A wavelet packet algorithm for classification and detection of moving vehicles

In this paper we propose a robust algorithm that solves two related problems: 1) Classification of acoustic signals emitted by different moving vehicles. The recorded signals have to be assigned to pre-existing categories independently from the recording surrounding conditions. 2) Detection of the presence of a vehicle in a certain class via analysis of its acoustic signature against the existing database of recorded and processed acoustic signals. To achieve this detection with practically no false alarms we construct the acoustic signature of a certain vehicle using the distribution of the energies among blocks which consist of wavelet packet coefficients. We allow no false alarms in the detection even under severe conditions; for example when the acoustic recording of target object is a superposition of the acoustics emitted from other vehicles that belong to other classes. The proposed algorithm is robust even under severe noise and a range of rough surrounding conditions. This technology, which has many algorithmic variations, can be used to solve a wide range of classification and detection problems which are based on acoustic processing which are not related to vehicles. These have numerous applications.