信息工程大学学报2026，Vol.27Issue(3)：291-296,303,7.DOI:10.3969/j.issn.1671-0673.2026.03.006
基于REINFORCE算法的组网测向选站方法
A Station Selection Method for Networked Direction-Finding Based on the REINFORCE Algorithm
摘要
Abstract
To address the issue of the poor timeliness and difficulty of real-time tracking in traditional networked direction-finding methods when handling fast-moving targets with short signal burst dura-tions,a station selection method based on the REINFORCE algorithm is proposed.A Markov decision process(MDP)framework is employed to decompose the station combination process into a multi-step sequential decision process.By selecting stations one by one,the combinatorial optimization problem is transformed into a sequential decision problem.The positional relationship between stations and the target is used as the state space,the number of stations in the combination constrains the agent's learn-ing steps,action masking is applied to the selected stations,and the geometrical dilution of precision(GDOP)serves as the reward function to evaluate the quality of station selection schemes.Experimen-tal results demonstrate that the proposed method significantly outperforms both the exhaustive method and the genetic algorithm in terms of time complexity,while achieving comparable localization accu-racy to the exhaustive method.Furthermore,it exhibits strong generalization ability by learning the mapping between station spatial configuration and GDOP,enabling effective network deployment deci-sions for unseen target scenarios.关键词
组网测向/序贯决策/强化学习/动作屏蔽/几何精度因子Key words
networked direction-finding/sequential decision/reinforcement learning/action masking/geometric dilution of precision分类
信息技术与安全科学引用本文复制引用
朱晨晨,张静..基于REINFORCE算法的组网测向选站方法[J].信息工程大学学报,2026,27(3):291-296,303,7.
