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Improved TOA Localization Using Modified Polar Representation
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AI
DOI：10.1109/LCOMM.2024.3430319.png)
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Abstract
En 中文
Existing communication systems are required to provide highly precise locations of users or terminals to support diverse applications. This study enhances the performance of time of arrival localization by utilizing modified polar representation, regardless of the range of users or terminals. We propose two solutions: 1) the two-stage semidefinite relaxation (2S-SDR), enhancing accuracy by refining the weighting matrix after initial SDR; 2) the maximum likelihood estimator (MLE), using Gauss-Newton iteration to minimize its cost function. Both solutions achieve the Cram & eacute;r-Rao lower bound (CRLB) under moderate noise levels. Particularly, the MLE demonstrates CRLB accuracy and lower bias in the low noise region. Simulation results validate the effectiveness of the proposed solutions.
Keywords:
Location awareness
Noise
Mathematical models
Maximum likelihood estimation
Accuracy
Vectors
Three-dimensional displays
Mobile communication localization (MCL)
time of arrival (TOA)
modified polar representation (MPR)
wireless sensor network (WSN)
semidefinite relaxation (SDR)
Journal
IF:
4.4
Papers:
1.3W
Citations:
2.2W