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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kim, K.H. |
| Copyright Year | 1994 |
| Description | Author affiliation: Mitre Corp., Bedford, MA, USA (Kim, K.H.) |
| Abstract | This paper describes techniques for track level fusion of surveillance data that are applicable to existing and near term tactical surveillance systems. The linear optimal fused estimate is a convex combination of remote estimates with weights being the estimation confidences (covariances). The covariance based algorithm is most applicable where the track estimate is generated by a Kalman filter based tracking system. When track covariance is not available, such as in /spl alpha/-/spl beta/ tracking systems, an estimated covariance can be used for track fusion. In addition, track fusion also requires accounting for the cross covariance between tracks. Various approaches to estimating the auto covariances and the cross covariances are examined, and the performance is evaluated through computer simulations. |
| Starting Page | 1037 |
| Ending Page | 1041 |
| File Size | 447521 |
| Page Count | 5 |
| File Format | |
| ISBN | 0780317831 |
| DOI | 10.1109/ACC.1994.751905 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1994-06-29 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Target tracking Surveillance Density functional theory Postal services Fusion power generation Filters Computer architecture Application software Communication networks Approximation methods |
| Content Type | Text |
| Resource Type | Article |
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