引用本文:罗旭,柴利,杨君.无线传感器网络下移动扩散源追踪算法[J].控制理论与应用,2014,31(2):201~208.[点击复制]
LUO Xu,CHAI Li,Yang Jun.Mobile diffusion source tracking in wireless sensor networks[J].Control Theory and Technology,2014,31(2):201~208.[点击复制]
无线传感器网络下移动扩散源追踪算法
Mobile diffusion source tracking in wireless sensor networks
摘要点击 2188  全文点击 1608  投稿时间：2013-05-09  修订日期：2013-09-21
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DOI编号  10.7641/CTA.2014.30457
  2014,31(2):201-208
中文关键词  离散化浓度模型  无线传感器网络  最小二乘  Sage-Husa卡尔曼滤波  移动扩散源追踪
英文关键词  discrete concentration model  wireless sensor networks  least squares  Sage-Husa Kalman filter  mobile diffusion source tracking
基金项目  国家自然科学基金资助项目(61171160); 湖北省高等学校优秀中青年科技创新团队计划资助项目(T201302).
作者单位E-mail
罗旭 武汉科技大学 冶金自动化与检测技术教育部工程研究中心  
柴利* 武汉科技大学 冶金自动化与检测技术教育部工程研究中心 eechai@gmail.com 
杨君 武汉科技大学 冶金自动化与检测技术教育部工程研究中心  
中文摘要
      与移动瞬时源追踪相比, 移动扩散源追踪相对困难. 本文分析了移动扩散源扩散过程, 给出了离散化浓度 场模型. 将连续线源目标追踪问题转化为离散点源目标追踪的次优问题, 提出了一种离散化移动扩散源追踪算法. 在该算法中, 先采用约束最小二乘方法估计目标实时位置、到达时间等相关参数, 并进一步采用仅针对位置序列的 Sage-Husa卡尔曼滤波方法优化位置估计. 该算法克服了一般基于动态序列的追踪方法无法直接应用于离散移动扩 散源追踪问题的不足. 在仿真实验中, 分别在匀速率平滑曲线运动与变速非平滑曲线运动的情形下进行追踪实验, 分析了追踪精度与采样间隔以及观测节点密度的关系. 仿真结果说明了提出的移动扩散源追踪算法的有效性.
英文摘要
      Generally it is more difficult to track a mobile diffusion source than to track a mobile instantaneous source. The diffusion process of mobile sources is analyzed, and a discrete concentration model is proposed. The problem of tracking a continuous line diffusion source is transformed into a suboptimal problem of tracking a discrete mobile diffusion source, to which the discrete tracking algorithm is proposed. In the algorithm, a constrained least squares method is adopted to estimate the related parameters including positions in real-time and arrival time. Next, the Sage-Husa Kalman filter is used to obtain the optimal estimation of the target positions. The algorithm overcomes the shortcoming that the general tracking methods based on dynamic sequence cannot be directly applied to the discrete tracking problem of the mobile diffusion source. The simulation experiments are carried out in two scenarios, in one of which the target moves along a smooth curve with a constant rate, and in another the target moves along a non-smooth curve with a varying velocity. In the simulations, the relation between the tracking accuracy and the sampling density as well as the node density is investigated. The results illustrate the effectiveness of the proposed mobile diffusion tracking algorithm.