Cooperative Localization Using Posterior Linearization Belief Propagation
Artikel i vetenskaplig tidskrift, 2018

This paper presents the posterior linearization belief propagation (PLBP) algorithm for cooperative localization in wireless sensor networks with nonlinear measurements. PLBP performs two steps iteratively: linearization and belief propagation. At the linearization step, the nonlinear functions are linearized using statistical linear regression with respect to the current beliefs. This SLR is performed in practice by using sigma-points drawn from the beliefs. In the second step, belief propagation is run on the linearized model. We show by numerical simulations how PLBP can outperform other algorithms in the literature.

posterior linearization

Gaussian message passing

cooperative localization

Belief propagation

sigma points

Författare

Angel Garcia

Aalto-Yliopisto

Lennart Svensson

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Signalbehandling

S. Särkkä

Aalto-Yliopisto

IEEE Transactions on Vehicular Technology

0018-9545 (ISSN)

Vol. 67 1 832-836 7999230

Ämneskategorier

Beräkningsmatematik

Reglerteknik

Signalbehandling

DOI

10.1109/TVT.2017.2734683

Mer information

Senast uppdaterat

2019-03-19