Update Algorithm on One-Step-Lag Out-of-Sequence Measurement with Correlated Noise Based on Particle Filter

DOI

10.2991/icamcs-16.2016.162How to use a DOI?

Keywords

OOSM, nonlinear, correlated noise, forward prediction, particle filter

Abstract

In the target tracking system, sensor measurements may arrive at the fusion center out of sequence because of the different communication delays, which results in the Out-of-Sequence Measurement(OOSM) problem. In order to solve one-step-lag OOSM problem with corrected process noise and measurement noise in nonlinear system, a new algorithm has been proposed. By combing the framework of the forward prediction filtering, wipe off the correlation, and use Particle filtering to estimate the state. Simulations verify the effectiveness of the proposed algorithm.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Kai Zhao
AU  - Jianwang Hu
AU  - Bing Ji
PY  - 2016/06
DA  - 2016/06
TI  - Update Algorithm on One-Step-Lag Out-of-Sequence Measurement with Correlated Noise Based on Particle Filter
BT  - Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science
PB  - Atlantis Press
SP  - 791
EP  - 795
SN  - 2352-5401
UR  - https://doi.org/10.2991/icamcs-16.2016.162
DO  - 10.2991/icamcs-16.2016.162
ID  - Zhao2016/06
ER  -