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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