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.
Semidefinite Programming Solutions for Elliptic Localization in Asynchronous Radar Networks
IEEE Transactions on Aerospace and Electronic Systems ; 58 , 4 ; 3385-3398
2022-08-01
1982567 byte
Article (Journal)
Electronic Resource
English
A Novel Semidefinite Programming-based UAV 3D Localization Algorithm with Gray Wolf Optimization
DOAJ | 2023
|Multiclass Image Labeling with Semidefinite Programming
British Library Conference Proceedings | 2006
|