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Volumn 4728, Issue , 2002, Pages 80-90

EM-based measurement fusion for HRR radar centroid processing

Author keywords

Centroid Processing; EM Algorithm; High Range Resolution Radar; Measurement Fusion; Target Tracking

Indexed keywords

ALGORITHMS; MISSILES; OBJECT RECOGNITION; PROBABILITY; RADAR TRACKING; TRACKING (POSITION);

EID: 0036458468     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.478540     Document Type: Conference Paper
Times cited : (5)

References (17)
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    • Methods to reduce range glint in radars
    • C.A. Hamner and M.W. Maier, "Methods to reduce range glint in radars," IEEE Aerospace Conference 3, pp. 83-102, 1997.
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  • 9
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    • Comparison of two measurement fusion methods for Kalman-filter-based multisensor data fusion
    • January
    • Q. Gan and C.J. Harris, "Comparison of two measurement fusion methods for Kalman-filter-based multisensor data fusion," IEEE Trans. on Aerospace and Electronic Systems 37, pp. 273-280, January 2001.
    • (2001) IEEE Trans. on Aerospace and Electronic Systems , vol.37 , pp. 273-280
    • Gan, Q.1    Harris, C.J.2
  • 14
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    • A non-divergent estimation algorithm in the presence of unknown correlations
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    • Julier, S.J.1    Uhlmann, J.K.2
  • 15
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    • Information fusion based on fast covariance intersection filtering
    • Submitted Preprint, July
    • W. Niehsen, "Information fusion based on fast covariance intersection filtering," Submitted Preprint, International Conference on Information Fusion, July 2002.
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    • Niehsen, W.1
  • 17
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    • Determining the number of components in Gaussian mixtures using agglomerative clustering
    • S. Medasani and R. Krishnapuram, "Determining the number of components in Gaussian mixtures using agglomerative clustering," International Conference on Neural Networks 3, pp. 1412-1417, 1997.
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    • Medasani, S.1    Krishnapuram, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.