›› 2015, Vol. 24 ›› Issue (2): 20702-020702.doi: 10.1088/1674-1056/24/2/020702

• GENERAL • 上一篇    下一篇

Estimation of spatially distributed processes using mobile sensor networks with missing measurements

江正仙a b c, 崔宝同a b   

  1. a Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, China;
    b School of IoT Engineering, Jiangnan University, Wuxi 214122, China;
    c School of Science, Jiangnan University, Wuxi 214122, China
  • 收稿日期:2014-03-27 修回日期:2014-09-01 出版日期:2015-02-05 发布日期:2015-02-05
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 61174021, 61473136, and 61104155) and the 111 Project (Grant No. B12018).

Estimation of spatially distributed processes using mobile sensor networks with missing measurements

Jiang Zheng-Xian (江正仙)a b c, Cui Bao-Tong (崔宝同)a b   

  1. a Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, China;
    b School of IoT Engineering, Jiangnan University, Wuxi 214122, China;
    c School of Science, Jiangnan University, Wuxi 214122, China
  • Received:2014-03-27 Revised:2014-09-01 Online:2015-02-05 Published:2015-02-05
  • Contact: Jiang Zheng-Xian E-mail:zhengxian@jiangnan.edu.cn
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 61174021, 61473136, and 61104155) and the 111 Project (Grant No. B12018).

摘要: This paper investigates the estimation problem for a spatially distributed process described by a partial differential equation with missing measurements. The randomly missing measurements are introduced in order to better reflect the reality in the sensor network. To improve the estimation performance for the spatially distributed process, a network of sensors which are allowed to move within the spatial domain is used. We aim to design an estimator which is used to approximate the distributed process and the mobile trajectories for sensors such that, for all possible missing measurements, the estimation error system is globally asymptotically stable in the mean square sense. By constructing Lyapunov functionals and using inequality analysis, the guidance scheme of every sensor and the convergence of the estimation error system are obtained. Finally, a numerical example is given to verify the effectiveness of the proposed estimator utilizing the proposed guidance scheme for sensors.

关键词: estimation, spatially distributed process, mobile sensor network, missing measurements

Abstract: This paper investigates the estimation problem for a spatially distributed process described by a partial differential equation with missing measurements. The randomly missing measurements are introduced in order to better reflect the reality in the sensor network. To improve the estimation performance for the spatially distributed process, a network of sensors which are allowed to move within the spatial domain is used. We aim to design an estimator which is used to approximate the distributed process and the mobile trajectories for sensors such that, for all possible missing measurements, the estimation error system is globally asymptotically stable in the mean square sense. By constructing Lyapunov functionals and using inequality analysis, the guidance scheme of every sensor and the convergence of the estimation error system are obtained. Finally, a numerical example is given to verify the effectiveness of the proposed estimator utilizing the proposed guidance scheme for sensors.

Key words: estimation, spatially distributed process, mobile sensor network, missing measurements

中图分类号:  (Sensors (chemical, optical, electrical, movement, gas, etc.); remote sensing)

  • 07.07.Df
02.30.Jr (Partial differential equations) 84.40.Ua (Telecommunications: signal transmission and processing; communication satellites)