5 papers · 1 filter
Discover Fast Power Allocation Solution for Multi-Target Tracking via AlphaEvolve Evolution
Zhenkang Hou, Wenqiang Pu, Junkun Yan +2
Efficient radar resource allocation is a fundamental yet computationally challenging problem, as optimal solutions typically require iterative optimization with high complexity. Mo…
Learning an Opponent-aware Anti-jamming Strategy via Online Convex Optimization
Liangqi Liu, Wenqiang Pu, Yingru Li +1
The dynamic competition against intelligent jammer systems presents a significant challenge to modern radar. Traditional active anti-jamming strategy learning methods often suffer…
Radar Anti-jamming Strategy Learning via Domain-knowledge Enhanced Online Convex Optimization
Liangqi Liu, Wenqiang Pu, Yingru Li +2
The dynamic competition between radar and jammer systems presents a significant challenge for modern Electronic Warfare (EW), as current active learning approaches still lack sampl…
Counterfactual Regret Minimization for Anti-jamming Game of Frequency Agile Radar
Huayue Li, Zhaowei Han, Wenqiang Pu +3
The competition between radar and jammer is one emerging issue in modern electronic warfare, which in principle can be viewed as a non-cooperative game with two players. In this wo…
Learning to Continuously Optimize Wireless Resource In Episodically Dynamic Environment
Haoran Sun, Wenqiang Pu, Minghe Zhu +3
There has been a growing interest in developing data-driven and in particular deep neural network (DNN) based methods for modern communication tasks. For a few popular tasks such a…