Distributed Recursive Filtering Over Sensor Networks With Nonlogarithmic Sensor Resolution

Tracking performance of incremental LMS algorithm over adaptive distributed sensor networks

in this paper we focus on the tracking performance of incremental adaptive LMS algorithm in an adaptive network. For this reason we consider the unknown weight vector to be a time varying sequence. First we analyze the performance of network in tracking a time varying weight vector and then we explain the estimation of Rayleigh fading channel through a random walk model. Closed form relations a...

Distributed Kalman Filtering and Sensor Fusion in Sensor Networks

The problem of distributed Kalman filtering (DKF) for sensor networks is one of the most fundamental distributed estimation problems for scalable sensor fusion. This paper addresses the DKF problem by reducing it to two separate dynamic consensus problems in terms of weighted measurements and inverse-covariance matrices. These to data fusion problems are solved is a distributed way using lowpas...

Distributed Kalman Filtering in Sensor Networks with Quantifiable Performance

We analyze the performance of a distributed Kalman filter proposed in recent work on distributed dynamical systems. This approach to distributed estimation is novel in that it admits a systematic analysis of its performance as various network quantities such as connection density, topology, and bandwidth are varied. Our main contribution is a frequency-domain characterization of the distributed...

Distributed linear estimation over sensor networks

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Fault Detection Over Wireless Sensor Networks using Distributed Kalman and Distributed Particle Filtering