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.
Bibliographical noteFunding 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.
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
- Convex Hull Optimization Method
- Covariance Matrix Fusion Method
- Multistatic radar
- T/R pair selection
- Target localization
ASJC Scopus subject areas
- Earth and Planetary Sciences(all)