Optimal update with out-of-sequence measurements for distributed filtering

Keshu Zhang; X. Rong Li; Yunmin Zhu

doi:10.1109/ICIF.2002.1020997

Optimal update with out-of-sequence measurements for distributed filtering

Keshu Zhang
, X. Rong Li
, Yunmin Zhu

Research output: Contribution to conference › Paper › peer-review

46 Scopus citations

Abstract

This paper is concerned with optimal filtering in a distributed multiple sensor system with the so-called out-of-sequence measurements (OOSM). Based on BLUE (best linear unbiased estimation) fusion, we present two algorithms for updating with OOSM that are optimal for the information available at the time of update. Different minimum storage of information concerning the occurrence time of OOSMs are given for both algorithms. It is shown by analysis and simulation results that the two proposed algorithms are flexible and simple.

Original language	English
Pages	1519-1526
Number of pages	8
DOIs	https://doi.org/10.1109/ICIF.2002.1020997
State	Published - 2002
Externally published	Yes
Event	5th International Conference on Information Fusion, FUSION 2002 - Annapolis, MD, United States Duration: 8 Jul 2002 → 11 Jul 2002

Conference

Conference	5th International Conference on Information Fusion, FUSION 2002
Country/Territory	United States
City	Annapolis, MD
Period	8/07/02 → 11/07/02

Keywords

BLUE
Kalman filter
Out of sequence measurement
Target tracking

Access to Document

10.1109/ICIF.2002.1020997

Cite this

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abstract = "This paper is concerned with optimal filtering in a distributed multiple sensor system with the so-called out-of-sequence measurements (OOSM). Based on BLUE (best linear unbiased estimation) fusion, we present two algorithms for updating with OOSM that are optimal for the information available at the time of update. Different minimum storage of information concerning the occurrence time of OOSMs are given for both algorithms. It is shown by analysis and simulation results that the two proposed algorithms are flexible and simple.",

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AU - Zhang, Keshu

AU - Li, X. Rong

AU - Zhu, Yunmin

PY - 2002

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N2 - This paper is concerned with optimal filtering in a distributed multiple sensor system with the so-called out-of-sequence measurements (OOSM). Based on BLUE (best linear unbiased estimation) fusion, we present two algorithms for updating with OOSM that are optimal for the information available at the time of update. Different minimum storage of information concerning the occurrence time of OOSMs are given for both algorithms. It is shown by analysis and simulation results that the two proposed algorithms are flexible and simple.

AB - This paper is concerned with optimal filtering in a distributed multiple sensor system with the so-called out-of-sequence measurements (OOSM). Based on BLUE (best linear unbiased estimation) fusion, we present two algorithms for updating with OOSM that are optimal for the information available at the time of update. Different minimum storage of information concerning the occurrence time of OOSMs are given for both algorithms. It is shown by analysis and simulation results that the two proposed algorithms are flexible and simple.

KW - BLUE

KW - Kalman filter

KW - Out of sequence measurement

KW - Target tracking

UR - https://www.scopus.com/pages/publications/84901404869

U2 - 10.1109/ICIF.2002.1020997

DO - 10.1109/ICIF.2002.1020997

M3 - 论文

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T2 - 5th International Conference on Information Fusion, FUSION 2002

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ER -

Optimal update with out-of-sequence measurements for distributed filtering

Abstract

Conference

Keywords

Access to Document

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