We detect the presence of a vehicle or an air borne target from a certain class via the analysis of its acoustic signature against an existing database of recorded and processed acoustic signals. To achieve this detection with no false alarms we construct the acoustic signatures of certain targets to be found by the distribution of the energies among blocks which consist of wavelet packet coefficients. We developed an efficient procedure for adaptive selection of the characteristic blocks. We modified the CART algorithm in order to utilize it as a decision unit in our scheme. A wide series of field experiments manifested a remarkable efficiency of the algorithm. The detection had been achieved practically with no false alarms even under severe conditions such as the acoustic recording of sought-after object was a superposition of the acoustic emitted from other targets that belong to other classes. The detection was even immune to severe noisy surroundings.
|Number of pages||12|
|Journal||Proceedings of SPIE - The International Society for Optical Engineering|
|State||Published - 4 Feb 2000|
- Acoustic Signatur
- CART Algorithm
- Discriminant Blocks
- Wavelet Packets