Fusion filtering for rectangular descriptor systems with stochastic bias and random observation delays under weighted try-once-discard protocol

This paper studies the fusion filtering problem for a class of multi-sensor rectangular descriptor systems with stochastic bias and random observation delays under weighted try-once-discard (WTOD) protocol. In order to reflect the stochastic behavior generated by disturbances, a dynamic equation is utilized to describe the stochastic bias. The random observation delays are modeled by Bernoulli random variables with individual occurrence probability. Furthermore, the WTOD protocol is used to lessen the network traffic burden. Firstly, by introducing matrix transformation and the singular value decomposition method, the rectangular descriptor systems are transformed into two non-descriptor subsystems with lower orders, where the augmentation technique is adopted to obtain new augmented systems. Secondly, the relevant local filter gains are obtained by minimizing the filtering error covariances based on the local filters (LFs) designed by new systems. Subsequently, the local filters and the fusion filters of the original descriptor systems are obtained by state transformation and covariance intersection (CI) fusion technique, respectively. The major contribution lies in that a novel fusion filtering algorithm avoiding the calculation of error cross-covariances is proposed for rectangular descriptor systems, where special effort is devoted to handling the impacts from the WTOD protocol, stochastic bias and random observation delays. Finally, the effectiveness of the fusion algorithm is demonstrated by a simulation example.