Target localization based on bistatic T/R pair selection in GNSS-based multistatic radar system

Research output: Contribution to journalArticlepeer-review

Standard

Target localization based on bistatic T/R pair selection in GNSS-based multistatic radar system. / Shao, Yu'e; Ma, Hui; Zhou, Shenghua; Wang, Xue; Antoniou, Michail; Liu, Hongwei.

In: Remote Sensing, Vol. 13, No. 4, 707, 15.02.2021.

Research output: Contribution to journalArticlepeer-review

Harvard

APA

Vancouver

Author

Bibtex

@article{fd301c94498945dea1ef90ad83f53dc5,
title = "Target localization based on bistatic T/R pair selection in GNSS-based multistatic radar system",
abstract = "To cope with the increasingly complex electromagnetic environment, multistatic radar systems, especially the passive multistatic radar, are becoming a trend of future radar development due to their advantages in anti-electronic jam, anti-destruction properties, and no electromagnetic pollution. However, one problem with this multi-source network is that it brings a huge amount of information and leads to considerable computational load. Aiming at the problem, this paper introduces the idea of selecting external illuminators in the multistatic passive radar system. Its essence is to optimize the configuration of multistatic T/R pairs. Based on this, this paper respectively pro-poses two multi-source optimization algorithms from the perspective of resolution unit and resolution capability, the Covariance Matrix Fusion Method and Convex Hull Optimization Method, and then uses a Global Navigation Satellite System (GNSS) as an external illuminator to verify the algo-rithms. The experimental results show that the two optimization methods significantly improve the accuracy of multistatic positioning, and obtain a more reasonable use of system resources. To eval-uate the algorithm performance under large number of transmitting/receiving stations, further simulation was conducted, in which a combination of the two algorithms were applied and the combined algorithm has shown its effectiveness in minimize the computational load and retain the target localization precision at the same time.",
keywords = "Convex Hull Optimization Method, Covariance Matrix Fusion Method, Multistatic radar, T/R pair selection, Target localization",
author = "Yu'e Shao and Hui Ma and Shenghua Zhou and Xue Wang and Michail Antoniou and Hongwei Liu",
note = "Funding Information: This research was funded by the National Science Fund for Distinguished Young Scholars (No. 61525105), the Fund for Foreign Scholars in University Research and Teaching Programs (the 111 Project No. B18039), the program for Cheung Kong Scholars, the Postdoctoral Innovation Talent Support Program, the National Natural Science Foundation of China(No. 61901344), the National Defense Foundation of China, the foundation of Science and Technology on Electronic Information Control Laboratory, Chinese Postdoctoral Science Funding and the National Natural Science Foundation of Shaanxi Province (No. 2019JQ-289). (Corresponding author_ Hui Ma.) Special thanks to Prof. Jun Wang for his guidance on this paper. Publisher Copyright: {\textcopyright} 2021 by the authors. Licensee MDPI, Basel, Switzerland.",
year = "2021",
month = feb,
day = "15",
doi = "10.3390/rs13040707",
language = "English",
volume = "13",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "MDPI",
number = "4",

}

RIS

TY - JOUR

T1 - Target localization based on bistatic T/R pair selection in GNSS-based multistatic radar system

AU - Shao, Yu'e

AU - Ma, Hui

AU - Zhou, Shenghua

AU - Wang, Xue

AU - Antoniou, Michail

AU - Liu, Hongwei

N1 - Funding Information: This research was funded by the National Science Fund for Distinguished Young Scholars (No. 61525105), the Fund for Foreign Scholars in University Research and Teaching Programs (the 111 Project No. B18039), the program for Cheung Kong Scholars, the Postdoctoral Innovation Talent Support Program, the National Natural Science Foundation of China(No. 61901344), the National Defense Foundation of China, the foundation of Science and Technology on Electronic Information Control Laboratory, Chinese Postdoctoral Science Funding and the National Natural Science Foundation of Shaanxi Province (No. 2019JQ-289). (Corresponding author_ Hui Ma.) Special thanks to Prof. Jun Wang for his guidance on this paper. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2021/2/15

Y1 - 2021/2/15

N2 - To cope with the increasingly complex electromagnetic environment, multistatic radar systems, especially the passive multistatic radar, are becoming a trend of future radar development due to their advantages in anti-electronic jam, anti-destruction properties, and no electromagnetic pollution. However, one problem with this multi-source network is that it brings a huge amount of information and leads to considerable computational load. Aiming at the problem, this paper introduces the idea of selecting external illuminators in the multistatic passive radar system. Its essence is to optimize the configuration of multistatic T/R pairs. Based on this, this paper respectively pro-poses two multi-source optimization algorithms from the perspective of resolution unit and resolution capability, the Covariance Matrix Fusion Method and Convex Hull Optimization Method, and then uses a Global Navigation Satellite System (GNSS) as an external illuminator to verify the algo-rithms. The experimental results show that the two optimization methods significantly improve the accuracy of multistatic positioning, and obtain a more reasonable use of system resources. To eval-uate the algorithm performance under large number of transmitting/receiving stations, further simulation was conducted, in which a combination of the two algorithms were applied and the combined algorithm has shown its effectiveness in minimize the computational load and retain the target localization precision at the same time.

AB - To cope with the increasingly complex electromagnetic environment, multistatic radar systems, especially the passive multistatic radar, are becoming a trend of future radar development due to their advantages in anti-electronic jam, anti-destruction properties, and no electromagnetic pollution. However, one problem with this multi-source network is that it brings a huge amount of information and leads to considerable computational load. Aiming at the problem, this paper introduces the idea of selecting external illuminators in the multistatic passive radar system. Its essence is to optimize the configuration of multistatic T/R pairs. Based on this, this paper respectively pro-poses two multi-source optimization algorithms from the perspective of resolution unit and resolution capability, the Covariance Matrix Fusion Method and Convex Hull Optimization Method, and then uses a Global Navigation Satellite System (GNSS) as an external illuminator to verify the algo-rithms. The experimental results show that the two optimization methods significantly improve the accuracy of multistatic positioning, and obtain a more reasonable use of system resources. To eval-uate the algorithm performance under large number of transmitting/receiving stations, further simulation was conducted, in which a combination of the two algorithms were applied and the combined algorithm has shown its effectiveness in minimize the computational load and retain the target localization precision at the same time.

KW - Convex Hull Optimization Method

KW - Covariance Matrix Fusion Method

KW - Multistatic radar

KW - T/R pair selection

KW - Target localization

UR - http://www.scopus.com/inward/record.url?scp=85101227259&partnerID=8YFLogxK

U2 - 10.3390/rs13040707

DO - 10.3390/rs13040707

M3 - Article

AN - SCOPUS:85101227259

VL - 13

JO - Remote Sensing

JF - Remote Sensing

SN - 2072-4292

IS - 4

M1 - 707

ER -