Distributed Fusion Estimation For Multi-Sensor Networked Systems With Asynchronous Sampling And Network-Induced Features

In recent years,multi-sensor information fusion estimation has attracted more and more attention and has application in a broad range of areas such as mobile robots,smart power grids and so on.Distributed fusion estimation based on wireless sensor networks(WSNs)has become a research hotspot at home and abroad.For example,practical problems such as WSNs-based mobile robot tracking,multi-sensor three-tank liquid level estimation and greenhouse temperature control estimation are based on distributed estimation or fusion estimation theory.However,in the fusion estimation framework,data will be affected by network-induced characteristics such as delay and packet loss and malicious network attacks during date transmission process,these factors may lead to the degradation of the estimation performance,and also make the analysis and design of the fusion estimation system face many challenges.Therefore,how to reduce the influence of network uncertainty factors induced in the process of multi-sensor information transmission on state estimation is one of the difficulties in distributed estimation research based on WSNs.The key to information fusion is to design a highly robust and reliable distributed filtering algorithm.but there is less research work on these issues.Considering multi-sensor multi-rate asynchronous sampling mechanism,network induced characteristics such as delay and packet loss during transmission and cyber-attack,this paper studies WSN-based distributed fusion estimation.The main work and innovative achievements are as follows(1)This paper reviews the research status and challenges of distributed multi-sensor fusion estimation at home and abroad.(2)The distributed fusion estimation problem of wireless sensor network system with model uncertainty,network-induced delay and data packet loss is studied,and a distributed fusion estimator based on robust Kalman filter is designed.In view of the time-delay induced by multi-channel network in the process of data transmission of different sensors,the time-delay system is transformed into a delay-free system by using the compensation mechanism,and multiple Bernoulli sequences are used to model the data packet loss phenomenon of different channels.Based on the successfully arrived sampling data,a set of networked estimators based on robust Kalman filtering algorithm is designed to obtain local estimators,and the covariance interaction fusion method is used to reduce the burden of communication and calculation,so as to obtain a fusion estimator with higher accuracy than local estimation.(3)This paper further studies the hierarchical clustering fusion estimation problem for a class of networked systems with multi-sensor and multi-rate sampling.Considering the characteristics of spatial distribution and energy limitation of sensor nodes,a twolayer asynchronous distributed estimation strategy based on intra-cluster local estimation and inter-cluster fusion estimation is proposed.Considering packet loss and cyber-attack of wireless sensor network,a networked strong tracking filter based on multi-rate sampling data of nodes in the cluster is designed in the cluster-head node to obtain the local estimation of the system,the time-varying fading factor can compensate the modeling errors caused by asynchronous sampling and unknown system interference.Furthermore,a multirate fusion estimation method with time-varying fusion time is proposed by using local state estimation or predicted state estimation signals of several neighbor cluster head nodes.The proposed method takes full account of multi-rate sampling,multi-rate data transmission and distributed structure of hierarchical clustering,and is suitable for asynchronous multisensor distributed estimation system.In this paper,the distributed fusion estimation problem of networks-induced characteristics such as delay,packet loss and cyber-attack during the transmission process with multi-sensor and multi-rate asynchronous sampling is studied.Two kinds of filtering fusion methods are designed to respectively carry out numerical simulation on moving target tracking and three-tank ITTS.The simulation results verify the feasibility of the proposed distributed fusion estimation method.