Kalman filter based multiple sensor data fusion in systems with time delayed state

2016 ◽  
Author(s):  
N Shivashankarappa ◽  
Sudarshan Adiga ◽  
R A Avinash ◽  
H R Janardhan
Keyword(s):  
Kalman Filter ◽  
Data Fusion ◽  
Sensor Data ◽  
Sensor Data Fusion ◽  
Multiple Sensor

Weighted Multi-Sensor Data Fusion Based on Fuzzy Kalman Filter for Seam Tracking of the Welding Robots

2012 ◽  
Vol 542-543 ◽  
pp. 800-805 ◽  
Author(s):  
Jun Du ◽  
Mei Sun ◽  
Liang Hua ◽  
Jia Sheng Ge ◽  
Ju Ping Gu
Keyword(s):  
Kalman Filter ◽  
Data Fusion ◽  
Maximum Modulus ◽  
Seam Tracking ◽  
Measurement Noise ◽  
Sensor Data ◽  
Inference System ◽  
Sensor Data Fusion ◽  
Noise Characteristics ◽  
Multi Sensor Data Fusion

In order to resolve the problem of seam tracking of the welding robots with unknown noise characteristics, a Weighted Multi-Sensor Data Fusion (MSDF) algorithm based on the fuzzy Kalman filter algorithm is proposed. Firstly, each Fuzzy Kalman Filter (FKF) uses a fuzzy inference system based on a covariance matching technique to adjust the weight coefficient of measurement noise covariance matrix, so it makes measurement noise close to the true noise level. Secondly, a membership function in fuzzy set is used to measure the mutual support degree matrix of each FKF and corresponding weight coefficients are allocated by this matrix’s maximum modulus eigenvectors, hence, the final expression of data fusion is obtained. Finally, simulation results show that MSDF in seam tracking has both high precision and strong ability of stableness.

scholarly journals PERSON AUTHENTICATION USING MULTIPLE SENSOR DATA FUSION

2011 ◽  
Vol 01 (04) ◽  
pp. 189-196 ◽  
Author(s):  
Vasuhi S. ◽  
◽  
Vaidehi V. ◽  
Naresh Babu N.T. ◽  
◽  
...  
Keyword(s):  
Data Fusion ◽  
Sensor Data ◽  
Sensor Data Fusion ◽  
Multiple Sensor
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