The Research on Asynchronous Data Fusion Algorithm Based on Sampling of Rational Number Times
GE Quan-bo, Guoan Wang · Dianzi xuebao · 2006
This paper explores data fusion of distributed multisensor dynamic systems,these sensors hold different sampling rates.For the proportion between them is usually rational;a new fusion algorithm based on asynchronous sampling data is proposed.Firstly,the new algorithm maps and unifies all measurements in the reference frame and clock with fusion centre.Secondly,using the difference between predict value to object state of next time and state estimate value of this time,we establish the dynamic model between object state vector of every sampling point in the fusion period.Thirdly,combining the new established model with traditional Kalman filter,every state in this period can be estimated and updated by obtaining orderly measures.Finally,the next state estimate or predicted estimate may be got by global information after all state estimates relative to all observation point in this period have been obtained in turn.With introducing the basic idea of the new algorithm,the processes to win it are presented step by step.Using of computer simulation in terms of comparing the results utilizing the new algorithm with those based on time calibrated method via estimate accuracy,the good performance arising from this new approach has been effectively validated.