DocumentCode
1622661
Title
Using self-organising maps to classify radar range profiles
Author
Luttrell, S.P.
Author_Institution
Defence Res. Agency, UK
fYear
1995
Firstpage
335
Lastpage
340
Abstract
A model based approach to radar range profile classification is presented, and it is shown to be equivalent to training a topographic mapping neural network (T. Kohonen, 1984) on each of the range profile categories to be classified. The topographic mapping method is basically a Euclidean distance method of classifying range profiles. However, because it is model based, it offers much more flexibility, and will perform better in situations where there is little training data
Keywords
pattern classification; radar altimetry; radar signal processing; self-organising feature maps; Euclidean distance method; Kohonen SOMs; model based approach; radar range profile classification; range profile categories; self organising maps; topographic mapping method; topographic mapping neural network training; training data;
fLanguage
English
Publisher
iet
Conference_Titel
Artificial Neural Networks, 1995., Fourth International Conference on
Conference_Location
Cambridge
Print_ISBN
0-85296-641-5
Type
conf
DOI
10.1049/cp:19950578
Filename
497841
Link To Document