Comparison of neural networks and statistical methods for track association in Over The Horizon Radar

J. Zhu; R. E. Bogner; A. Bouzerdoum; K. J. Pope; M. L. Southcott

doi:10.1109/ICNN.1995.487740

Comparison of neural networks and statistical methods for track association in Over The Horizon Radar

J. Zhu, R. E. Bogner, A. Bouzerdoum, K. J. Pope, M. L. Southcott

Research output: Contribution to conference › Paper › peer-review

3 Citations (Scopus)

Abstract

An ionospheric model-free pattern classification approach is proposed for associating tracks in Over The Horizon Radar. A set of track features and track affinity measures are derived according to human perceptual grouping principles. To facilitate the pairwise association of the tracks, neural networks and statistical methods are applied to combine different track affinities. A posterior pseudo-probability measuring association is produced for every pair of tracks.

Original language	English
Pages	2415-2420
Number of pages	6
DOIs	https://doi.org/10.1109/ICNN.1995.487740
Publication status	Published - 1995
Externally published	Yes
Event	Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) - Perth, Aust Duration: 27 Nov 1995 → 1 Dec 1995

Conference

Conference	Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6)
City	Perth, Aust
Period	27/11/95 → 1/12/95

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10.1109/ICNN.1995.487740Licence: In Copyright

Cite this

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title = "Comparison of neural networks and statistical methods for track association in Over The Horizon Radar",

abstract = "An ionospheric model-free pattern classification approach is proposed for associating tracks in Over The Horizon Radar. A set of track features and track affinity measures are derived according to human perceptual grouping principles. To facilitate the pairwise association of the tracks, neural networks and statistical methods are applied to combine different track affinities. A posterior pseudo-probability measuring association is produced for every pair of tracks.",

author = "J. Zhu and Bogner, {R. E.} and A. Bouzerdoum and Pope, {K. J.} and Southcott, {M. L.}",

year = "1995",

doi = "10.1109/ICNN.1995.487740",

language = "English",

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note = "Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) ; Conference date: 27-11-1995 Through 01-12-1995",

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AU - Zhu, J.

AU - Bogner, R. E.

AU - Bouzerdoum, A.

AU - Pope, K. J.

AU - Southcott, M. L.

PY - 1995

Y1 - 1995

N2 - An ionospheric model-free pattern classification approach is proposed for associating tracks in Over The Horizon Radar. A set of track features and track affinity measures are derived according to human perceptual grouping principles. To facilitate the pairwise association of the tracks, neural networks and statistical methods are applied to combine different track affinities. A posterior pseudo-probability measuring association is produced for every pair of tracks.

AB - An ionospheric model-free pattern classification approach is proposed for associating tracks in Over The Horizon Radar. A set of track features and track affinity measures are derived according to human perceptual grouping principles. To facilitate the pairwise association of the tracks, neural networks and statistical methods are applied to combine different track affinities. A posterior pseudo-probability measuring association is produced for every pair of tracks.

UR - http://www.scopus.com/inward/record.url?scp=0029457352&partnerID=8YFLogxK

U2 - 10.1109/ICNN.1995.487740

DO - 10.1109/ICNN.1995.487740

M3 - Paper

AN - SCOPUS:0029457352

SP - 2415

EP - 2420

T2 - Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6)

Y2 - 27 November 1995 through 1 December 1995

ER -

Comparison of neural networks and statistical methods for track association in Over The Horizon Radar

Abstract

Conference

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