Distributed Kalman-Consensus Filtering for Sparse Signal Estimation

Yisha Liu, Haiyang Yu and Jian Wang

Mathematical Problems in Engineering, 2014, vol. 2014, 1-7

Abstract:

A Kalman filtering-based distributed algorithm is proposed to deal with the sparse signal estimation problem. The pseudomeasurement-embedded Kalman filter is rebuilt in the information form, and an improved parameter selection approach is discussed. By introducing the pseudomeasurement technology into Kalman-consensus filter, a distributed estimation algorithm is developed to fuse the measurements from different nodes in the network, such that all filters can reach a consensus on the estimate of sparse signals. Some numerical examples are provided to demonstrate the effectiveness of the proposed approach.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:138146

DOI: 10.1155/2014/138146

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