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Title: Unmanned aircraft system (UAS) detection and assessment via temporal intensity aliasing

Abstract

A method and system for temporal frequency analysis for identification of unmanned aircraft systems. The method includes obtaining a sequence of video image frames and providing a pixel from an output frame of the video; generating a fluctuating pixel value vector; examining the fluctuating pixel value vector over a period of time; obtaining the frequency information present in the pixel fluctuations; summing the frequency coefficients for the vectorized pixel values from the fluctuating pixel value vector; obtaining an image representing a two dimensional space based on the summed center frequency coefficients; generating a series of still frames equal to a summation of the center frequency coefficients for pixel variations; and combining the temporal information into spatial locations in a matrix to provide a single image containing the spatial and temporal information present in the sequence of video image frame.

Inventors:
; ; ;
Issue Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1823841
Patent Number(s):
10977772
Application Number:
16/141,385
Assignee:
National Technology & Engineering Solutions of Sandia, LLC (Albuquerque, NM)
Patent Classifications (CPCs):
G - PHYSICS G06 - COMPUTING G06T - IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
DOE Contract Number:  
NA0003525
Resource Type:
Patent
Resource Relation:
Patent File Date: 09/25/2018
Country of Publication:
United States
Language:
English

Citation Formats

Woo, Bryana Lynn, Birch, Gabriel Carlisle, Stubbs, Jaclynn Javonna, and Kouhestani, Camron G. Unmanned aircraft system (UAS) detection and assessment via temporal intensity aliasing. United States: N. p., 2021. Web.
Woo, Bryana Lynn, Birch, Gabriel Carlisle, Stubbs, Jaclynn Javonna, & Kouhestani, Camron G. Unmanned aircraft system (UAS) detection and assessment via temporal intensity aliasing. United States.
Woo, Bryana Lynn, Birch, Gabriel Carlisle, Stubbs, Jaclynn Javonna, and Kouhestani, Camron G. Tue . "Unmanned aircraft system (UAS) detection and assessment via temporal intensity aliasing". United States. https://www.osti.gov/servlets/purl/1823841.
@article{osti_1823841,
title = {Unmanned aircraft system (UAS) detection and assessment via temporal intensity aliasing},
author = {Woo, Bryana Lynn and Birch, Gabriel Carlisle and Stubbs, Jaclynn Javonna and Kouhestani, Camron G.},
abstractNote = {A method and system for temporal frequency analysis for identification of unmanned aircraft systems. The method includes obtaining a sequence of video image frames and providing a pixel from an output frame of the video; generating a fluctuating pixel value vector; examining the fluctuating pixel value vector over a period of time; obtaining the frequency information present in the pixel fluctuations; summing the frequency coefficients for the vectorized pixel values from the fluctuating pixel value vector; obtaining an image representing a two dimensional space based on the summed center frequency coefficients; generating a series of still frames equal to a summation of the center frequency coefficients for pixel variations; and combining the temporal information into spatial locations in a matrix to provide a single image containing the spatial and temporal information present in the sequence of video image frame.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2021},
month = {4}
}

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