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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-04282011-110619


Tipo di tesi
Tesi di laurea specialistica
Autore
LISCHI, STEFANO
URN
etd-04282011-110619
Titolo
Human recognition and motion classification by acoustic micro-Doppler signatures
Dipartimento
INGEGNERIA
Corso di studi
INGEGNERIA DELLE TELECOMUNICAZIONI
Relatori
tutor Dott. Balleri, Alessio
correlatore Prof. Griffiths, Hugh
controrelatore Prof. Gini, Fulvio
relatore Prof.ssa Greco, Maria Sabrina
Parole chiave
  • acoustic
  • cepstrum
  • feature extraction
  • gait recognition
  • gaussian mixture model
  • mel cepstrum
  • micro-Doppler
  • radar
  • target classification
  • ultrasound
Data inizio appello
27/06/2011
Consultabilità
Parziale
Data di rilascio
27/06/2051
Riassunto
Classification of personnel targets by micro-Doppler signatures has received a growing interest in recent years. Although most of the work has been carried out in the RF regime for radar systems, much less research has been done in acoustic.
In this thesis a dataset collected with an acoustic radar, which consists of micro-Doppler signatures of different personnel targets undertaking various motions, is analysed. A set of heuristic features, such as the micro-Doppler signature bandwidth and period, is extracted from the data and it is used together with Cepstral features to assess classification performance of a Maximum Likelihood classifier.
Results show that high level classification performance can be achieved for both human recognition and motion classification.
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