Efficient Radar-Target Assignment in Low Probability of Intercept Radar Networks: A Machine-Learning Approach
Hamid Amiriara,
Seyed Mehdi Hosseini Andargoli,
Vahid Meghdadi
Abstract: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)-based approach over all possible sensor combinations has exponential complexity, making it challenging to implement in networks with a large number of radars or targets. This limits the implementation of the BF app… Show more
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