TY - JOUR
T1 - Distributed fusion in wireless sensor networks based on a novel event-triggered strategy
AU - Jiang, Lu
AU - Yan, Liping
AU - Xia, Yuanqing
AU - Guo, Qiao
AU - Fu, Mengyin
AU - Li, Li
N1 - Publisher Copyright:
© 2018 The Franklin Institute
PY - 2019/11
Y1 - 2019/11
N2 - In this paper, the event-triggered distributed multi-sensor data fusion algorithm is presented for wireless sensor networks (WSNs) based on a new event-triggered strategy. The threshold of the event is set according to the chi-square distribution that is constructed by the difference of the measurement of the current time and the measurement of the last sampled moment. When the event-triggered decision variable value is larger than the threshold, the event is triggered and the observation is sampled for state estimation. In designing the dynamic event-triggered strategy, we relate the threshold with the quantity in the chi-square distribution table. Therefore, compared to the existed event-triggered algorithms, this novel event-triggered strategy can give the specific sampling/communication rate directly and intuitively. In addition, for the presented distributed fusion in wireless sensor networks, only the measurements in the neighborhood (i.e., the neighbor nodes and the neighbor's neighbor nodes) of the fusion center are fused so that it can obtain the optimal state estimation under limited energy consumption. A numerical example is used to illustrate the effectiveness of the presented algorithm.
AB - In this paper, the event-triggered distributed multi-sensor data fusion algorithm is presented for wireless sensor networks (WSNs) based on a new event-triggered strategy. The threshold of the event is set according to the chi-square distribution that is constructed by the difference of the measurement of the current time and the measurement of the last sampled moment. When the event-triggered decision variable value is larger than the threshold, the event is triggered and the observation is sampled for state estimation. In designing the dynamic event-triggered strategy, we relate the threshold with the quantity in the chi-square distribution table. Therefore, compared to the existed event-triggered algorithms, this novel event-triggered strategy can give the specific sampling/communication rate directly and intuitively. In addition, for the presented distributed fusion in wireless sensor networks, only the measurements in the neighborhood (i.e., the neighbor nodes and the neighbor's neighbor nodes) of the fusion center are fused so that it can obtain the optimal state estimation under limited energy consumption. A numerical example is used to illustrate the effectiveness of the presented algorithm.
UR - http://www.scopus.com/inward/record.url?scp=85046669942&partnerID=8YFLogxK
U2 - 10.1016/j.jfranklin.2018.04.021
DO - 10.1016/j.jfranklin.2018.04.021
M3 - Article
AN - SCOPUS:85046669942
SN - 0016-0032
VL - 356
SP - 10315
EP - 10334
JO - Journal of the Franklin Institute
JF - Journal of the Franklin Institute
IS - 17
ER -