@inproceedings{dc2186c257384905a7650d14515f8e8d,
title = "Conjugate unscented transform based joint probability data association",
abstract = "The conventional Joint Probabilistic Data Association (JPDA) filtering approach is extended using quadrature based methods to achieve better accuracy and stability. Recently developed conjugate unscented transformation is used in conjunction with the probabilistic data association approach to estimate the association probabilities, while carrying out the state estimation filters for the target candidates of interest. Numerical examples are used to evaluate the utility of the proposed algorithms with Extended Kalman Filter (EKF) based approaches for target association.",
author = "Nagavenkat Adurthi and Manoranjan Majji and Mishra, {Utkarsh Ranjan} and Puneet Singla",
note = "Funding Information: This material is based upon the work supported by the AFOSR grant FA9550-15-1-0313. Publisher Copyright: {\textcopyright} 2018 Univelt Inc. All rights reserved.; AAS/AIAA Astrodynamics Specialist Conference, 2017 ; Conference date: 20-08-2017 Through 24-08-2017",
year = "2018",
language = "English (US)",
isbn = "9780877036456",
series = "Advances in the Astronautical Sciences",
publisher = "Univelt Inc.",
pages = "537--552",
editor = "Seago, {John H.} and Strange, {Nathan J.} and Scheeres, {Daniel J.} and Parker, {Jeffrey S.}",
booktitle = "ASTRODYNAMICS 2017",
address = "United States",
}