Real-time observability of targets with constrained processing power

Author

Olivier, Christian

Author_Institution

9 rue Francois Villon, Paris, France

Volume

41

Issue

5

fYear

1996

fDate

5/1/1996 12:00:00 AM

Firstpage

689

Lastpage

701

Abstract

This paper discusses an issue in the implementation of Kalman filter tracking systems. The issue is the relationship between processing time in generating measurement data, the search area needed for such measurements, and the errors in the measurement data produced. A key observation is that in certain cases (particularly when the underlying model used in the Kalman filter is not asymptotically stable) processing time may be a very real issue. The analysis of several cases shows that a variable precision measurement computation strategy may be of benefit. One of the motivating examples is a tracking system using image-type data. The study is performed for a first-order system and shows the difficulties encountered with multidimensional systems

Keywords

Kalman filters; computer vision; multidimensional systems; observability; optimisation; real-time systems; stochastic systems; target tracking; tracking; Kalman filter; computer vision; constrained processing; first-order system; multidimensional systems; processing time; real-time systems; resolution optimisation; stochastic systems; target observability; target tracking; Area measurement; Charge measurement; Current measurement; Motion measurement; Observability; Performance evaluation; Power measurement; Sampling methods; Target tracking; Time measurement;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/9.489205

Filename

489205