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[ZSV08] Automatic identification of bird targets with radar via patterns produced by wing flappingRevue Internationale avec comité de lecture : Journal Journal R. Soc. Interface, vol. 5(26), pp. 1041-1053 , 2008, (doi:10.1098/rsif.2007.1349)Mots clés: radar ornithology,bird identification,pattern recognition,continuous wavelet transform, feature extraction ,support vector machine
Résumé:
Bird identification with radar is important for bird migration research, environmental
impact assessments (e.g. wind farms), aircraft security and radar meteorology. In a study on
bird migration, radar signals from birds, insects and ground clutter were recorded. Signals
from birds show a typical pattern due to wing flapping. The data were labelled by experts into
the four classes BIRD, INSECT, CLUTTER and UFO (unidentifiable signals). We present a
classification algorithm aimed at automatic recognition of bird targets. Variables related to
signal intensity and wing flapping pattern were extracted (via continuous wavelet
transform). We used support vector classifiers to build predictive models. We estimated
classification performance via cross validation on four datasets. When data from the same
dataset were used for training and testing the classifier, the classification performance was
extremely to moderately high. When data from one dataset were used for training and the
three remaining datasets were used as test sets, the performance was lower but still extremely
to moderately high. This shows that the method generalizes well across different locations or
times. Our method provides a substantial gain of time when birds must be identified in large
collections of radar signals and it represents the first substantial step in developing a real time
bird identification radar system. We provide some guidelines and ideas for future research.
Equipe:
msdma
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