Semidefinite Programming Solutions for Elliptic Localization in Asynchronous Radar Networks

In this article, semidefinite programming (SDP) solutions are proposed for the elliptic localization problem in asynchronous radar networks, where the transmitters are subject to clock offsets. Relaxing the nonconvex problem into different convex forms, we design tight SDP (TSDP) and global SDP (GSD...

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Published in:IEEE transactions on aerospace and electronic systems Vol. 58; no. 4; pp. 3385 - 3398
Main Authors: Wu, Xiaoping, Shen, Yana, Zhu, Xuefen, Lin, Qinman
Format: Journal Article
Language:English
Published: New York IEEE 01.08.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Asynchronous radar network
clock offset
Clocks
Correlation
Cramer-Rao bounds
elliptic localization
Localization
Location awareness
Lower bounds
MIMO radar
Performance enhancement
Programming
Radar
Radar networks
Receivers
Semidefinite programming
semidefinite programming (SDP)
Transmitters
ISSN:0018-9251, 1557-9603
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Abstract In this article, semidefinite programming (SDP) solutions are proposed for the elliptic localization problem in asynchronous radar networks, where the transmitters are subject to clock offsets. Relaxing the nonconvex problem into different convex forms, we design tight SDP (TSDP) and global SDP (GSDP) solutions for this problem. The TSDP solution includes several SDP cones to solve the problem, and the correlation is not considered. Hence, the TSDP solution performs poorly in the presence of correlated noise. We further put forward the GSDP solution to improve the performance by introducing a new GSDP form, which includes only one SDP cone to handle the correlated noise. We also theoretically prove that the GSDP problem is tight enough so that its performance is able to sufficiently approach the Cramér–Rao lower bound (CRLB) accuracy. The simulated results show that the TSDP solution can provide the comparable performance with the GSDP in the absence of related noise. The performance of the GSDP solution can almost attain the CRLB accuracy using less receivers.
AbstractList In this article, semidefinite programming (SDP) solutions are proposed for the elliptic localization problem in asynchronous radar networks, where the transmitters are subject to clock offsets. Relaxing the nonconvex problem into different convex forms, we design tight SDP (TSDP) and global SDP (GSDP) solutions for this problem. The TSDP solution includes several SDP cones to solve the problem, and the correlation is not considered. Hence, the TSDP solution performs poorly in the presence of correlated noise. We further put forward the GSDP solution to improve the performance by introducing a new GSDP form, which includes only one SDP cone to handle the correlated noise. We also theoretically prove that the GSDP problem is tight enough so that its performance is able to sufficiently approach the Cramér–Rao lower bound (CRLB) accuracy. The simulated results show that the TSDP solution can provide the comparable performance with the GSDP in the absence of related noise. The performance of the GSDP solution can almost attain the CRLB accuracy using less receivers.
Author Lin, Qinman
Zhu, Xuefen
Wu, Xiaoping
Shen, Yana
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SubjectTerms Asynchronous radar network
clock offset
Clocks
Correlation
Cramer-Rao bounds
elliptic localization
Localization
Location awareness
Lower bounds
MIMO radar
Performance enhancement
Programming
Radar
Radar networks
Receivers
Semidefinite programming
semidefinite programming (SDP)
Transmitters
Title Semidefinite Programming Solutions for Elliptic Localization in Asynchronous Radar Networks
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Volume 58
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