Efficient Radar-Target Assignment in Low Probability of Intercept Radar Networks: A Machine-Learning Approach

Efficient Radar-Target Assignment in Low Probability of Intercept Radar Networks: A Machine-Learning Approach

To achieve low probability of intercept (LPI) in radar networks for multiple target detection, it is necessary to find the optimal assignment of distributed radars to targets. The multi-radar to multi-target assignment (MRMTA) problem aims to find the best radar combination, but its brute-force (BF)...

Full description

Bibliographic Details
Main Authors: Hamid Amiriara, Seyed Mehdi Hosseini Andargoli, Vahid Meghdadi
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Open Journal of the Communications Society
Subjects:
Multi-radar to multi-target assignment (MRMTA)
supervised machine-learning (ML)
low probability intercept radars
feed-forward neural network (FNN)
radar network
information fusion
Online Access:https://ieeexplore.ieee.org/document/10242370/

Internet

https://ieeexplore.ieee.org/document/10242370/

Similar Items