The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 14, 2000

Filed:

Jul. 12, 1996
Applicant:
Inventors:

Peter J Palmadesso, Montclair, VA (US);

John A Antoniades, Fulton, MD (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K / ;
U.S. Cl.
CPC ...
382191 ;
Abstract

The Intelligent Hypersensor Processing System (IHPS) is a system for the rapid detection of small, weak, or hidden objects, substances, or patterns embedded in complex backgrounds. providing fast adaptive processing for demixing and recognizing patterns or signatures in data provided by certain types of 'hypersensors'. This system represents an alternative to prior systems for hidden object detection by solving the problems encountered when attempting to detect hidden objects/targets in dynamic scenarios at real-time. IHPS accomplishes this by forming, a series of pattern vectors through the concatenation of the outputs of multiple sensors. Each sensor measures a different attribute of the system being observed, and has a consistent relationship to all the other sensors. The data stream form the sensors is entered into a processing system which employs a parallel-pipeline architecture. The data stream is simultaneously sent to two separate processor pipes. The first is the Demixer Module, which decomposes each pattern vector into a convex combination of a set of fundamental patterns which are the constituents of the mixture. The decomposition is accomplished using projection operations called `Filter Vectors` generated by the Adaptive Learning Module. The signature pattern of a weak constituent or unresolved small target is separated from background patterns which may hide the target pattern in the unmixed data. A prior knowledge about the signatures of known targets can be used and approximate signatures of unknown constituents are determined automatically. Information detailing the composition of the demixed data patterns is sent to the Display/Output Module along with information about the fundamental patterns and Filter Vectors.


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