引用本文:陆科林,周锐,张翔伦.多无人机航迹融合算法及性能评估[J].控制理论与应用,2015,32(10):1392~1399.[点击复制]
LU Ke-lin,ZHOU Rui,Zhang Xiang-lun.Exact algorithms for track-to-track fusion by multiple UAVs and performance evaluation[J].Control Theory and Technology,2015,32(10):1392~1399.[点击复制]
多无人机航迹融合算法及性能评估
Exact algorithms for track-to-track fusion by multiple UAVs and performance evaluation
摘要点击 3028  全文点击 1902  投稿时间:2015-04-30  修订日期:2015-07-19
查看全文  查看/发表评论  下载PDF阅读器
DOI编号  10.7641/CTA.2015.50353
  2015,32(10):1392-1399
中文关键词  航迹融合  无人机  卡尔曼滤波器  目标跟踪  估计
英文关键词  track-to-track fusion  unmanned aerial vehicles  Kalman filters  target tracking  estimation
基金项目  国家自然科学基金(61273349, 61175109, 61203223);航空科学基金(2013ZA18001, 2014ZA18004)
作者单位E-mail
陆科林* 北京航空航天大学 klu@buaa.edu.cn 
周锐 北京航空航天大学  
张翔伦 西安自动飞行控制研究所  
中文摘要
      航迹融合是多无人机系统进行协同侦察, 巡逻和目标跟踪领域中的一个重要问题. 本文根据不同信息反馈配置 给出了局部航迹之间的协方差的精确计算, 并据此提出一种精确、具有可扩展性并且适用于任意通信频率的航迹融合 算法. 此外, 本文通过求解对应的离散代数Riccati方程求取融合估计的稳态误差协方差, 并以此进行融合性能分析. 最 后, 本文利用Monte Carlo仿真比较理论和实际结果, 实验结果验证了该融合算法的有效性.
英文摘要
      Track-to-track fusion is an important topic for cooperative surveillance, reconnaissance and target tracking by multiple unmanned aerial vehicles (UAVs). In this paper, the accurate cross-covariances between the local estimates are obtained from various information feedback configurations, which gives rise to the scalable and consistent algorithms for track-to-track fusion (T2TF) at an arbitrary communication rate. Furthermore, the steady-state error covariance of the fused estimate is obtained by solving the corresponding discrete algebraic Riccati equation for performance analysis. In addition, the theoretical results are compared with those from the extensive Monte Carlo simulation, which validates the effectiveness of the proposed fusion algorithms.