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Airborne multi-sensor target recognition method based on weighted fuzzy reasoning network and improved DS evidence theory
| Content Provider | Scilit |
|---|---|
| Author | Zhang, Hubiao Wang, Xing Wu, Xiaotian Zhou, Yipeng Chen, You |
| Copyright Year | 2020 |
| Description | Journal: Journal of Physics: Conference Series Difficult obtainment of basic probability assignment (BPA) and inaccurate recognition due to conflicting data are the problems in applying Dempster-Shafer (DS) evidence theory to airborne multi-sensor target recognition. In order to effectively deal with them, an airborne multi-sensor target recognition method based on weighted fuzzy reasoning network (WFRN) and improved Dempster-Shafer (IDS) evidence theory is proposed in this paper. First, the feature vector consisting of 5 feature components is constructed. And then a 4-layer WFRN consisting of 3 kinds of basic units is established to obtain BPA of the feature vector. Finally, conflict data is processed through IDS evidence theory to obtain the final fusion recognition result. The simulation results indicate that the proposed airborne multi-sensor target recognition method is able to obtain BPA reasonably and deal with conflict information. |
| Related Links | https://iopscience.iop.org/article/10.1088/1742-6596/1550/3/032112/pdf |
| ISSN | 17426588 |
| e-ISSN | 17426596 |
| DOI | 10.1088/1742-6596/1550/3/032112 |
| Journal | Journal of Physics: Conference Series |
| Issue Number | 3 |
| Volume Number | 1550 |
| Language | English |
| Publisher | IOP Publishing |
| Publisher Date | 2020-05-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: Journal of Physics: Conference Series Urban and Regional Planning Evidence Theory Multi Sensor Target Sensor Target Recognition |
| Content Type | Text |
| Resource Type | Article |
| Subject | Physics and Astronomy |
