Recursive Fusion Algorithm with Correlated Noises and One-Step Out-of-Sequence Measurements
Chenglin Wen · Chuangan jishu xuebao · 2009
Because of the special communication modes of sensor networks and the different data of pre-processing time of each sensor node,the ordered measurements from the same target often arrive in the fusion center out of sequence across sensor networks,named as out-of-sequence measurement(OOSM) problem.And most of fusion algorithms are presented for the independent noises assumption.This paper researches the OOSMs Sensor networks composed of multiple subsystems and each of them has two sensors where one has the sampling rate and sampling time,and another is asynchronous with the fusion center.For the case with correlated sensor and system noises,a recursive distributed weighted OOSMs fusion algorithm,which can real-timely estimate target state variables and is optimal in minimizing the trace of the error covariance matrix,is developed.The theory analysis and computer simulation both show the advantages of the proposed algorithm such as in the cases of application range,real-time processing capability,storage capability and fusion estimate accuracy and so on.