Volume 5, Issue 3 (Journal of Control, V.5, N.3 Fall 2011)
JoC 2011, 5(3): 24-35 |
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Moaveni B, Rouhi S. Comparison the State Vector Fusion Methods for Data Fusion in Multi Sensors Networks. JoC 2011; 5 (3) :24-35
URL: http://joc.kntu.ac.ir/article-1-80-en.html
URL: http://joc.kntu.ac.ir/article-1-80-en.html
Abstract: (9536 Views)
In this paper, we compare the performance of state vector fusion methods for data fusion of multi sensors networks by comparing the estimation errors covariance. Here, we represent the three main state vector data fusion methods and we prove the equivalency of the estimation error covariance matrices corresponding to these three methods. In last part of the paper, the simulation results are presented to show the effectiveness of the theoretical results. Also, we analyze the computational load of these three methods by simulation analysis.
Keywords: Multi-Sensor Data Fusion, State Vector Fusion, Kalman Filter, Estimation Error Covariance.
Type of Article: Research paper |
Subject:
Special
Received: 2014/06/15 | Accepted: 2014/06/15 | Published: 2014/06/15
Received: 2014/06/15 | Accepted: 2014/06/15 | Published: 2014/06/15
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