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