半定规划
放松(心理学)
凸优化
克拉姆-饶行
上下界
数学优化
计算机科学
传输(电信)
算法
噪音(视频)
正多边形
到达时间
职位(财务)
缩小
最优化问题
数学
估计理论
电信
人工智能
数学分析
无线
心理学
社会心理学
几何学
财务
经济
图像(数学)
作者
Xiao Ma,Benjian Hao,Hailin Zhang,Pengwu Wan
出处
期刊:IEEE Signal Processing Letters
[Institute of Electrical and Electronics Engineers]
日期:2022-01-01
卷期号:29: 622-626
被引量:7
标识
DOI:10.1109/lsp.2022.3151006
摘要
This letter addresses the time-of-arrival based localization problem when the source and sensors are not synchronized, whereby an unknown transmission time is introduced. A non-convex weighted least squares (WLS) minimization problem is first formulated to jointly estimate the source position and the unknown transmission time by transforming the measurement model, and then semidefinite relaxation is applied to relax the WLS problem as a convex semidefinite program (SDP). The relaxed SDP problem is always tight and thus the optimal solution of the WLS problem can always be obtained. The proposed method is then extended to the moving source localization scenario, where the source velocity is assumed to be a constant for a sufficiently small observation period. Simulation results show that the proposed method is able to reach the Cramer-Rao lower bound accuracy when the noise is not very large.
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