ACOUSTIC SIGNATURE RECOGNITION OF RUNNING VEHICLES USING SPECTRO-TEMPORAL DYNAMIC NEURAL NETWORK
First Claim
1. An apparatus for identifying running vehicles using acoustic signatures, comprising:
- an input sensor configured to capture an acoustic waveform produced by a vehicle source in an area to be monitored and convert the waveform into a digitized electrical signal; and
a processing system configured todivide the digitized electrical signal into a plurality of frames;
compute at least one spectral feature vector for each frame;
integrate said spectral feature vectors over the plurality of frames to produce a spectro-temporal representation of said acoustic waveform, andapply values obtained from said spectro-temporal representation as inputs to a learning function to determine an acoustic signature of the vehicle source.
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Accused Products
Abstract
A method and apparatus for identifying running vehicles in an area to be monitored using acoustic signature recognition. The apparatus includes an input sensor for capturing an acoustic waveform produced by a vehicle source, and a processing system. The waveform is digitized and divided into frames. Each frame is filtered into a plurality of gammatone filtered signals. At least one spectral feature vector is computed for each frame. The vectors are integrated across a plurality of frames to create a spectro-temporal representation of the vehicle waveform. In a training mode, values from the spectro-temporal representation are used as inputs to a Nonlinear Hebbian learning function to extract acoustic signatures and synaptic weights. In an active mode, the synaptic weights and acoustic signatures are used as patterns in a supervised associative network to identify whether a vehicle is present in the area to be monitored. In response to a vehicle being present, the class of vehicle is identified. Results may be provided to a central computer.
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Citations
30 Claims
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1. An apparatus for identifying running vehicles using acoustic signatures, comprising:
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an input sensor configured to capture an acoustic waveform produced by a vehicle source in an area to be monitored and convert the waveform into a digitized electrical signal; and a processing system configured to divide the digitized electrical signal into a plurality of frames; compute at least one spectral feature vector for each frame; integrate said spectral feature vectors over the plurality of frames to produce a spectro-temporal representation of said acoustic waveform, and apply values obtained from said spectro-temporal representation as inputs to a learning function to determine an acoustic signature of the vehicle source. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A method for identifying running vehicles using acoustic signatures, comprising:
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capturing an acoustic waveform produced by a vehicle source in an area to be monitored; amplifying the acoustic waveform; converting the waveform into a digitized electrical signal; dividing the digitized electrical signal into a plurality of frames; computing at least one spectral feature vector for each frame; integrating said spectral feature vectors over the plurality of frames to produce a spectro-temporal representation of said acoustic waveform; and applying values obtained from said spectro-temporal representation as inputs to a learning function to determine an acoustic signature of the vehicle source. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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25. A system for identifying running vehicles in an area to be monitored using acoustic signatures, comprising:
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at least one local sensor, the local sensor comprising an input sensor configured to capture an acoustic waveform produced by a vehicle source, and convert the waveform into an electrical signal, a processing system configured to divide the electrical signal into frames;
compute a spectral feature vector for each frame;
integrate said spectral feature vectors over the plurality of frames to produce a spectro-temporal representation of said acoustic waveform, apply values obtained from said spectro-temporal representation as inputs to a learning function to determine an acoustic signature of the vehicle source, and identify, based on the determined acoustic signature, the vehicle source; anda command center comprising a central computer configured to receive a message from said at least one local sensor, said message comprising information sufficient to identify said source. - View Dependent Claims (26, 27, 28, 29)
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30. An apparatus for identifying running vehicles using acoustic signatures, comprising:
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input sensor means for capturing an acoustic waveform produced by a vehicle source in an area to be monitored and converting the waveform into a digitized electrical signal; and processing means for dividing the digitized electrical signal into a plurality of frames, computing at least one spectral feature vector for each frame, integrating said spectral feature vectors over the plurality of frames to produce a spectro-temporal representation of said acoustic waveform, and applying values obtained from said spectro-temporal representation as inputs to a learning function to determine an acoustic signature of the vehicle source.
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Specification