Multistatic Target Localization Exploiting Multiple Transmitters With Imperfect Time Synchronization

This correspondence investigates the multistatic target localization problem, accounting for time offsets of transmitters and sensor position uncertainties. A maximum likelihood estimation (MLE) problem involving the target position, sensor positions and time offsets is formulated by directly using the original measurements. To solve the non-convex MLE problem, an efficient two-step semidefinite relaxation (SDR) method is proposed. Specifically, the SDR technique is employed to solve the MLE problem and then the solution is further refined by estimating the error term. Furthermore, it is analytically demonstrated that the proposed method can achieve the Cram´er-Rao lower bound (CRLB) under low-noise conditions. Simulation results validate the theoretical development and show that the performance of the proposed method outperforms existing algorithms

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Publication Details

Journal
IEEE Transactions on Aerospace and Electronic Systems
Published
2025-09-03
DOI
https://doi.org/10.1109/taes.2025.3605903
Citations
1
Primary Topic
Sparse and Compressive Sensing Techniques
Type
article
Field-Weighted Citation Impact
1.33
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article

Multistatic Target Localization Exploiting Multiple Transmitters With Imperfect Time Synchronization

Yanbin Zou, Minyi You, Guodong Qin, Liehu Wu et al.
1 citations
IEEE Transactions on Aerospace and Electronic Systems
Sparse and Compressive Sensing Techniques
1.33
article

Multistatic Target Localization Exploiting Multiple Transmitters With Imperfect Time Synchronization

Yanbin Zou, Minyi You, Guodong Qin, Liehu Wu, Duofang Chen
article en
1 citations

Abstract

This correspondence investigates the multistatic target localization problem, accounting for time offsets of transmitters and sensor position uncertainties. A maximum likelihood estimation (MLE) problem involving the target position, sensor positions and time offsets is formulated by directly using the original measurements. To solve the non-convex MLE problem, an efficient two-step semidefinite relaxation (SDR) method is proposed. Specifically, the SDR technique is employed to solve the MLE problem and then the solution is further refined by estimating the error term. Furthermore, it is analytically demonstrated that the proposed method can achieve the Cram´er-Rao lower bound (CRLB) under low-noise conditions. Simulation results validate the theoretical development and show that the performance of the proposed method outperforms existing algorithms

IEEE Transactions on Aerospace and Electronic SystemsVol. 61(6)
Xidian University (CN), Shantou University (CN), National Engineering Research Center of Electromagnetic Radiation Control Materials (CN)
Openalex Percentile: Top 19%
Sparse and Compressive Sensing Techniques
1.33
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