Data fusion of infrared and radar for target tracking

Author

Zhu, Anfu ; Jing, Zhanrong ; Chen, Weijun ; Wang, Liguang ; LI, Yunfei ; CAO, Zhenlin

Author_Institution

Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´´an

fYear

2008

fDate

10-12 Dec. 2008

Firstpage

1

Lastpage

4

Abstract

A target tracking method based on data fusion of infrared and radar is proposed to improve tracking precision. Unscented Kalman filter (UKF) is applied to process data on distributed fusion architectures. The method combines the advantages of UKF and track-to-track algorithms. The cross-covariances of the two sensors are used to estimate overall covariance and states. The overall estimation is obtained by the track-to-track fusion algorithm for the optimal combination of two correlated estimates. The proposed method is applied to simulating target tracking of infrared and radar. The simulation results show the proposed method has advantages in higher precision, and probability of detection is increased.

Keywords

Kalman filters; millimetre waves; radar; sensor fusion; target tracking; cross-covariances; data fusion; infrared radar; mill-meter wave radar; target tracking; track-to-track algorithms; unscented Kalman filter; Doppler radar; Inference algorithms; Nonlinear filters; Radar tracking; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Signal processing algorithms; State estimation; Target tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems and Control in Aerospace and Astronautics, 2008. ISSCAA 2008. 2nd International Symposium on

Conference_Location

Shenzhen

Print_ISBN

978-1-4244-3908-9

Electronic_ISBN

978-1-4244-2386-6

Type

conf

DOI

10.1109/ISSCAA.2008.4776312

Filename

4776312