Importance Ranking of Features for Human Micro-Doppler Classification with a Radar Network
Küçük Resim Yok
Tarih
2013
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Over the past decade, the human micro-Doppler signature has been a subject of intense research. In particular, much work has been done in relation to computing features for use in a variety of classification problems, such as arm swing detection, activity classification, and target identification. Although dozens of features have been proposed for these purposes, little work has examined the issue of which features are more important - i.e., have a greater impact on classification performance - than others. In this work, an information theoretic approach is applied to compute the importance ranking of features prior to classification for the specific problem of discriminating human walking from running. Results show that the ranking of features according to mutual information directly relates to classification performance using support vector machines.
Açıklama
16th International Conference on Information Fusion (FUSION) -- JUL 09-12, 2013 -- Istanbul, TURKEY
Anahtar Kelimeler
human micro-Doppler; feature selection; classification; multistatic radar; radar network
Kaynak
2013 16th International Conference On Information Fusion (Fusion)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
