Name
Title | ||
|---|---|---|
Estimation fusion algorithms in the presence of partially known cross-correlation of local estimation errors. |
Abstract | ||
|---|---|---|
This paper addresses estimation fusion when the cross-correlation of local estimation errors is partially known. The statistical dependence of local estimation errors is first discussed, and then the concept of correlation coefficient is introduced to model the cross-correlation approximately. Two algorithms are proposed. One is based on min-max technique, which minimizes the maximal Mahalanobis distance between two fused estimates. The other one uses the prior distribution of the correlation coefficient and obtains a closed form of estimation fusion with the help of a series of matrix manipulations. Compared with some available algorithms in literature, simulation results demonstrate the effectiveness of the proposed approaches. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.inffus.2013.09.003 | Information Fusion |
Keywords | Field | DocType |
correlation coefficient,paper addresses estimation fusion,matrix manipulation,fused estimate,maximal mahalanobis distance,available algorithm,local estimation error,estimation fusion algorithm,closed form,estimation fusion,mahalanobis distance,cross correlation | Cross-correlation,Correlation coefficient,Pattern recognition,Matrix (mathematics),Fusion,Algorithm,Mahalanobis distance,Artificial intelligence,Prior probability,Mathematics | Journal |
Volume | ISSN | Citations |
18 | 1566-2535 | 5 |
PageRank | References | Authors |
0.47 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongyan Zhu | 1 | 42 | 8.57 |
| Qiaozhu Zhai | 2 | 12 | 3.75 |
| Mingwei Yu | 3 | 5 | 1.83 |
| Chongzhao Han | 4 | 446 | 71.68 |