Cross-product algorithms for source tracking using an EM vector sensor

Author

Nehorai, Arye ; Tichavsky, Petr

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., Illinois Univ., Chicago, IL, USA

Volume

5

fYear

1999

fDate

1999

Firstpage

2781

Abstract

We present two adaptive cross-product algorithms for tracking the direction to a moving source using an electromagnetic vector sensor. The first is a cross-product algorithm with a forgetting factor, for which we analyze the performance and derive an asymptotic expression of the variance of angular estimation error. We find the optimal forgetting factor that minimizes this variance. The second is a Kalman filter combined with the cross-product algorithm, which is applicable when the angular acceleration of the source is approximately constant

Keywords

Kalman filters; adaptive signal processing; direction-of-arrival estimation; electromagnetic fields; target tracking; EM vector sensor; Kalman filter; adaptive cross-product algorithms; angular acceleration; angular estimation error; asymptotic expression; cross-product algorithm; electromagnetic vector sensor; forgetting factor; moving source; performance; source tracking; Acceleration; Algorithm design and analysis; Analysis of variance; Computational complexity; Costs; Electromagnetic measurements; Estimation error; Magnetic field measurement; Wideband; Yield estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on

Conference_Location

Phoenix, AZ

ISSN

1520-6149

Print_ISBN

0-7803-5041-3

Type

conf

DOI

10.1109/ICASSP.1999.761323

Filename

761323