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Integrating a sensor suite with ability to discriminate potential Chemical/Biological (CB) events from high-explosive
(HE) events employing a standalone acoustic sensor with a Time Difference of Arrival (TDOA)
algorithm we developed a cueing mechanism for more power intensive and range limited sensing
techniques. Enabling the event detection algorithm to locate to a blast event using TDOA we then provide
further information of the event as either Launch/Impact and if CB/HE. The added information is provided
to a range limited chemical sensing system that exploits spectroscopy to determine the contents of the
chemical event. The main innovation within this sensor suite is the system will provide this information on
the move while the chemical sensor will have adequate time to determine the contents of the event from a
safe stand-off distance. The CB/HE discrimination algorithm exploits acoustic sensors to provide early
detection and identification of CB attacks. Distinct characteristics arise within the different airburst
signatures because HE warheads emphasize concussive and shrapnel effects, while CB warheads are
designed to disperse their contents over large areas, therefore employing a slower burning, less intense
explosive to mix and spread their contents. Differences characterized by variations in the corresponding
peak pressure and rise time of the blast, differences in the ratio of positive pressure amplitude to the
negative amplitude, and variations in the overall duration of the resulting waveform. The discrete wavelet
transform (DWT) is used to extract the predominant components of these characteristics from air burst
signatures at ranges exceeding 3km. Highly reliable discrimination is achieved with a feed-forward neural
network classifier trained on a feature space derived from the distribution of wavelet coefficients and
higher frequency details found within different levels of the multiresolution decomposition. The
development of an adaptive noise floor to provide early event detection assists in minimizing the false
alarm rate and increasing the confidence whether the event is blast event or back ground noise. The
integration of these algorithms with the TDOA algorithm provides a complex suite of algorithms that can
give early warning detection and highly reliable look direction from a great stand-off distance for a moving
vehicle to determine if a candidate blast event is CB and if CB what is the composition of the resulting
cloud.
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