Kalman filter

Ahmed Abdelgawad, Magdy Bayoumi

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations


This chapter has briefly discussed the need of the DKF and introduced the literature work of the DKF. Most DKF methods proposed in the literature rely on consensus filters algorithm. The convergence rate of such distributed consensus algorithms typically depends on the network topology and the weights given to the edges between neighboring sensors. The next chapter proposes a low power DKF. The proposed DKF is based on a fast polynomial filter to accelerate distributed average consensus in static network topologies. The idea is to apply a polynomial filter on the network matrix that will shape its spectrum in order to increase the convergence rate by minimizing its second largest eigenvalue. Fast convergence can contribute to significant energy saving.

Original languageEnglish
Title of host publicationResource-Aware Data Fusion Algorithms for Wireless Sensor Networks
PublisherSpringer Verlag
Number of pages18
ISBN (Print)9781461413493
StatePublished - 2012

Publication series

NameLecture Notes in Electrical Engineering
Volume118 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119


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