Abstract
In many practical systems there is a delay in some of the sensor devices, for instance vision measurements that may have a long processing time. How to fuse these measurements in a Kalman filter is not a trivial problem if the computational delay is critical. Depending on how much time there is at hand, the designer has to make trade offs between optimality and computational burden of the filter. In this paper various methods in the literature along with a new method proposed by the authors will be presented and compared. The new method is based on “extrapolating” the measurement to present time using past and present estimates of the Kalman filter and calculating an optimal gain for this extrapolated measurement
Original language | English |
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Title of host publication | Decision and Control, 1998. Proceedings of the 37th IEEE Conference on |
Volume | 4 |
Publisher | IEEE |
Publication date | 1998 |
Pages | 3972-3977 |
ISBN (Print) | 0-7803-4394-8 |
DOIs | |
Publication status | Published - 1998 |
Event | 37th IEEE Conference on Decision and Control - Tampa, FL, United States Duration: 16 Dec 1998 → 18 Dec 1998 Conference number: 37 http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6103 |
Conference
Conference | 37th IEEE Conference on Decision and Control |
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Number | 37 |
Country/Territory | United States |
City | Tampa, FL |
Period | 16/12/1998 → 18/12/1998 |
Internet address |