurately represents the true system (the truth model). Multiple model adaptive estimation (MMAE) uses a bank of Kalman filters, each with a differen...
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| Veröffentlicht in: | IEEE transactions on aerospace and electronic systems 2000-01, Vol.36 (1), p.114-131 |
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| container_title | IEEE transactions on aerospace and electronic systems |
| container_volume | 36 |
| creator | Hanlon, P.D. Maybeck, P.S. |
| description | The mean and covariance of a Kalman filter residual are computed for specific cases in which the Kalman filter model differs from a linear model that accurately represents the true system (the truth model). Multiple model adaptive estimation (MMAE) uses a bank of Kalman filters, each with a different internal model, and a hypothesis testing algorithm that uses the residuals from this bank of Kalman filters to estimate the true system model. At most, only one Kalman filter model will exactly match the truth model and will produce a residual whose mean and standard deviation have already been analyzed. All of the other filters use internal models that mismodel the true system. We compute the effects of a mismodeled input matrix, output matrix, and state transition matrix on these residuals. The computed mean and covariance are compared with simulation results of flight control failures that correspond to mismodeled input matrices and output matrices. |
| doi_str_mv | 10.1109/7.826316 |
| format | Article |
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The computed mean and covariance are compared with simulation results of flight control failures that correspond to mismodeled input matrices and output matrices.</description><subject>Adaptive estimation</subject><subject>Aerospace control</subject><subject>Algorithms</subject><subject>Banks</subject><subject>Computation</subject><subject>Computational modeling</subject><subject>Covariance</subject><subject>Covariance matrix</subject><subject>Kalman filters</subject><subject>Matched filters</subject><subject>Mathematical analysis</subject><subject>Matrices</subject><subject>Matrix methods</subject><subject>Military computing</subject><subject>Nonlinear filters</subject><subject>Standard deviation</subject><subject>State estimation</subject><subject>Studies</subject><subject>System testing</subject><issn>0018-9251</issn><issn>1557-9603</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2000</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqN0k1LxDAQBuAgCq6r4NlT8SBeqpmk-TrK4rfgRc8lTSeapduuSXvQX2-XFQUPrqcwMw8vSRhCDoGeAVBzrs40kxzkFpmAECo3kvJtMqEUdG6YgF2yl9J8LAtd8Am5m73aaF2PMXzYPnRt1vns3jYL22Y-NGM_i5hCPdgmZaHN-lfMlmMHW4crughp0dXYhPZln-z4UeHB1zklz1eXT7Ob_OHx-nZ28ZC7Qpg-9wqqympAY4uKC62FrEBS56qaVd7UzljlmVQ1AyhqWwl03qKglntTgAY-JSfr3GXs3gZMfTlewmHT2Ba7IZXMMCYk05uh1gUAl_-AYKShbDNUDAwI-BdUnK8ST_-EIBUwzqRcZR7_ovNuiO341eX4EK05Y_CT52KXUkRfLmNY2PheAi1XC1Kqcr0gIz1a04CI3-xr-Amw4LPJ</recordid><startdate>200001</startdate><enddate>200001</enddate><creator>Hanlon, P.D.</creator><creator>Maybeck, P.S.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| source | IEEE Electronic Library (IEL) |
| subjects | Adaptive estimation Aerospace control Algorithms Banks Computation Computational modeling Covariance Covariance matrix Kalman filters Matched filters Mathematical analysis Matrices Matrix methods Military computing Nonlinear filters Standard deviation State estimation Studies System testing |
| title | Characterization of Kalman filter residuals in the presence of mismodeling |
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