Data fusion for target tracking in wireless sensor networks using quantized innovations and Kalman filtering  

作　　者：XU Jian LI JianXun XU Sheng 

机构地区：[1]Department of Automation,Science and Technology on Avionics Integration Laboratory,Shanghai Jiao Tong University,Shanghai 200240,China [2]Department of Automation,System Control and Information Processing,Ministry of Education of China,Shanghai Jiao Tong University,Shanghai 200240,China [3]School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China

出　　处：《Science China(Information Sciences)》2012年第3期530-544,共15页中国科学（信息科学）（英文版）

基　　金：supported by National Natural Science Foundation of China (Grant Nos. 61175008, 60935001,60874104);National Basic Research Program of China (Grant Nos. 2009CB824900, 2010CB734103);Space Foundation of Supporting-Technology (Grant No. 2011-HT-SHJD002);Aeronautical Science Foundation of China(Grant No. 20105557007)

摘　　要：A novel networked data-fusion method is developed for the target tracking in wireless sensor networks （WSNs）. Specifically, this paper investigates data fusion scheme under the communication constraint between the fusion center and each sensor. Such a message constraint is motivated by the bandwidth limitation of the communication links, fusion center, and by the limited power budget of local sensors. In the proposed scheme, each sensor collects one noise-corrupted sample, performs a quantizing operation, and transmits quantized message to the fusion center. Then the fusion center combines the received quantized messages to produce a final estimate. The novel data-fusion method is based on the quantized measurement innovations and decentralized Kalman filtering （DKF） with feedback. For the proposed algorithm, the performance analysis of the estimation precision is provided. Finally, Monte Carlo simulations show the effectiveness of the proposed scheme.A novel networked data-fusion method is developed for the target tracking in wireless sensor networks （WSNs）. Specifically, this paper investigates data fusion scheme under the communication constraint between the fusion center and each sensor. Such a message constraint is motivated by the bandwidth limitation of the communication links, fusion center, and by the limited power budget of local sensors. In the proposed scheme, each sensor collects one noise-corrupted sample, performs a quantizing operation, and transmits quantized message to the fusion center. Then the fusion center combines the received quantized messages to produce a final estimate. The novel data-fusion method is based on the quantized measurement innovations and decentralized Kalman filtering （DKF） with feedback. For the proposed algorithm, the performance analysis of the estimation precision is provided. Finally, Monte Carlo simulations show the effectiveness of the proposed scheme.

关 键 词：data fusion target tracking limited bandwidth quantized innovation Kalman filtering 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置] TU473.11[自动化与计算机技术—控制科学与工程]