Agent detection in the presence of background clutter

Abstract

The present invention generally provides systems and methods for detection of agents of interest in a bulk quantity of matter, which also contains clutter and other constituents that typically interfere with the detection of one or more agents of interest. A detection system of the invention generally contains a collection subsystem for obtaining a bulk sample, an interrogation subsystem for generating one or more analytical signals representative of the composition of the bulk sample, and an analytical subsystem according to the teachings of the invention that implements the methods and algorithms of the invention for analyzing the sample analytical signals to determine whether one or more agents of interest are present, e.g., at quantities above a certain threshold, in the bulk sample.

Description

RELATED APPLICATION[0001]The present application claims priority to provisional application No. 60 / 723,985 entitled “Agent detection in the presence of background clutter,” filed on Oct. 3, 2005, which is herein incorporated by reference.[0002]This invention was made with U.S. Government support under contract number DAAD13-03-C-0077 awarded by the Department of Defense. The government has certain rights in the invention.BACKGROUND OF THE INVENTION[0003]The present invention relates generally to methods and systems for detecting agents in a bulk sample that can include one or more background constituents, and more particularly, for detecting bio-aerosol warfare agents.[0004]The detection of bio-aerosol warfare agents in the presence of either indoor or outdoor backgrounds is a difficult problem. Natural backgrounds are variable and can simultaneously include multiple constituents. The variation of each constituent may be larger than the concentration level of an agent whose detectio...

AI Technical Summary

Benefits of technology

[0010]The agent-detection methods of the present invention can be utilized in conjunction with bulk collection and immobilization of a sample under investigation to achieve greater sensitivity, lower cost than conventional techniques, and to render a large variety of measurements of the sample feasible. As discussed in more detail below, the methods and systems of the invention allow suppressing contributions of unwanted background constituents in a bulk sample to information obtained about the sample (e.g., via spectral measurements) by utilizing previously-obtained information about the signatures of the agents and the background constituents of interest. The present invention advantageously increases the types of signatures that can be employed for agent detection.

[0011]In one aspect, the invention provides a method of detecting an agent in a bulk sample, which includes at least one background constituent, that comprises utilizing a measurement modality to interrogate the sample with electromagnetic radiation so as to generate spectral data corresponding to the sample. The principal components of the spectral data can then be derived and represented as a vector in a principal component space. A rotate-and-suppress transformation can be applied to the principal component vector, wherein the transformation suppresses, and preferably eliminates, the contributions of the background constituent, if present, thereby generating a background-suppressed principal component vector corresponding to the sample. This transformed sample vector can be compared with a background-suppressed principal component vector corresponding to the agent to determine whether the agent is present in the bulk sample. The background-suppressed principal component vector of the agent can be generated by application of the rotate-and-suppress transformation to the principal components of the spectral data of the agent obtained by employing the same measurement modality as that utilized to interrogate the sample.

[0012]The above step of comparing the background-suppressed principal component vectors of the sample and the agent can comprise determining a spectral angle that separates the two vectors in the principal component space. If the spectral angle is within a pre-defined range, a detection of the agent in the sample can be indicated. In some embodiments, this criterion constitutes only one prong of a two-prong test for indicating the detection of the agent within the sample. The other prong requires that the dot product of the two vectors obtained, for example, in selected two-dimensional sub-spaces of the principal component space, be above a pre-defined threshold. In some embodiments, once it is determined that the angle between the two vectors lies in a predefined range, a warning is issued. If not only the angle is within the range, but also the dot product is above a selected threshold, an Alert / Alarm processor is triggered. Such a two-step test procedure can lower the risk of issuing false alarms.

[0015]In many embodiments, Principal Component Analysis (PCA) is utilized for deriving the principal components of spectral data associated with the agents, background constituents, as well as the samples under investigation. Principal Component Analysis (PCA) is a well-known technique for determining the most important components of multi-dimensional measurements of a collection of agents and backgrounds. Using PCA, the dimensionality of the measurement space can be reduced while maintaining the distinguishing features of the original measurements.

Problems solved by technology

The detection of bio-aerosol warfare agents in the presence of either indoor or outdoor backgrounds is a difficult problem.

The detection problems can be further exacerbated by the presence of spikes in measurement data of a naturally-occurring background, which may be an order of magnitude larger than the contribution of the normal quiescent background.

Such spikes may last for minutes and may exhibit large variations in particle count.

The detection of other important agents share some of the difficulties associated with the detection of bioaerosols.

The detection sensitivity can be increased by concentrating the sample to be analyzed, but at the risk of having both large amounts of background and small amounts of agent in the same sample.

Thus, the detection of simulants is also an important problem requiring solution.

However, it is not suitable for signatures that have broad features, such as UV-induced fluorescence spectra and lifetime measurements, x-ray fluorescence spectra, and terahertz (THz) spectra.

Hence, this conventional approach has the disadvantage that it limits the detection techniques that can be used to solve a given agent detection problem.

However, single particle flow-through systems have several disadvantages.

However, even with more expensive hardware, the detection rate for very small particles is generally negligible, leading to an inability to detect aerosols composed of small particles (such as viruses), even if the particle number density is large.

Even for large particles, a low detection rate can render sufficient data collection for a statistically meaningful detection (build-up of a particle count that is sufficient for agent detection) cumbersome and time-consuming.

Second, only a small number of measurements can be made simultaneously.

This can result, in turn, in placing different particle types in the same histogram bin, leading to a high false alarm rate.

Finally, the flow of particles near the large aperture collection optics of such systems can lead to fouling of the optics, thus lowering the optical efficiency of the system and driving up maintenance costs.

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