Distributed Localization of Target for MIMO Radar With Widely Separated Directional Transmitters and Omnidirectional Receivers

Conventional target localization algorithms for the multiple-input multiple-output (MIMO) radar with widely separated antennas are mainly based on the centralized localization framework, which suffer from huge burdens of computation and communication as well as robustness defect in complex environme...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2023-06, Vol.59 (3), p.3171-3187
Main Authors: Xiong, Kui, Cui, Guolong, Yi, Wei, Wang, Shiyuan, Kong, Lingjiang
Format: Article
Language:English
Subjects:
Algorithms
Angle of incidence (AOI)
Antenna measurements
bistatic range (BR)
constrained total least squares (LS)
Cramer-Rao bounds
distributed localization
Incidence angle
Localization
Lower bounds
Mathematical analysis
Matrices (mathematics)
MIMO communication
MIMO radar
multiple-input multiple-output (MIMO) radar
Position measurement
Radar
Receivers
Robustness (mathematics)
Transmitters
Wireless sensor networks
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Summary:Conventional target localization algorithms for the multiple-input multiple-output (MIMO) radar with widely separated antennas are mainly based on the centralized localization framework, which suffer from huge burdens of computation and communication as well as robustness defect in complex environments. To overcome these issues, this article first considers the MIMO radar with widely separated directional transmitters and omnidirectional receivers generating the bistatic range (BR) and angle of incidence (AOI) measurements for target localization, which is proven that the position of the target can be uniquely determined with one transmitter and one receiver. Then, the distributed localization framework using the hybrid BR and AOI measurements is developed, where each receiver acts as a fusion center extracting the BR and AOI measurements to perform the localization process, and the localization problem is formulated as solving a linear matrix equation. The distributed constrained total least squares (DCTLS) algorithm considering errors in both data matrix and observation vector is proposed for each receiver for target localization. The localization performance regarding the Cramér–Rao lower bound is derived for theoretical analysis. Numerical simulations are performed to validate the efficacy and superiority of the proposed DCTLS algorithm over other typical localization algorithms.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2022.3221686