Further results on cooperative localization via semidefinite programming

Ning Wang; Liuqing Yang

doi:10.1109/CISS.2011.5766221

Further results on cooperative localization via semidefinite programming

Ning Wang, Liuqing Yang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Scopus citations

Abstract

As a powerful tool to convert nonconvex problems into convex ones, semidefinite programing (SDP) has been introduced to both cooperative and non-cooperative localization systems. In this paper, we derive the Cramér-Rao Lower Bound (CRLB) for several scenarios to show the advantage of cooperative localization. We then consider cooperative localization via SDP using various semidefinite relaxations, including existing Standard SDP (SSDP), Edge-based SDP (ESDP), Node-based SDP (NSDP) and our proposed Component-wise SDP (CSDP). We analyze their performances and complexity and find that CSDP has advantages in both aspects. Simulations will also be carried out to corroborate our analyses.

Original language	English (US)
Title of host publication	2011 45th Annual Conference on Information Sciences and Systems, CISS 2011
DOIs	https://doi.org/10.1109/CISS.2011.5766221
State	Published - 2011
Externally published	Yes
Event	2011 45th Annual Conference on Information Sciences and Systems, CISS 2011 - Baltimore, MD, United States Duration: Mar 23 2011 → Mar 25 2011

Publication series

Name	2011 45th Annual Conference on Information Sciences and Systems, CISS 2011

Other

Other	2011 45th Annual Conference on Information Sciences and Systems, CISS 2011
Country/Territory	United States
City	Baltimore, MD
Period	3/23/11 → 3/25/11

Keywords

Cooperative Localization
Semidefinite Programming (SDP)

Publisher link

10.1109/CISS.2011.5766221

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Wang, N & Yang, L 2011, Further results on cooperative localization via semidefinite programming. in 2011 45th Annual Conference on Information Sciences and Systems, CISS 2011., 5766221, 2011 45th Annual Conference on Information Sciences and Systems, CISS 2011, 2011 45th Annual Conference on Information Sciences and Systems, CISS 2011, Baltimore, MD, United States, 3/23/11. https://doi.org/10.1109/CISS.2011.5766221

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title = "Further results on cooperative localization via semidefinite programming",

abstract = "As a powerful tool to convert nonconvex problems into convex ones, semidefinite programing (SDP) has been introduced to both cooperative and non-cooperative localization systems. In this paper, we derive the Cram{\'e}r-Rao Lower Bound (CRLB) for several scenarios to show the advantage of cooperative localization. We then consider cooperative localization via SDP using various semidefinite relaxations, including existing Standard SDP (SSDP), Edge-based SDP (ESDP), Node-based SDP (NSDP) and our proposed Component-wise SDP (CSDP). We analyze their performances and complexity and find that CSDP has advantages in both aspects. Simulations will also be carried out to corroborate our analyses.",

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author = "Ning Wang and Liuqing Yang",

year = "2011",

doi = "10.1109/CISS.2011.5766221",

language = "English (US)",

isbn = "9781424498475",

series = "2011 45th Annual Conference on Information Sciences and Systems, CISS 2011",

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T1 - Further results on cooperative localization via semidefinite programming

AU - Wang, Ning

AU - Yang, Liuqing

PY - 2011

Y1 - 2011

N2 - As a powerful tool to convert nonconvex problems into convex ones, semidefinite programing (SDP) has been introduced to both cooperative and non-cooperative localization systems. In this paper, we derive the Cramér-Rao Lower Bound (CRLB) for several scenarios to show the advantage of cooperative localization. We then consider cooperative localization via SDP using various semidefinite relaxations, including existing Standard SDP (SSDP), Edge-based SDP (ESDP), Node-based SDP (NSDP) and our proposed Component-wise SDP (CSDP). We analyze their performances and complexity and find that CSDP has advantages in both aspects. Simulations will also be carried out to corroborate our analyses.

AB - As a powerful tool to convert nonconvex problems into convex ones, semidefinite programing (SDP) has been introduced to both cooperative and non-cooperative localization systems. In this paper, we derive the Cramér-Rao Lower Bound (CRLB) for several scenarios to show the advantage of cooperative localization. We then consider cooperative localization via SDP using various semidefinite relaxations, including existing Standard SDP (SSDP), Edge-based SDP (ESDP), Node-based SDP (NSDP) and our proposed Component-wise SDP (CSDP). We analyze their performances and complexity and find that CSDP has advantages in both aspects. Simulations will also be carried out to corroborate our analyses.

KW - Cooperative Localization

KW - Semidefinite Programming (SDP)

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U2 - 10.1109/CISS.2011.5766221

DO - 10.1109/CISS.2011.5766221

M3 - Conference contribution

AN - SCOPUS:79957871086

SN - 9781424498475

T3 - 2011 45th Annual Conference on Information Sciences and Systems, CISS 2011

BT - 2011 45th Annual Conference on Information Sciences and Systems, CISS 2011

T2 - 2011 45th Annual Conference on Information Sciences and Systems, CISS 2011

Y2 - 23 March 2011 through 25 March 2011

ER -

Further results on cooperative localization via semidefinite programming

Abstract

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Keywords

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