Delayed and asequent data in decentralized sensing networks

Eric W. Nettleton; Hugh F. Durrant-Whyte

doi:10.1117/12.444148

4 October 2001 Delayed and asequent data in decentralized sensing networks

Eric W. Nettleton, Hugh F. Durrant-Whyte

Proceedings Volume 4571, Sensor Fusion and Decentralized Control in Robotic Systems IV; (2001) https://doi.org/10.1117/12.444148
Event: Intelligent Systems and Advanced Manufacturing, 2001, Boston, MA, United States

Abstract

This paper presents an exact solution to the delayed data problem for the information form of the Kalman filter, together with its application to decentralised sensing networks. To date, the most common method of handling delayed data in sensing networks has been to use a conservative time alignment of the observation data with the filter time. However, by accounting for the correlation between the late data and the filter over the delayed period, an exact solution is possible. The inclusion of this information correlation term adds little extra complexity, and may be applied in an information filter update stage which is associative. The delayed data algorithm can also be used to handle data that is asequent or out of order. The asequent data problem is presented in a simple recursive information filter form. The information filter equations presented in this paper are applied in a decentralised picture compilation problem. This involves multiple aircraft tracking multiple ground targets and the construction of a single common tactical picture.

Citation Download Citation

Eric W. Nettleton and Hugh F. Durrant-Whyte "Delayed and asequent data in decentralized sensing networks", Proc. SPIE 4571, Sensor Fusion and Decentralized Control in Robotic Systems IV, (4 October 2001); https://doi.org/10.1117/12.444148

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available