UAV Payload Trades Analysis and Effects Based Selection
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Transcript of UAV Payload Trades Analysis and Effects Based Selection
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7/28/2019 UAV Payload Trades Analysis and Effects Based Selection
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October 29th, 2007
Gregory GertenAnalytical Graphics Inc.
UAV payload trades, analysis and
effects based selection
This Presentation isApproved for Public
Release
UNCLASSIFIED
Derived from:
Internet sources
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Problem
UAV proliferation and sensor payload types are increasing
Size, weight and power (SWAP) are crucial to small UAVs
Interdependencies exist between different sensor systems and
communication and navigation needs
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UNCLASSIFIED
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Agenda
UAV modeling
Flight dynamics
Ground control
Environment/Terrain
Current use / success
Summary
System modeling
Communication
Navigation
Sensors
Effects Based Selection
BAMS
Boarder Patrol
Campaign analysis - MCOs
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UNCLASSIFIED
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Flight Dynamics
6DOF route creation
Platform specific models
Take-off, landing, cruise
Circles, racetracks, figure-8s...
Route optimization
Minimize red/blue threats
Maximize sensor coverage/effects
Optimize profile to maximize time on target
Inter/ra-object geometry calculations Coordinate transformations
Off axis antenna translations / effects
Range, vectors, angles, magnitudes, etc.
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Ground Control
Transmitters (Tx)
Platform Tx and antennas
Controller Tx and antennas
Red/blue Tx (EA) and antennas
Receivers (Rx) Platform Rx and antennas
Controller Rx and antennas
Red/blue Rx (ES) and antennas
Repeater links Network operations
Link Budget analysis
Dynamic networks
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Environmental effects
Accuracy errors due to the environmentTerrain (DTED)
Weather models
IonosphereObscura / Multipath
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Analysis outputs
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RF Coverage 2D/3D
Tip-offs and visual cues
Link budget reports and graphs
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Communication Systems - Tx
Modeling a transmitter
Frequency, Power, Data Rate, Modulation
Antenna, Polarization, Gains
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Communication Systems - Rx
Modeling a Receiver Frequency
Bandwidth
Antenna
Polarization
Gains
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Communication Environment
Taking environment into account Terrain . Urban, Masking
Rain, Cloud, and Fog
Gaseous Absorption
Tropospheric, Plug-ins
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Navigation
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UAVs require Navigation Auto-pilot and situational awareness
Precise timing and reference
Sensor and weapon hand-off
UAVs are closer to the threats Less range and body masking
Civilian vs military receivers
Long durations beyond FLOT
Navwar effects everyone Blue EA assets may effect Blue EP
Need to ensure system interoperability
GPS to UAVs as Oxygen to humans
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Sensors
Plethora of sensors to choose Imagery - SAR, FLIR, EO, IR, etc.
Signals Entire bandwidth to consider
Geolocation methods TDoA, FDoA, AoA
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Sensor dependencies Size, weight and power
Communication and navigation demands
Processing (On/Off board) Automation?
Fusion process / capability Fusion with other on-board sensors
Fusion across the battle-space
Boiled down nuggets of value
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BAMS (Maritime Surveillance)
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Multiple object handling
Land, air, sea, and space
Sensors, comms, navigation, radar
Red or blue targets / structures
Queuing and targeting
In-view analysis and reporting
Time on target reporting
Targeting collection analysis
Situational Awareness Data exchange and visualization
Change detection and tip-offs
Quick look analysis and reporting
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Boarder Patrol
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Coverage analysis
Sensors field of view / targeting
Revisit time / duration covered
Multiple coverage / platforms
Assured Communications
Terrain / obscura effects
Jamming / noise effects
Tx / Rx link budget
Multiple UAS Sensor / Target mixes
Airspace deconfliction
Network Centric data exchange
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Campaign analysis - MCOs
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Many-on-Many analysis
Performance attribute control
Engagement level measures
Full force on force outcomes
Collaborative approach
DIS/HLA data exchange
Components to a large system
Ingest and output real-time data
Multiple UAS Sensor / Target mixes
Airspace deconfliction
Network Centric data exchange
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Canadian Forces Aerospace Warfare Center
Outcome:
Problem:
Solution: Model different platform (manned,unmanned & satellites) and sensorcombinations in different missions andanalyze surveillance results.
What platform and sensor types will
best meet system requirements?
System platform and sensor options analysisusing a single low risk COTS product.
Full surveillance system modeling and
analysis using a low risk COTS product.
JUSTAS Program(Joint Unmanned Surveillance Target Acquisition System)
Concepts Analysis
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T&E Planning, Analysis andVisualization
Outcome:
Problem:
Solution: STK based Mission Planning Labre-creates any mission to buildfeasibility studies and costanalysis quickly and accurately
Lengthy feasibility studies andcosts associated with them BEFORE contract award
$1M + contract awarded on
the spot
Turn complex concepts into feasible options &
secure FUNDS in hours instead of months
NASA Wallops Island Flight Facility
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Test and Evaluation Safety
Outcome:
Problem:
Solution: Full 3D Analysis environment.Explore What-ifs? in faster than real-time. React to custom requirementchanges on the fly.
Major UAV ISTAR Program:Operational Analysis and TrialPlanning. Effective de-riskingrequired prior to live trials.
Significant Cost and Time savings in designingT&E plans with the customer.
AGI technology used for operational analysis,
T&E planning, and post-trial analysis.
UK JUEP: Thales Aerospace Division
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Real-time System
Restricted Air Space Analysis
Airfield visualization (DAFIF)
Coverage Analysis
Terrain and imagery
Communications Analysis
Aircraft 3D Models
Tactical Decision Aids
Real-time Trials withSOCOM/AFSOC
Real-time data can be analyzed as it happens
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Summary
Ensure
System level -
Effects based
acquisition
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Requirement validation and analysis
Sensor trades and collection optimization
Perform effects based selection
Program collaboration and risk reduction
Leverage efforts across community
Performance Attributes
You can do it!
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Hardware in-the-loop Simulation
Transfers the M&S scenario data/inputs into actualhardware to simulate test conditions and collect thisdata to determine system performance in real-time
Perform M&S
Bound theproblem space
Create testscenarios
Transfer testparameters to thehardware
Hardware
Import simulation parameters
Create signals (power,frequency, phasing, etc.)
Combine signals and pass tohardware under test
Send truth data to simulation
Quick look Visualization
Import data feeds
TruthTest Hardware
Calculate RT differences
Visualize entire scenarioincluding environment
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