Maximum likelihood registration for multiple dissimilar sensors

Author

Okello, Nickens ; Ristic, Branko

Author_Institution

Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia

Volume

39

Issue

3

fYear

2003

fDate

7/1/2003 12:00:00 AM

Firstpage

1074

Lastpage

1083

Abstract

A study of the maximum likelihood registration (MLR) algorithm for spatial alignment of multiple, possibly dissimilar (active or passive) sensors is presented. The MLR algorithm is a batch algorithm which outputs estimates of the registration parameters, registered sensor measurements and registered target location estimates, expressed in a common coordinate system. The Cramer-Rao type bound for registration of multiple dissimilar sensors is discussed and some numerical examples for sensor registration are presented in support of the theory.

Keywords

maximum likelihood estimation; random noise; sensor fusion; Cramer-Rao type bound; MLR; batch algorithm; common coordinate system; maximum likelihood registration; multiple dissimilar sensors; registered sensor measurements; registration parameters; spatial alignment; Azimuth; Error correction; Maximum likelihood estimation; Noise measurement; Position measurement; Sensor fusion; Sensor phenomena and characterization; Sensor systems; State estimation; Surveillance;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/TAES.2003.1238759

Filename

1238759