Classifying launch/impact events of mortar and artillery rounds utilizing DWT derived features and feedforward neural networks

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 6247, Issue , 2006, Pages

  Desai, Sachi ^a   Hohil, Myron ^a   Morcos, Amir ^a  

^a US Army Research Development and Engineering Command   (United States)

Author keywords

Acoustic Sensors; Artillery; Discrete Wavelet Transform; DWT; Impact; Launch; Multiresolutional Analysis; Neural Network

Indexed keywords

ACOUSTIC SIGNATURES; ARTILLERY; DISCRETE WAVELET TRANSFORM (DWT); IMPACT; LAUNCH; MULTIRESOLUTIONAL ANALYSIS;

ALGORITHMS; CLASSIFICATION (OF INFORMATION); DETONATION; FEATURE EXTRACTION; FEEDFORWARD NEURAL NETWORKS; MORTAR;

WAVELET TRANSFORMS;

EID: 33747339459     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.667877     Document Type: Conference Paper

References (6)

1. H.E. Bass, "Aero Acoustic Blast Classification Study (ACBS)", Interim Report for contract 95-F139300-000, January, 1996
2. Birenzvige, A., Sickenberger, D., and Reyes, F., "Disparate Sensor Integration Program Description and Preliminary Data Analysis", Report ECBC-TR-251, Edgewood Chemical Biological Center. September 2002.
3. Daubechies, I., 1992, Ten Lectures on Wavelets: SIAM, Capital City Press.
4. Vetterli, M., Kovacevic, J., "Wavelets and Subband Coding", Prentice Hall, NJ 1995
5. Mallet, S., "A theory for Multiresolution Signal Decomposition: The Wavelet Representation.", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 11. No. 7. July 1989.
6. Hohil, M., Desai. S., Chang, J., "Discrimination between High Explosive and Chemical/Biological Artillery Using Acoustic Sensors." Military Sensing Symposia, Laurel. MD. August 2004.