Discover the power of cognitive radar with adaptive waveform selection. Explore a stochastic dynamic programming model and Q-learning to optimize wave-form ...
Adaptive waveform selection is an important problem in cognitive radar, with the aim of selecting the optimal waveform and tracking targets with more accuracy ...
The problem of adaptive waveform selection is modeled as stochastic dynamic programming model, then Q-learning is used to solve it and it is demonstrated ...
In this paper, the problem of adaptive waveform selection is modeled as stochastic dynamic programming model. Then Q-learning is used to solve it. Q-learning ...
This paper combines deep Q-learning networks in deep reinforcement learning with a posteriori estimation of the target state and proposes a cognitive radar ...
In this paper, the running process of cognitive radar adaptive transmission is analyzed, the tracking waveform parameter selection is correlated with the target ...
Missing: Q- | Show results with:Q-
Oct 14, 2024 · In this work, we focus on proposing adaptive algorithms that select waveform parameters in an online fashion.
The performance of temporal difference learning is better than Q-learning, but Q-learning is more suitable to use in radar scene. Finally, the whole paper ...
Oct 14, 2024 · We propose three reinforcement learning algorithms: bandwidth scaling, Q-learning, and Q-learning lookahead. These algorithms dynamically choose ...
Jun 10, 2024 · We compare our energy-efficient Q-Learning (EEQ) algorithm with traditional Power Allocation Q-Learning (PAQ) algorithm. The EEQ outperforms the ...