UAS Detection Classification and Neutralization: Market Survey 2015

Birch, Gabriel Carisle; Griffin, John Clark; Erdman, Matthew Kelly

doi:10.2172/1222445

Title: UAS Detection Classification and Neutralization: Market Survey 2015

Full Record
Other Related Research

Abstract

The purpose of this document is to briefly frame the challenges of detecting low, slow, and small (LSS) unmanned aerial systems (UAS). The conclusion drawn from internal discussions and external reports is the following; detection of LSS UAS is a challenging problem that can- not be achieved with a single detection modality for all potential targets. Classification of LSS UAS, especially classification in the presence of background clutter (e.g., urban environment) or other non-threating targets (e.g., birds), is under-explored. Though information of avail- able technologies is sparse, many of the existing options for UAS detection appear to be in their infancy (when compared to more established ground-based air defense systems for larger and/or faster threats). Companies currently providing or developing technologies to combat the UAS safety and security problem are certainly worth investigating, however, no company has provided the statistical evidence necessary to support robust detection, identification, and/or neutralization of LSS UAS targets. The results of a market survey are included that highlights potential commercial entities that could contribute some technology that assists in the detection, classification, and neutral- ization of a LSS UAS. This survey found no clear and obvious commercial solution, though recommendations are given for further investigationmore » of several potential systems.« less

Authors:

Birch, Gabriel Carisle ^[1]; Griffin, John Clark ^[1]; Erdman, Matthew Kelly ^[1]

Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Publication Date:: Wed Jul 01 00:00:00 EDT 2015

Research Org.:: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Sponsoring Org.:: USDOE National Nuclear Security Administration (NNSA)

OSTI Identifier:: 1222445

Report Number(s):: SAND2015-6365
606150

DOE Contract Number:: AC04-94AL85000

Resource Type:: Technical Report

Country of Publication:: United States

Language:: English

Citation Formats


                    Birch, Gabriel Carisle, Griffin, John Clark, and Erdman, Matthew Kelly. UAS Detection Classification and Neutralization: Market Survey 2015.  United States: N. p., 2015. 
        Web.  doi:10.2172/1222445.

Copy to clipboard


                    Birch, Gabriel Carisle, Griffin, John Clark, & Erdman, Matthew Kelly. UAS Detection Classification and Neutralization: Market Survey 2015.  United States.  https://doi.org/10.2172/1222445

Copy to clipboard


                    Birch, Gabriel Carisle, Griffin, John Clark, and Erdman, Matthew Kelly. 2015.  
        "UAS Detection Classification and Neutralization: Market Survey 2015".  United States.  https://doi.org/10.2172/1222445.  https://www.osti.gov/servlets/purl/1222445.

Copy to clipboard


                    
@article{osti_1222445,

  title        = {UAS Detection Classification and Neutralization: Market Survey 2015},

  author       = {Birch, Gabriel Carisle and Griffin, John Clark and Erdman, Matthew Kelly},

  abstractNote = {The purpose of this document is to briefly frame the challenges of detecting low, slow, and small (LSS) unmanned aerial systems (UAS). The conclusion drawn from internal discussions and external reports is the following; detection of LSS UAS is a challenging problem that can- not be achieved with a single detection modality for all potential targets. Classification of LSS UAS, especially classification in the presence of background clutter (e.g., urban environment) or other non-threating targets (e.g., birds), is under-explored. Though information of avail- able technologies is sparse, many of the existing options for UAS detection appear to be in their infancy (when compared to more established ground-based air defense systems for larger and/or faster threats). Companies currently providing or developing technologies to combat the UAS safety and security problem are certainly worth investigating, however, no company has provided the statistical evidence necessary to support robust detection, identification, and/or neutralization of LSS UAS targets. The results of a market survey are included that highlights potential commercial entities that could contribute some technology that assists in the detection, classification, and neutral- ization of a LSS UAS. This survey found no clear and obvious commercial solution, though recommendations are given for further investigation of several potential systems.},

  doi          = {10.2172/1222445},

  url          = {https://www.osti.gov/biblio/1222445},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {Wed Jul 01 00:00:00 EDT 2015},

  month        = {Wed Jul 01 00:00:00 EDT 2015}

}

Copy to clipboard

Technical Report:

View Technical Report (8.30 MB)

https://doi.org/10.2172/1222445

Save / Share:

Export Metadata

Save to My Library

Similar records in OSTI.GOV collections:

Polarized Radar for Detection and Automatic Non-Visual Assessment of Unmanned Aerial Systems.

Technical Report McVay, John

This Laboratory Directed Research and Development ( LDRD ) effort performed fundamental Research and Development ( R&D ) to develop a robust radar processing algorithm capable of assessing the difference between an Unmanned Aerial System (UAS) and a biological target such as a bird, based on mathematics applied to the polarized radar returns of the target object , alone. The current threat s of using such a UAS as a delivery platform for a host of destructive components is a major concern for the protection of various assets. Most r ecently , on 14 th Sept . 2019, dozens ofmore »« less
https://doi.org/10.2172/1570099

Full Text Available
UAS Activity Profile Survey

Technical Report Burr, Casey

Commercial vendors, trying to tap into the physical protection of critical infrastructure, are offering nuclear facilities the opportunity to borrow detection counter-unmanned aircraft systems (CUAS) equipment to survey the airspace over and around the facility. However, using one vendor or method of detection (e.g., radio frequency [RF], radar, acoustic, visual) will not necessarily provide a complete airspace profile since no single method can detect all UAS threats. Using several detection technologies, the unmanned aircraft systems (UAS) Team, who supports the U.S. National Nuclear Security Administration (NNSA) Office of International Nuclear Security (INS), would like to offer partners a comprehensive airspacemore »« less
https://doi.org/10.2172/1900361

Full Text Available
DHS S&T First Responders Group and NATO Counter UAS Proposal Interest Response.

Technical Report Salton, Jonathan

The capability, speed, size, and widespread availability of small unmanned aerial systems (sUAS) makes them a serious security concern. The enabling technologies for sUAS are rapidly evolving and so too are the threats they pose to national security. Potential threat vehicles have a small cross-section, and are difficult to reliably detect using purely ground-based systems (e.g. radar or electro-optical) and challenging to target using conventional anti-aircraft defenses. Ground-based sensors are static and suffer from interference with the earth, vegetation and other man-made structures which obscure objects at low altitudes. Because of these challenges, sUAS pose a unique and rapidly evolvingmore » threat to national security.« less
https://doi.org/10.2172/1420749

Full Text Available
Flight Considerations and Hyperspectral Image Classifications for Dryland Vegetation Management from a Fixed-wing UAS

Journal Article Mitchell, Jessica; Glenn, Nancy; Anderson, Matthew; ... - Environmental Management and Sustainable Development

Unmanned Aerial Systems (UAS)-based hyperspectral remote sensing capabilities developed by the Idaho National Lab and Boise Center Aerospace Lab were tested via demonstration flights that explored the influence of altitude on geometric error, image mosaicking, and dryland vegetation classification. The motivation for this study was to better understand the challenges associated with UAS-based hyperspectral data for distinguishing native grasses such as Sandberg bluegrass (Poa secunda) from invasives such as burr buttercup (Ranunculus testiculatus) in a shrubland environment. The test flights successfully acquired usable flightline data capable of supporting classifiable composite images. Unsupervised classification results support vegetation management objectives that relymore »« less
https://doi.org/10.5296/emsd.v5i2.9343

Full Text Available
A Highly Miniaturized Cloud and Aerosol Instrument Package for Small UAS's

Technical Report Lawson, R.

Unmanned Aerial Systems (UAS’s), which include Unmanned Aerial Vehicles (UAV’s) and tethered balloon systems (TBS) offer significant advantages over conventional research aircraft. They are capable of long-duration measurements of cloud properties in regions where piloted aircraft are unsafe, e.g., at very low altitudes over remote regions, such as tundra and open ocean. TBS and UAV’s are now widely recognized as a technology that can provide unprecedented insights into cloud and radiation processes, but development of miniature sensors capable of providing sophisticated measurements of cloud, aerosol and radiative properties lag behind. In Phase II of this SBIR research, Stratton Park Engineeringmore »« less
https://doi.org/10.2172/1542254

Full Text Available

Similar Records