北京航空航天大学学报2026，Vol.52Issue(8)：2729-2737,9.DOI:10.13700/j.bh.1001-5965.2025.0645
多偏斜量测下异构无人机群EM自适应跟踪方法
EM-based adaptive tracking method for heterogeneous UAV swarm with multi-skewed measurements
摘要
Abstract
Because of their complementing roles and cooperative skills,heterogeneous unmanned aerial vehicle(UAV)swarms have become a serious threat to air defense systems.The heterogeneous UVA swarms often exhibit a non-convex shape and multi-skewed measurements,which is attributable to variations in the size and spatial distribution of its internal sub-targets.Most existing group target tracking relies upon the hypothesis of convex target shapes and uniform measurement distributions.However,these assumptions could no longer be valid in the real scenario,which may deteriorate the tracking performance.To address the problem of tracking a UAV swarm with non-convex contours and non-uniformly distributed measurements,an expectation maximization(EM)-based adaptive tracking for a heterogeneous UAV swarm with multi-skewed measurements is proposed.Firstly,a multi-skewed measurements noise model is established,and the number of the heterogeneous subgroup targets and the measurements noise parameters are calculated by using an online EM approach.Following the formulation of a joint probability density function for each heterogeneous subgroup target's kinematic state,shape,and skewed noise parameters,online state and shape estimation is accomplished via a variational inference approach.Finally,the shapes of multiple subgroup targets are fused to acquire the extended shape of the heterogeneous UAV swarm.Simulation results demonstrate that the proposed algorithm significantly outperforms existing approaches,including random matrix model(RMM)-based,random hypersurface model(RHM)-based,multi-ellipsoidal model(MEM)-based,and skew-normal variational Bayes algorithms,in both kinematic state and shape estimation accuracy.关键词
异构无人机群/多偏斜分布/非凸扩展形态/期望最大化算法/变分贝叶斯推理Key words
heterogeneous unmanned aerial vehicle swarm/multi-skewed distribution/non-convex shape/expectation maximization algorithm/variational Bayes inference分类
信息技术与安全科学引用本文复制引用
马天力,李红,石沛灵,陈超波,王可鑫..多偏斜量测下异构无人机群EM自适应跟踪方法[J].北京航空航天大学学报,2026,52(8):2729-2737,9.基金项目
国家自然科学基金(62303368,52572487) （62303368,52572487）
陕西省重点研发计划(2024GX-YBXM-112) （2024GX-YBXM-112）
陕西省教育厅科学研究计划青年创新团队项目(24JP081) National Natural Science Foundation of China(62303368,52572487) （24JP081）
Key Research and Development Project of Shaanxi Province(2024GX-YBXM-112) （2024GX-YBXM-112）
Youth Innovation Team Project of Shaanxi Provincial Department of Education Research Plan(24JP081) （24JP081）
