Name
Title | ||
|---|---|---|
Event-Triggered Sequential Fusion Filters Based On Estimators Of Observation Noises For Multi-Sensor Systems With Correlated Noises |
Abstract | ||
|---|---|---|
This paper studies event-triggered sequential fusion filtering problems for multi-sensor systems where observation noises are mutually correlated at the same moment and correlated with the process noise at the previous moment. To save energy consumption of sensors, an event-triggered mechanism is employed to reduce communication rates from a sensor to the fusion center. Event-triggered estimators of observation noises under the linear minimum variance criterion are derived for the first time. Based on estimators of observation noises, an event-triggered optimal sequential fusion filter under the linear minimum variance criterion is presented by taking the information of the event-triggered condition into account which brings some integral calculations. To reduce computational burden, an event-triggered suboptimal sequential fusion filter is also presented by ignoring the information of the event-triggered condition. Boundedness of variance of the proposed suboptimal sequential fusion filter is analyzed. Two simulation examples verify the effectiveness of our algorithms. (C) 2020 Elsevier Inc. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.dsp.2020.102960 | DIGITAL SIGNAL PROCESSING |
Keywords | DocType | Volume |
Event-triggered mechanism, Sequential fusion filter, Correlated noise, Estimator of observation noise, Multi-sensor system | Journal | 111 |
ISSN | Citations | PageRank |
1051-2004 | 0 | 0.34 |
References | Authors | |
0 | 2 | |