Conjugate unscented transform based joint probability data association

Nagavenkat Adurthi, Manoranjan Majji, Utkarsh Ranjan Mishra, Puneet Singla

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationASTRODYNAMICS 2017
EditorsJohn H. Seago, Nathan J. Strange, Daniel J. Scheeres, Jeffrey S. Parker
PublisherUnivelt Inc.
Pages537-552
Number of pages16
ISBN (Print)9780877036456
StatePublished - Jan 1 2018
EventAAS/AIAA Astrodynamics Specialist Conference, 2017 - Stevenson, United States
Duration: Aug 20 2017Aug 24 2017

Publication series

NameAdvances in the Astronautical Sciences
Volume162
ISSN (Print)0065-3438

Other

OtherAAS/AIAA Astrodynamics Specialist Conference, 2017
CountryUnited States
CityStevenson
Period8/20/178/24/17

Fingerprint

Extended Kalman filters
State estimation
transform
state estimation
Kalman filters
quadratures
Kalman filter
filters
estimates
filter

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Space and Planetary Science

Cite this

Adurthi, N., Majji, M., Mishra, U. R., & Singla, P. (2018). Conjugate unscented transform based joint probability data association. In J. H. Seago, N. J. Strange, D. J. Scheeres, & J. S. Parker (Eds.), ASTRODYNAMICS 2017 (pp. 537-552). (Advances in the Astronautical Sciences; Vol. 162). Univelt Inc..
Adurthi, Nagavenkat ; Majji, Manoranjan ; Mishra, Utkarsh Ranjan ; Singla, Puneet. / Conjugate unscented transform based joint probability data association. ASTRODYNAMICS 2017. editor / John H. Seago ; Nathan J. Strange ; Daniel J. Scheeres ; Jeffrey S. Parker. Univelt Inc., 2018. pp. 537-552 (Advances in the Astronautical Sciences).
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Adurthi, N, Majji, M, Mishra, UR & Singla, P 2018, Conjugate unscented transform based joint probability data association. in JH Seago, NJ Strange, DJ Scheeres & JS Parker (eds), ASTRODYNAMICS 2017. Advances in the Astronautical Sciences, vol. 162, Univelt Inc., pp. 537-552, AAS/AIAA Astrodynamics Specialist Conference, 2017, Stevenson, United States, 8/20/17.

Conjugate unscented transform based joint probability data association. / Adurthi, Nagavenkat; Majji, Manoranjan; Mishra, Utkarsh Ranjan; Singla, Puneet.

ASTRODYNAMICS 2017. ed. / John H. Seago; Nathan J. Strange; Daniel J. Scheeres; Jeffrey S. Parker. Univelt Inc., 2018. p. 537-552 (Advances in the Astronautical Sciences; Vol. 162).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Adurthi N, Majji M, Mishra UR, Singla P. Conjugate unscented transform based joint probability data association. In Seago JH, Strange NJ, Scheeres DJ, Parker JS, editors, ASTRODYNAMICS 2017. Univelt Inc. 2018. p. 537-552. (Advances in the Astronautical Sciences).