Title :
A comparison of neural networks and statistical methods for track association in over the horizon radar
Author :
Zhu, J. ; Bogner, R.E. ; Bouzerdoum, A. ; Pope, K.J. ; Southcott, M.L.
Author_Institution :
Dept. of Electr. & Electron. Eng., Adelaide Univ., SA, Australia
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
Keywords :
feature extraction; multilayer perceptrons; pattern classification; radar target recognition; statistical analysis; human perceptual grouping principles; ionospheric model-free pattern classification; neural networks; over the horizon radar; pairwise association; statistical methods; track affinities; track association; Feature extraction; Humans; Intelligent networks; Ionosphere; Neural networks; Pattern classification; Radar tracking; Statistical analysis; Target tracking; Testing;
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
DOI :
10.1109/ICNN.1995.487740
