We address an estimation problem of nonlinear dynamic system through a large-scale sensor network. Even though much research has been done in data fusion, the extension to nonlinear dynamic system is ...
This paper studies the problem of the designing the robust local and centralized fusion Kalman filters for multisensor system with uncertain noise variances. Using the minimax robust estimation princi...
This paper studies the problem of the designing the robust local and centralized fusion Kalman filters for multisensor system with uncertain noise variances. Using the minimax robust estimation princi...
This paper studies the problem of designing two-level robust sequential covariance intersection SCI fusion Kalman predictors for the clustering sensor networks with noise variances uncertainties. The ...
This paper studies the distributed robust fusion estimation problem with stochastic and deterministic parameter uncertainties, where the covariance of the Gaussian white noise is unknown, and the cova...
This paper proposes a distributed robust Kalman filter for time-varying uncertain linear multisensor systems subjected to stochastic uncertainties. A consensus algorithm is utilized to compromise on a...
This paper is concerned with the problem of two targets tracking over sensor networks. A heterogeneous sensor network framework in considered, in which two types of sensors are employed (denoted as x-...
This paper is concerned with the problem of reliable filter synthesis for a class of stochastic systems with random occurring nonlinearities and mode-dependent delays under nonhomogeneous Markovian sw...
This paper is concerned with the problem of designing H"~ filters for a class of nonlinear networked control systems (NCSs) with transmission delays and packet losses. This problem is investigated und...
This paper is concerned with the distributed target tracking for a moving target of discrete time-varying nonlinear dynamics over a wireless sensor network. A number of spatially distributed sensors a...
This paper investigates the problem of fusion filtering for a class of networked multisensor fusion systems with multiple uncertainties, including sensor failures, stochastic parameter uncertainties, ...
This paper investigates the optimal filtering and its information form for linear discrete-time systems with single time-delay in the observation signal. By introducing delay-free observation, the opt...
This paper investigates the l2-l∞ filtering problem for a class of discrete-time system subject to network-induced delays. The objective is to design a reduced-order filter, such that the estimation e...
This paper considers the optimal power scheduling for the distributed estimation of a source parameter using quantized samples of noisy sensor observations in a wireless sensor network (WSN). Repetiti...
This paper addresses the design of robust weighted fusion time-varying Kalman smoothers for multisensor time-varying system with uncertain noise variances by the augmented state approach. According to...
This paper addresses the design of robust weighted fusion Kalman filters for multisensor time-varying systems with uncertainties of noise variances. Using the minimax robust estimation principle and t...
This letter investigates the hierarchical fusion estimation for clustered sensor networks. The sensors within the same cluster are connected to a local estimator, and all the local estimators are link...
The robust state estimation problem is on how to design robust filters for estimating an unknown state of uncertain systems. This paper considers this problem for multi-agent systems with multiplicati...
The robust fusion filtering problem is considered for linear time-varying uncertain systems observed by multiple sensors. A performance index function for this problem is defined as an indefinite quad...
The problem of distributed state estimation for time-varying uncertain systems over a sensor network within the robust Kalman filtering framework is studied. It is assumed that the parameters of the u...