메뉴 건너뛰기




Volumn , Issue , 2009, Pages 810-817

Unifying Bayesian networks and IMM filtering for improved multiple model estimation

Author keywords

Bayesian network; IMM; Meta model filter; Multiple model estimation

Indexed keywords

FILTER BANDWIDTH; HOLISTIC APPROACH; IMM; INTERACTING MULTIPLE MODEL; MANEUVERING TARGET TRACKING; META MODEL; META MODEL FILTER; MOTION PATTERN; MULTIPLE MODEL ESTIMATION; MULTIPLE-MODEL FILTERING; ROAD VEHICLES; UNCERTAIN KNOWLEDGE;

EID: 70449370053     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (16)

References (18)
  • 1
    • 0024057021 scopus 로고
    • The interacting multiple model algorithm for systems with Markovian switching coefficients
    • Aug
    • H.A.P. Blom and Y. Bar-Shalom. The interacting multiple model algorithm for systems with Markovian switching coefficients. Automatic Control, IEEE Transactions on, 33(8):780-783, Aug 1988.
    • (1988) Automatic Control, IEEE Transactions on , vol.33 , Issue.8 , pp. 780-783
    • Blom, H.A.P.1    Bar-Shalom, Y.2
  • 7
    • 0034929691 scopus 로고    scopus 로고
    • Multitarget tracking with the IMM and Bayesian networks: Empirical studies
    • B. V. Dasarathy, editor, Society of Photo-Optical Instrumentation Engineers SPIE, March
    • S. K. Hautaniemi and J. P. Saarinen. Multitarget tracking with the IMM and Bayesian networks: empirical studies. In B. V. Dasarathy, editor, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, volume 4385, pages 47-57, March 2001.
    • (2001) Conference Series , vol.4385 , pp. 47-57
    • Hautaniemi, S.K.1    Saarinen, J.P.2
  • 8
    • 33947511176 scopus 로고    scopus 로고
    • Aaron Plotnik and Stephen Rock. Improved Estimation of Target Velocity Using Multiple Model Estimation and a Dynamic Bayesian Network for a Robotic Tracker of Ocean Animals. In Sebastian Thrun, Rodney A. Brooks, and Hugh F. Durrant-Whyte, editors, ISRR, 28 of Springer Tracts in Advanced Robotics, pages 402-415. Springer, 2005.
    • Aaron Plotnik and Stephen Rock. Improved Estimation of Target Velocity Using Multiple Model Estimation and a Dynamic Bayesian Network for a Robotic Tracker of Ocean Animals. In Sebastian Thrun, Rodney A. Brooks, and Hugh F. Durrant-Whyte, editors, ISRR, volume 28 of Springer Tracts in Advanced Robotics, pages 402-415. Springer, 2005.
  • 13
    • 70449414986 scopus 로고    scopus 로고
    • Decision System Laboratory, University of Pittsburgh
    • Decision System Laboratory. Smile reasoning engine. University of Pittsburgh, http://dsl.sis.pitt.edu.
    • Smile reasoning engine
  • 14
    • 56749124684 scopus 로고    scopus 로고
    • Multi level fusion for environment recognition
    • Philipp Lindner, Ullrich Scheunert, and Eric Richter. Multi level fusion for environment recognition. Pro-Fusion2 e-Journal, 2:24-30, 2008.
    • (2008) Pro-Fusion2 e-Journal , vol.2 , pp. 24-30
    • Lindner, P.1    Scheunert, U.2    Richter, E.3
  • 16
    • 57749185921 scopus 로고    scopus 로고
    • Radar and Vision based Data Fusion - Advanced Filtering Techniques for a Multi Object Vehicle Tracking System
    • 4-6 June
    • Eric Richter, Robin Schubert, and Gerd Wanielik. Radar and Vision based Data Fusion - Advanced Filtering Techniques for a Multi Object Vehicle Tracking System. In Proceedings of the IEEE Intelligent Vehicles Symposium, pages 120-125, 4-6 June 2008.
    • (2008) Proceedings of the IEEE Intelligent Vehicles Symposium , pp. 120-125
    • Richter, E.1    Schubert, R.2    Wanielik, G.3
  • 17
    • 21244437999 scopus 로고    scopus 로고
    • Unscented filtering and nonlinear estimation
    • Simon J. Julier and Jeffrey K. Uhlmann. Unscented filtering and nonlinear estimation. Proceedings of the IEEE, 92(3):401-422, 2004.
    • (2004) Proceedings of the IEEE , vol.92 , Issue.3 , pp. 401-422
    • Julier, S.J.1    Uhlmann, J.K.2
  • 18
    • 70449437908 scopus 로고    scopus 로고
    • Wan and Rudolph van der Merwe
    • chapter The Unscented Kalman Filter, Adaptive and Learning Systems for Signal Processing, Communications, and Control. John Wiley & Sons, Inc
    • Eric A. Wan and Rudolph van der Merwe. Kalman Filtering and Neural Networks, chapter The Unscented Kalman Filter, pages 221-280. Adaptive and Learning Systems for Signal Processing, Communications, and Control. John Wiley & Sons, Inc., 2001.
    • (2001) Kalman Filtering and Neural Networks , pp. 221-280
    • Eric, A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.