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Swarm
Unmanned Aerial System (UAS) operations by sophisticated state and even
non-state actors are a cause for concern to the U.S. Navy partly because
the threat potential is not fully known. Some military theorists assert
that “swarming” could be the Third Offset Strategy in military thinking and
the basis for possible wide-scale impacts on military operations and
tactics (e.g., [i]).
Swarming is “a tactic that employs multiple Unmanned Aerial Vehicles (UAV)
[often small UAV or sUAV] to overwhelm targets by using mass and attrition
in combination with decentralized maneuvers or combined fires from multiple
directions.”[ii]
Swarms may be used to disrupt ship deck or
aircraft flight operations, confuse the tactical picture and situational
awareness, precipitate inefficient or pre-mature expenditure of defensive
weapons, conduct reconnaissance and intelligence gathering, obscure or mask
high-threat units, overwhelm defenses, or themselves deliver
micro-munitions including chemical or biologic using coordinated ambush,
circling, or multi-axis attacks. Swarms can be trained to exhibit intricate
and difficult-to-predict animal or biological behaviors[iii].
Detection,
identification, and tracking of UAS sUAV swarms is challenging because of
deformability, low sUAV Signal to Noise Ratio (SNR), large numbers of
units, and elements of tactics such as ambush. Irregular grouping and
ungrouping dynamics complicate the swarm picture, as the arrangement can
change fluidly. Detection, identification, and tracking are functions of
data fusion (DF). A specialized DF function is the identification
(including classification) of hard to detect and recognize objects, e.g., swarms,
for which Deep Learning (DL) has in recent years shown to be a good
solution. MSDIT’s innovations to this DF problem include:
Resolve
Multiple Targets in a Single Return Pulse. For long to mid-range
swarms, Detection and Identification (D&I) as an Unresolved Group
Target (UGT) by radar intrapulse modulations using DL trained on
synthetically superposed sUAV inverse backscattering and sUAV propeller
Doppler signatures.
Volumetric Spatial
Frequencies Analysis. For mid to short-range swarms, D&I as a Partially-resolved / Resolved Group Target (P/RGT) using
a novel spectral frequency technique using DL trained on volumetric Fourier
transforms of swarm formations.
These two
innovations provide a seamless solution to sensor target resolution wherein
the UGT continuously give way to P/RGT detections as swarm range closes.
Optimizing
Linear Assignment for Multi-modal Fusion. Radar and IR sensing are made
complimentary, as the signal and 3-D characteristics of the radar inform
swarm detections and IR detections refine identification / classification.
Both are used to form swarm tracks without ever having to track individual
sUAVs. Associating and tracking at the swarm level allows low visible, dim,
and weakly resolved image detections to be merged into the swarm track
while discarding non-associated noise detections.
This blend of
sensors and swarm signature-based DL and DF has never been tried before but
is well-founded and solves many of the long-standing issues with swarm
tracking.
Approach:
Blend of
sensors and swarm signature-based DL and DF that is
innovative but well-founded and solves many of the long-standing issues
with swarm tracking and that integrates well with
existing DoN Sense-Command-Act architectures.
Anticipated
Phase I Results:
Provide, “a
clear, accurate, and actionable view of the sUAV swarm, improving
classification confidence, and enabling effective decision-making.”
Anticipated Customers:
DoD:
Counter-Small Unmanned Aircraft Systems (C-sUAS) ;
Joint Counter-small Unmanned Aircraft Systems (C-sUAS) Capability
Commercial:
monitoring agricultural drone crop spraying; wildlife surveys; congested
waterways safety; detection of dangerous flocks to aircraft; riot and crowd
management; space debris cloud tracking
i
Korpela, C., & Caton, J.
L. (2015). Swarms in the Third Offset. ed. White, SR, Closer than you
think: The implications of the Third Offset Strategy for the US Army, US
Army Command and General Staff College, Fort Leavenworth, KS, US. Liang, Q &
Xiangsui, W.
ii
UAS Technical Exploitation Lexicon, 2nd Edition, 16 August 2019
iii China:
Digital Pheromones and Wolf Packs, Swarm Intelligence for UAVs; 547
Intelligence Squadron; 16 October 2019
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