Maximum likelihood identification of glint noise
| dc.citation.epage | 51 | en_US |
| dc.citation.issue | 1 | en_US |
| dc.citation.spage | 41 | en_US |
| dc.citation.volume | 32 | en_US |
| dc.citation.woscount | 9 | |
| dc.contributor.author | Wu, WR | en_US |
| dc.contributor.department | 交大名義發表 | zh_TW |
| dc.contributor.department | 電信工程研究所 | zh_TW |
| dc.contributor.department | National Chiao Tung University | en_US |
| dc.contributor.department | Institute of Communications Engineering | en_US |
| dc.date.accessioned | 2014-12-08T15:02:56Z | |
| dc.date.available | 2014-12-08T15:02:56Z | |
| dc.date.issued | 1996-01-01 | en_US |
| dc.description.abstract | If the non-Gaussian distribution function of radar glint noise is known, the Masreliez filter can be applied to improve target tracking performance. We investigate the glint identification problem using the maximum likelihood (ML) method. Two models for the glint distribution are used, a mixture of two Gaussian distributions and a mixture of a Gaussian and a Laplacian distribution An efficient initial estimate method based on the QQ-plot is also proposed. Simulations show that the ML estimates converge to truths. | en_US |
| dc.identifier.doi | 10.1109/7.481248 | en_US |
| dc.identifier.issn | 0018-9251 | en_US |
| dc.identifier.journal | IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS | en_US |
| dc.identifier.uri | http://dx.doi.org/10.1109/7.481248 | en_US |
| dc.identifier.uri | https://ir.lib.nycu.edu.tw/handle/11536/1535 | |
| dc.identifier.wosnumber | WOS:A1996TQ35200005 | |
| dc.language.iso | en_US | en_US |
| dc.title | Maximum likelihood identification of glint noise | en_US |
| dc.type | Article | en_US |