Unified optimal linear estimation fusion. II. Discussions and examples

X. Rong Li; Jie Wang

doi:10.1109/IFIC.2000.862452

Unified optimal linear estimation fusion. II. Discussions and examples

X. Rong Li
, Jie Wang

University of New Orleans
Xi'an Jiaotong University

科研成果: 会议稿件 › 论文 › 同行评审

23 引用（Scopus）

摘要

Several unified optimal estimation/track fusion rules in the sense of best linear unbiased estimation (BLUE) and weighted least squares (WLS) have been presented in pt.I for centralized, distributed, and hybrid fusion architectures. This paper discusses their pros and cons, verifies these rules, and demonstrate via simulation examples how these fusion rules can be used in cases with either complete, incomplete, or no prior information about the estimate (i.e., the quantity to be estimated).

源语言	英语
页	MoC218-MoC225
DOI	https://doi.org/10.1109/IFIC.2000.862452
出版状态	已出版 - 2000
已对外发布	是
活动	3rd International Conference on Information Fusion, FUSION 2000 - Paris, 法国期限: 10 7月 2000 → 13 7月 2000

会议

会议	3rd International Conference on Information Fusion, FUSION 2000
国家/地区	法国
市	Paris
时期	10/07/00 → 13/07/00

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10.1109/IFIC.2000.862452

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链接到 Scopus 的出版物

引用此

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title = "Unified optimal linear estimation fusion. II. Discussions and examples",

abstract = "Several unified optimal estimation/track fusion rules in the sense of best linear unbiased estimation (BLUE) and weighted least squares (WLS) have been presented in pt.I for centralized, distributed, and hybrid fusion architectures. This paper discusses their pros and cons, verifies these rules, and demonstrate via simulation examples how these fusion rules can be used in cases with either complete, incomplete, or no prior information about the estimate (i.e., the quantity to be estimated).",

keywords = "BLUE, Estimation fusion, MMSE estimation, fusion rules, least squares, track fusion",

author = "Li, \{X. Rong\} and Jie Wang",

year = "2000",

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language = "英语",

pages = "MoC218--MoC225",

note = "3rd International Conference on Information Fusion, FUSION 2000 ; Conference date: 10-07-2000 Through 13-07-2000",

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AU - Li, X. Rong

AU - Wang, Jie

PY - 2000

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N2 - Several unified optimal estimation/track fusion rules in the sense of best linear unbiased estimation (BLUE) and weighted least squares (WLS) have been presented in pt.I for centralized, distributed, and hybrid fusion architectures. This paper discusses their pros and cons, verifies these rules, and demonstrate via simulation examples how these fusion rules can be used in cases with either complete, incomplete, or no prior information about the estimate (i.e., the quantity to be estimated).

AB - Several unified optimal estimation/track fusion rules in the sense of best linear unbiased estimation (BLUE) and weighted least squares (WLS) have been presented in pt.I for centralized, distributed, and hybrid fusion architectures. This paper discusses their pros and cons, verifies these rules, and demonstrate via simulation examples how these fusion rules can be used in cases with either complete, incomplete, or no prior information about the estimate (i.e., the quantity to be estimated).

KW - BLUE

KW - Estimation fusion

KW - MMSE estimation

KW - fusion rules

KW - least squares

KW - track fusion

UR - https://www.scopus.com/pages/publications/84901451703

U2 - 10.1109/IFIC.2000.862452

DO - 10.1109/IFIC.2000.862452

M3 - 论文

AN - SCOPUS:84901451703

SP - MoC218-MoC225

T2 - 3rd International Conference on Information Fusion, FUSION 2000

Y2 - 10 July 2000 through 13 July 2000

ER -

Unified optimal linear estimation fusion. II. Discussions and examples

摘要

会议

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