An Index Policy Based on Sarsa and Q-learning for Heterogeneous Smart Target Tracking

arXiv:2402.12015v1 Announce Type: cross
Abstract: In solving the non-myopic radar scheduling for multiple smart target tracking within an active and passive radar network, we need to consider both short-term enhanced tracking performance and a higher probability of target maneuvering in the future with active tracking. Acquiring the long-term tracking performance while scheduling the beam resources of active and passive radars poses a challenge. To address this challenge, we model this problem as a Markov decision process consisting of parallel restless …

abstract arxiv cs.lg cs.sy eess.sy future index multiple network performance policy probability q-learning radar scheduling smart tracking type