TY - GEN
T1 - Filtering Algorithm of Out-of-Sequence Measurement Based on Sequential Filtering
AU - Wang, Wenlong
AU - Qu, Yaohong
AU - Wang, Kai
AU - Xu, Shengyang
AU - Zhu, Xiaoping
N1 - Publisher Copyright:
© 2021 Technical Committee on Control Theory, Chinese Association of Automation.
PY - 2021/7/26
Y1 - 2021/7/26
N2 - In multi-sensor tracking and fusion system, due to the different pre-processing time and sampling rate of sensors, as well as the inherent random communication delay of the channel, the measurement data of sensor may arrive at the fusion center in an unordered manner. The current out-of-order measurement filtering methods cannot fully meet the engineering requirements in terms of tracking accuracy and computational complexity. This paper proposes a centralized data fusion method based on lag compensation. This method can deal with one-step or even multi-step delay measurement data, and the compensation accuracy can be closed to the fusion accuracy under orderly measurement. At the same time, this method has the ability of selective fusion, which improves the positioning accuracy while relatively reducing the amount of calculation and storage. The simulation results verify the effectiveness of the algorithm.
AB - In multi-sensor tracking and fusion system, due to the different pre-processing time and sampling rate of sensors, as well as the inherent random communication delay of the channel, the measurement data of sensor may arrive at the fusion center in an unordered manner. The current out-of-order measurement filtering methods cannot fully meet the engineering requirements in terms of tracking accuracy and computational complexity. This paper proposes a centralized data fusion method based on lag compensation. This method can deal with one-step or even multi-step delay measurement data, and the compensation accuracy can be closed to the fusion accuracy under orderly measurement. At the same time, this method has the ability of selective fusion, which improves the positioning accuracy while relatively reducing the amount of calculation and storage. The simulation results verify the effectiveness of the algorithm.
KW - Information fusion
KW - Out-of-Sequence Measurement (OOSM)
KW - Sequential filtering
UR - http://www.scopus.com/inward/record.url?scp=85117281023&partnerID=8YFLogxK
U2 - 10.23919/CCC52363.2021.9550397
DO - 10.23919/CCC52363.2021.9550397
M3 - 会议稿件
AN - SCOPUS:85117281023
T3 - Chinese Control Conference, CCC
SP - 3564
EP - 3569
BT - Proceedings of the 40th Chinese Control Conference, CCC 2021
A2 - Peng, Chen
A2 - Sun, Jian
PB - IEEE Computer Society
T2 - 40th Chinese Control Conference, CCC 2021
Y2 - 26 July 2021 through 28 July 2021
ER -