Distributed estimation has been an active research area since the late 1970's, starting with
decentralized filtering and estimation for control of large scale systems. Early research …

We study the problem of distributed Kalman filtering for sensor networks in the presence of
model uncertainty. More precisely, we assume that the actual state-space model belongs to …

The performance of a partial diffusion Kalman filtering (PDKF) algorithm for the networks
with noisy links is studied here. A closed-form expression for the steady-state mean square …

With the explosion of smart devices and the gradual maturation of mobile systems, mobile
crowdsensing (MCS) is playing more and more important roles in our daily life. In traditional …

We propose a distributed Kalman filter for a sensor network under model uncertainty. The
distributed scheme is characterized by two communication stages in each time step: in the …

This paper provides the parallel distributed Kalman filter (PDKF) with non-aligned time
indexes, which uses four processing nodes to run the linear Kalman filter in parallel. To …

Wireless sensor networks are applied in a broad range of applications such as medical,
industrial and military fields. Therefore, a precise Kalman filter mechanism is needed for …

As a distributed system, most applications in wireless sensor networks (WSNs) require clock
synchronization as support. However, clock crystal oscillators in WSNs are highly …

The Distributed Diffusion Kalman Filter (DDKF) algorithm in all its magnitude has earned
great attention lately and has shown an elaborate way to address the issue of distributed …

The integration of multiple wireless communication systems based on 5G is an important
development trend for achieving comprehensive coverage of communication networks in …