DocumentCode :
2345019
Title :
A high estimate accuracy fusion method for multisensor tracking association
Author :
Liu Yuan-Kui ; Fan Yang-yu ; Zhao Jiong ; Huang Ai-ping
Author_Institution :
Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´an, China
fYear :
2009
fDate :
25-27 May 2009
Firstpage :
3876
Lastpage :
3880
Abstract :
A high estimate accuracy fusion method for multisensor tracking association is presented. Based on the analysis of the state fusion and measurement fusion methods, the estimating effects of the two methods are compared. Considering the measurement covariance´s influence on the fusion result, we assign the elements of the measurement covariance matrix to the measurements from different sensors as their weights, and combine the weighted measurements to form the new measurement which is used in the Kalman filter. The simulation shows the new method´s estimate accuracy is much higher than the state and measurement fusion methods.
Keywords :
Kalman filters; covariance matrices; sensor fusion; tracking filters; Kalman filter; covariance matrix; high estimate accuracy fusion method; measurement fusion method; multisensor tracking association; Area measurement; Biomedical engineering; Covariance matrix; Estimation error; Filters; Remote monitoring; Sensor fusion; State estimation; Target tracking; Weight measurement; kalman filter multisensor; track fusion; weighted measurement fusion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-2799-4
Electronic_ISBN :
978-1-4244-2800-7
Type :
conf
DOI :
10.1109/ICIEA.2009.5138933
Filename :
5138933
Link To Document :
بازگشت