信号处理2025，Vol.41Issue(4)：668-682,15.DOI:10.12466/xhcl.2025.04.008
面向未知定向辐射源组合定位的无人机群优化部署
Optimization and Deployment of an Unmanned Aerial Vehicle Swarm for Unknown Directional Radiation Source Combination Positioning
摘要
Abstract
The future trend of unmanned aerial vehicle(UAV)swarm technology involves deploying a large number of low-cost UAVs to accomplish various complex tasks through collaborative sensing,information sharing,and a coordinated divi-sion of labor.These swarms possessed high intelligence and autonomy,and they gradually emerged as the future direction of UAV swarm technology.High-precision positioning technology played a crucial role in the maintenance of swarm stability,avoidance of collisions,and achievement of target guidance.Among these technologies,UAV swarms utilized IoT technol-ogy combined with advanced positioning algorithms to achieve precise positioning and coordination in the air.However,this also led to the emergence of complex joint UAV deployment and resource allocation problems(JUDRA).Hence,this study addressed the problem of optimizing UAV swarm positioning by proposing a more adaptable TDOA+AOA joint positioning framework as well as weak communication constraints between UAV swarms that were more closely aligned with practical ap-plication scenarios.By simplifying the complex UAV swarm resource optimization and deployment problem into a non-convex,non-concave min-max optimization problem with constraints and then decomposing it into master-slave problems,we used an improved Gibbs sampling algorithm for the master problem and a particle filtering algorithm for the slave prob-lem.The proposed method effectively dealt with the complex relationships between multiple variables and achieved optimiza-tion at different levels.To validate the effectiveness and practicality of the proposed method,we experimentally verified its ef-fectiveness in positioning performance under different positioning frameworks and communication constraints between UAVs.Moreover,by considering different numbers of UAV swarms and target uncertainty radii,we further verified the robustness of the algorithm,thereby demonstrating its wide applicability and reliability in practical use.关键词
资源优化/无人机协同定位/天线增益/到达时间差与到达角联合定位方法/非凸非凹min-max优化问题Key words
resource optimization/UAV collaborative positioning/antenna gain/time difference of arrival and angle of arrival joint positioning/non-convex,non-concave min-max optimization problems分类
信息技术与安全科学引用本文复制引用
赵倩倩,熊刚,王李军,尤明懿..面向未知定向辐射源组合定位的无人机群优化部署[J].信号处理,2025,41(4):668-682,15.基金项目
国家自然科学基金重点项目(U20B2038,62231010,U21B2001) （U20B2038,62231010,U21B2001）
国家自然科学基金面上项目(61971278)The State Key Program of National Natural Science Foundation of China(U20B2038,62231010,U21B2001) （61971278）
The National Natural Science Foundation of China(61971278) （61971278）
