SEAS - Systems Effectiveness Analysis Simulation - Space Surveillance Radar Study for US Army Space and Missile Defense Command. Presented at Spring SMC 2007. Approved for Public Release.

1. Colorado Springs Co
718-683-8733
11/23/2014
Space Radar & FCS-BCT
System Effectiveness
Analysis
SMDC Study
Approved for Public Release
09-SMDC-4814 (2 SEPT 07)

2. Agenda
• Study Objectives Overview
– Review of Study Issues, MOE, and Analysis Products
• FCS-BCT Scenario Overview
• Assumptions Update
• SEAS Force Composition
• Space Radar Composition
• ISR Collection Scheduler
• Run Matrix Summary and Changes
• Overview of Results (all study cases)
• Conclusion & Recommendations for Further Study
• Detailed Analysis (Base Case – 100 Runs)
11/23/2014 2

3. Study Issues
• Study Issue 1. What are the impacts on BCT ground effectiveness with
varying priorities of Army FCS BCT information requests?
– Objective 1. [Effectiveness] Can the BCT meet mission vignette objectives, given
varying priorities of information requests?
– Objective 2. [Efficiency]. How long does it take the BCT to achieve mission
vignette objectives given varying priorities of information requests?
– Objective 3. [Lethality] What is the loss exchange ratio of the BCT to Threat while
achieving the mission vignette objective, given varying priorities of information
requests?
– Objective 4. [Survivability] How many BCT systems are lost achieving the
mission vignette objectives, given varying priorities of information requests?
• Study Issue 2. What are the impacts on BCT ground effectiveness with
varying schedule algorithms? (with similar objective.) Varying inputs?
• Study Issue 3. What are the impacts on BCT ground effectiveness with
varying ISR collection agents/platforms? (with similar objective.)
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4. Measure of Effectiveness (MOE)
• (1) Mission accomplishment. Does the BCT achieve the minimum
requirements for mission accomplishment defined by the mission vignettes?
• (2) Time to Complete Mission. What is the time required for the BCT to
achieve the minimum requirements for mission accomplishment defined by
the mission vignettes?
• (3) Loss Exchange Ratio (LOE). What is ratio of Blue to Threat system
losses incurred while the BCT achieves the minimum requirements for
mission accomplishment defined by the mission vignettes?
• (4) System Loss. How many BCT platforms are lost while the BCT achieves
the minimum requirements for mission accomplishment within the
vignettes?
• (5) Detection History. What is the per minute record of sensor-target
detections while BCT achieves the minimum requirements for mission
accomplishment defined by the mission vignettes?
• Make sure scenario, blue TTPs, and threat TTPs provide an opportunity to
measure OPTEMPO.
11/23/2014 4

5. Required Analysis Products
• Developing a simulated scheduler that
– takes pre-planned inputs based on global deck for all ISR
Optimization
systems
– schedules information requests based on constraints from SR
constellation capabilities
– evaluates Army FCS information requests for collection.
• Develop a BCT and below maneuver vignette to support
analysis using information requests as part of the global
collection plan.
• Show impacts of System Response in terms of ground
maneuver measures of effectiveness (MOE).
11/23/2014 5

6. Study Assumptions - Update
• FCS-BCT with organic UAV & UGS Sensors
provide continuous coverage (unrealistic)
• Red Force has comparable force capabilities,
including satellite access
• Communication time delays are constant
(unrealistic)
• UAVs are un-killable (unrealistic)
• SR is the only global ISR collection asset
(unrealistic)
11/23/2014 6

7. SEAS FCS-BCT & SR Scenario
11/23/2014 7

8. Colorado Springs Co
718-683-8733
11/23/2014
SEAS Overview

9. System of Systems
Satellites ● UAVs ● GSR ● Attack Help ● Dismount Units ● Mounted Units ● TBMs
11/23/2014 9

10. Where SEAS “Fits In”
Study Plan
• Scenario
• Data
• Tool(s) Selection
Numerous Runs
SEAS represents an important tool for military utility
analysis with emphasis on space based ISR and
communication systems that provides unique capability
to conduct trade studies and “what if” analyses
Analyze SEAS Results
Find areas or trends
that warrant more
detailed exploration
SEAS
Large Trade Space
Few Runs
Other Models
Extended Air Defense Simulation (EADSIM)
Vector-in-Commander (VIC)
JANUS
Satellite Tool Kit (STK)
Extended Air Defense Testbed (EADTB)
Simulation Location & Attack of Mobile Enemy
Missiles (SLAMEM)
Joint Conflict and Tactical Simulation (JCATS)
“Tends to Cause
and Effect”
Answer
“Cause and Effect By
This Much” Answer
Study Issue
Study Complete Analyze Results

11. SEAS Overview
● SEAS is a study-driven, agent-based, military utility analysis tool
● Physics-based, stochastic, Monte Carlo simulation
● Initially developed to support the military space acquisitions
community
● Used to explore the effects of space and C4ISR system
performance characteristics and concept of operations upon combat
outcomes
● Part of the Air Force Standard Analysis Toolkit (AFSAT)
● Part of the Air Force Space Command M & S Toolkit
● 100% Government-owned software
● Runs on Windows (PC) computers
11/23/2014 11

12. SEAS User Community
● A core team of government, FFRDC, and
SETA contractors guide the development of
SEAS based on the needs of the user
community
● The SEAS user community is quickly
growing and includes several organizations
across government and industry
SPARTA, Inc.
SETA Contractor
SEAS Developer,
Core TEAM SEAS
Member User
Community
0
SMC/TD
Gov’t Sponsor
Model Manager,
TEAM SEAS Lead
TEAM
SEAS
Aerospace
FFRDC
Core TEAM SEAS
Member
Member
RAND
Corporation
Core TEAM SEAS
11/23/2014 12

13. Applications of SEAS
Trade-Off Analysis
Architecture Evaluations
Force Mix/Force Structure Analysis
Wargame Analysis
Major
Combat
Operations
Operations
Other Than
War
Requirements Determination/Analysis
CONOPS Exploration
System Performance Analysis
Homeland
Defense/
Security
Special
Operations
Small Scale
Contingencies
11/23/2014 13

14. Multi-Agent Simulation
of Complex Systems
Yes, Ants can be modeled in SEAS…
Example: SEAS Simulation of Maneuver Behavior (24 Tanks)
Observe
Decide
Act
If no enemy detected:
• Stay in formation
• Move Towards Objective
If enemy detected:
• Task Other Sensors
• Engage it
When fired upon:
• Take Defensive Action
• Task Sensors
• Return Fire or Call Fire
Support
When Operational Picture
Changes
Self Organized Behavior Emerges from Local Rules
Orient
11/23/2014 14

15. SEAS Model Construction
• SEAS provides an N-dimensional “playground” for exploration
SEAS models contain hierarchies
of user-defined agents
Agents contain user-defined
rules (programmable logic)
which define their actions
and behaviors
Agents interact with each other and their
environment through user-defined sensors,
weapons, communications gear (devices)
Outcomes emerge from the
complex interactions of agents
Graphic illustration taken from Multi-Agent Systems, Jacques Ferber, Addison-Wesley, 1999.
Slide adapted from EINSTEIN: An Artificial Life Approach to War, Andy Illachinski, CNA, 2000.
Aggregated forces
(agents)
The SEAS User
FORCE
PLATFORM
Variable Resolution
Individual combatants
(agents)
UNIT
agent
agent
11/23/2014 15

16. SEAS Virtual Battlespace
11/23/2014 16

17. Unit Agent Overview
• Units can own other units (sub-units), platforms and equipment
• There are four key concepts that apply to unit agent actions and
interactions:
– The Local Target List (LTL)
– The Local Orders List (LOL)
– The Target Interaction Range (TIR)
– The Broadcast Interval (BI)
- Commands
- Target
Sightings
- Broadcast
Variables
I’d better
surrender Unit Agent
Target
Day/Night
Weather
Terrain
Personnel
Comm
User Programmed
Behaviors
• Perception
• Awareness
• Knowledge
• Understanding
• Decisions
Broadcast
Variables
_______
_______
_______
Owned
Platforms
Weapons
Sensors
Local
Target List
•TOS 1
•TOS 2
• etc.
Local
Orders List
•Formation Column
•Move Location
• etc.
Moving
Owned
Sub-units
11/23/2014 17

18. The Local Target List
● Each unit maintains a Local Target List (LTL) containing all enemy
platforms/units that it is aware of
● This LTL forms the unit’s sensed tactical picture of the battlefield
● Enemy plaftforms/units enter the LTL through:
─ Detection by onboard sensors
─ Via communications channels
● Enemy targets not updated by one of the two above methods within the unit’s
“Threat_Hold” time are removed from the LTL
● Enemy targets that are killed and BDA'd are also removed from the LTL
UAV
11/23/2014 18

19. The Local Orders List
● Each unit maintains a Local Orders List that contains a
stack of orders for execution
● Orders enter the list from onboard programmed behavior or
flow down from higher echelons via communications
channels
● Locally issued orders take precedence over externally
generated orders
UAV
11/23/2014 19

20. Target Interaction Range
& Broadcast Interval
● Targets outside the unit’s interaction range are not posted on
the LTL even though sensor sightings for that target are
available on the communications channel
● The maximum target range is set by default to 2.5 times the
maximum owned sensor or weapon range whichever is larger,
however the analyst can override this default behavior using
the “Max_Target_Range” parameter for units and platforms
● The agent broadcasts all targets on its LTL at an interval
defined by the “Broadcast_Interval”
Max
Target
Range
AKA Interaction Range
Max
Sensor
Range
Max
Weapon
Range
UAV
11/23/2014 20

21. Colorado Springs Co
718-683-8733
11/23/2014
The FCS BCT
Scenario
Caspian Sea 20 Vignette 1

22. Caspian Sea Strategic Context
11/23/2014 22

23. FCS BCT – A Unit Task Organization
UA
V
HHC BIC NLOS FSB
FCS (Manned):
ICV
C2V
R&SV
MCS
NLOS Mortar
FCS Cannon
FCS MV-Evac
FCS MV-T
FRMV
FCS (Unmanned):
ARV-RSTA
ARV A (L)
ARV-Assault
MULE –
Transport/Retrans
NLOS LS
SUGV
MULE w/ GSTAMIDS
Trucks/Trailers:
HMMWV (C2)
HMMWV (SPT)
HEMTT – LHS
HEMTT – Fueler
HMMWV – CMT
HMMWV - AMB
HEMTT Wrecker
Trailers – PLS
FRS (Includes LHS)
Tank Racks (POL)
Hippos
Camels
SATS Trailers
UAVs:
UAV CL I L/C Units
UAV CL I Aerial Vehicles
UAV CL II L/C Units
UAV CL II Aerial Vehicles
UAV CL III L/C Units
UAV CL III Aerial Vehicle
UAV CL IVa L/C Units
UAV CL IVa Aerial Vehicles
UAV CL IVb L/C Units
Other:
RAH-66 Comanche (or
alternate)
81mm Mortar
Forklift – 10K
Forklift – 4K
E-Q36 Radar
Q64 Radar
AAFARS
HTARS
11/23/2014 23

24. Caspian Sea 20 – Vignette Overview
11/23/2014 24

25. SEAS FCS-BCT Scenario Forces
11/23/2014 25

26. Space Radar
• Built-in Sat files
– SR1-SR12
– Sensor "BluIMINT_narrow“
• Min_Range 0
• Break_Range 2600
• Max_Range 2600
• Az_Width 1
• El_Min -.50
• El_Max .50
• TLE 10
– Comm "BlueSatRadio_Tr"
– Comm "BlueSatRadio_Rc"
11/23/2014 26

27. ISR Collection Scheduler
• Modeled in TPL as a
Scheduler vehicle
• Tasks are read from
external file
• Read into an array through
TPL
• Prioritized based upon user
priority variable
• Predetermined task
duration
• If no active task is in the
queue, then SRs look at
default locs
• Broadcasts LookLoc to the
SRs
11/23/2014 27

28. Colorado Springs Co
718-683-8733
11/23/2014
Comparative Results
SMDS Study

29. SMDC Study
Test Cases
- Alt 2 and Alt 3 (no Sensor Fusion) were not run
- Exc 2 (Limited Assuredness) was run for 50%, 10%, and 1% Assuredness
- Exc 3 (Partial Constellation) was run for 6 radars, 3 radars, and 1 radar
- An Additional Case (Exc 4) was run with No Space Radar
11/23/2014 29

30. Box-Plot Comparison - MOU
Blue Vehicles Lost & Battle Duration
No UAV/
UGS
No Space
Radar
Base Case
11/23/2014 30

31. SMDC Study Comparative Results
MOU – Avg Time to Withdraw or Defeat
11/23/2014 31

32. Colorado Springs Co
718-683-8733
11/23/2014
Conclusions &
Recommendations
For Further Study

33. Conclusions
• The combination of FCS-BCT organic sensors and
Space Radar generate a ISR collection dynamic that
increase system effectiveness.
• The combination of FCS-BCT organic sensors and
Space Radar “minimize” blue casualties and battle
duration. Neither alone are as effective.
• There are sensor interactions that cannot be
explained by the current analysis. These require
further investigation.
11/23/2014 33

34. Recommendations for Further Study
• Variable communication delays – sensor
information latency
• Stochastic UAV survivability modeled
• Non-continuous FCS-BCT UAV coverage
• Global UAV ISR collection assets (e.g., Warrior)
• Varying schedule algorithms – more complexity
11/23/2014 34