z-logo
open-access-imgOpen Access
Multisensor decentralized nonlinear fusion using adaptive cubature information filter
Author(s) -
Binglei Guan,
Xianfeng Tang
Publication year - 2020
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0241517
Subject(s) - computer science , filter (signal processing) , fusion center , sensor fusion , fading , algorithm , nonlinear system , noise (video) , control theory (sociology) , artificial intelligence , telecommunications , cognitive radio , decoding methods , physics , image (mathematics) , control (management) , quantum mechanics , wireless , computer vision
In nonlinear multisensor system, abrupt state changes and unknown variance of measurement noise are very common, which challenges the majority of the previously developed models for precisely known multisensor fusion techniques. In terms of this issue, an adaptive cubature information filter (CIF) is proposed by embedding strong tracking filter (STF) and variational Bayesian (VB) method, and it is extended to multi-sensor fusion under the decentralized fusion framework with feedback. Specifically, the new algorithms use an equivalent description of STF, which avoid the problem of solving Jacobian matrix during determining strong trace fading factor and solve the interdependent problem of combination of STF and VB. Meanwhile, A simple and efficient method for evaluating global fading factor is developed by introducing a parameter variable named fading vector. The analysis shows that compared with the traditional information filter, this filter can effectively reduce the data transmission from the local sensor to the fusion center and decrease the computational burden of the fusion center. Therefore, it can quickly return to the normal error range and has higher estimation accuracy in response to abrupt state changes. Finally, the performance of the developed algorithms is evaluated through a target tracking problem.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here