Improved JPDA For Fast Fault Detection
Regarding faults as dynamic modes which observe through the multi-sensors, with probabilistic data association based on multi-sensor, we obtain the fast fault detection results according to the association probability and threshold values. Joint Probabilistic Data Association (JPDA) algorithm is one of the effective ways for single-sensor multi-target tracking. Based on the analysis of JPDA algorithm, we improve the JPDA algorithm: first, we propose an approximation method for constructing the confirmation matrix through removing the small probability events using the right threshold values, and then, we present the mathematical division of the confirmation matrix according to the intersection area of the association gate of fault targets to be tracked; lastly, we compute the association probability of fault targets through attenuating the value of the public measurement. The simulation results show preliminarily that our improved JPDA algorithm saves the computing time greatly, and effectively meet the requirements of fast and real-time fault detection.
GUO Yangming CAI Xiaobin MA Jiezhong
School of Computer Science, Northwestern Polytechnical University, Xi’an 710072, P.R.China School of Computer Science, Northwestern Polytechnical University, Xi’an 710072, P.R.China Science a
国际会议
The 30th Chinese Control Conference(第三十届中国控制会议)
烟台
英文
1-3
2011-07-01（万方平台首次上网日期，不代表论文的发表时间）