Distributed fusion filter for networked multi-sensor systems with multiple random transmission delays and packet dropouts

Abstract

This paper is concerned with the distributed fusion filtering problem for networked multi-sensor systems with multiple random transmission delays (RTDs) and packet dropouts (PDs). Based on the new model and local filters (LFs) proposed in a recent literature, the distributed fusion filter weighted by scalars (DFFWS) is given in the linear minimum variance (LMV) sense. The cross-covariance matrices (CCMs) between any two local filtering errors are derived to compute the fusion weights (FWs). The measured data of each sensor are transmitted to the local processor (LP) over different communication channels with different RTD and PD rates. At each moment, the LP may receive one or multiple data packets or nothing. LFs at individual LPs are transmitted to the fusion center to obtain a fusion filter. A simulation example shows the effectiveness.