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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Choi, D. Shin, V. Byung-Ha Ahn Jun Il Ahn |
| Copyright Year | 2004 |
| Description | Author affiliation: Dept. of Mechatronics, Gwangju Inst. of Sci. & Technol., South Korea (Choi, D.; Shin, V.; Byung-Ha Ahn; Jun Il Ahn) |
| Abstract | This paper considers the problem of fusion of local filters. We derive an optimal mean square combination of arbitrary number of correlated estimates. In particular, for two sensors this combination represents the well-known Millman and Bar-Shalom-Campo formulae for uncorrelated and correlated estimation errors, respectively. The new combination is applied to an adaptive filtering problem and fusion of multisensor estimates. Two suboptimal filters with a parallel structure are herein proposed. The equation for error covariance characterizing the mean square accuracy of these filters is derived. In consequence of parallel structure of the filters, parallel computers can be used for their design. The examples demonstrate the effect of the common process noise on the fusion of the state estimates of a target based on measurements obtained by two different sensors. |
| Sponsorship | IEEE |
| Starting Page | 22 |
| Ending Page | 27 |
| File Size | 1097199 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780386396 |
| DOI | 10.1109/ISPACS.2004.1439008 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-11-18 |
| Publisher Place | South Korea |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Adaptive filters Sensor fusion Estimation error Filtering Target tracking Data processing Signal processing algorithms Mechatronics Sensor phenomena and characterization Equations |
| Content Type | Text |
| Resource Type | Article |
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