Combat Simulation to Support the Conceptual Design of Equipment
for the Soldier System
Vikram Mittal
1a
, Graham Webb
2
, Jackson Steiner
2
, Luke Shriver
2
and Sierra Butcher
2
1
Department of Systems Engineering, United States Military Academy, West Point, U.S.A.
2
Army Cyber Institute, West Point, U.S.A.
Keywords: Combat Modelling, Cyber Capabilities, Soldier Systems.
Abstract: Simulation will play an increasingly important role in designing future equipment for soldiers. The complex
operational environment necessitates that the soldier be treated as a system. A soldier system can be defined
as a soldier using equipment to complete a mission. Though it is often difficult to capture the mission aspect
of the system, constructive combat simulation provides a technique for testing out new equipment on a soldier
early in the system design lifecycle. Though combat simulations have historically been used primarily for
training purposes, they can be readily modified for analysis of new military capabilities. Additionally, these
simulations can be modified to reflect the changes in physical and cognitive load associated with these new
capabilities. This paper outlines a methodology for using combat simulation to perform analysis of new
capabilities for the soldier system. A case study is then presented to perform a trade space analysis on different
tactical-cyber capabilities given to dismounted soldiers. Using the Infantry Warrior Simulation (IWARS), the
case study quantified changes in soldier survivability and lethality with the addition of new technologies.
1 INTRODUCTION
Ground combat will always play a decisive role in
future conflicts. And as mission sets continue to
become more complex, so must the soldier. The
soldier is no longer a person with a helmet and a gun
standing on a volley line, shooting at an enemy.
Rather, the soldier is part of a complex system, where
they use an array of cutting-edge technology to
maintain a tactical advantage in a combat scenario.
As new technology gets introduced into this
soldier system, systems level analysis is required to
ensure that the technology provides the soldier with
the required capabilities without producing negative
consequences. This analysis requires the ability to
assess the usage of the new equipment in a relevant
operational environment. Combat simulation
provides the ability to perform this analysis early in
the conceptual phase, allowing for the determination
of design requirements for new equipment. Several
challenges exist with this approach, especially that
these simulation packages are typically developed for
training purposes and do not readily allow for the
integration of new equipment.
a
https://orcid.org/0000-0003-2485-2366
This paper presents a methodology to use combat
simulation to analyse changes to the soldier system.
It then presents a case study that evaluates different
tactical-cyber equipment. This analysis includes
accounting for change in physical and cognitive
overloading associated with these different
capabilities.
2 CHALLENGES OF DESIGNING
MILITARY EQUIPMENT
2.1 The Soldier System
In ancient armies, soldiers were given uniforms,
protective equipment, weapons, and sustenance. As
technologies advanced for one individual component,
it was simply swapped out, such as the iron age
resulting in the weapons changing from bronze.
However, the equipment set currently carried by
soldiers is significantly more advanced, creating a
complex system with numerous interrelationships. As
240
Mittal, V., Webb, G., Steiner, J., Shriver, L. and Butcher, S.
Combat Simulation to Support the Conceptual Design of Equipment for the Soldier System.
DOI: 10.5220/0009883602400247
In Proceedings of the 10th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2020), pages 240-247
ISBN: 978-989-758-444-2
Copyright
c
2020 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
such, the design of military equipment requires a
systems-level design approach.
The systems architecture for the soldier-system,
as shown in Figure 1, consists of three components:
the soldier, their equipment, and the mission to be
completed. This architecture leverages the Soldier
System Enterprise Architecture by the Natick Soldier
Research, Development, and Engineering Center
(McDonnell, 2015). The equipment alone is just a set
of inanimate objects; however, when coupled with a
soldier, the soldier and equipment form a relationship
that allows them to complete a mission. A systems
analysis requires understanding the internal
properties of each component and the interactions
between components. These interactions create
emergent effects that must be accounted for to fully
characterize soldier performance.
Figure 1: The soldier system defined as a soldier using their
equipment to perform a mission.
2.2 System Level Analysis
Although the soldier system, as depicted in Figure 1,
appears somewhat straightforward, it is difficult to
actually understand all the different interactions and
relationships related to the addition of a new piece of
equipment. The interaction between the new piece of
equipment and the user, indicated by the overlap in
the Venn Diagram in Figure 1, can be understood
through a standard usability assessment. However,
the interaction between the soldier using the
equipment to perform the mission, indicated by the
plus sign in Figure 1, is difficult to analyze. This
analysis becomes exceedingly difficult when the new
equipment is still in the conceptual phase.
For example, suppose that the Army is
considering replacing their existing body armor with
a slightly heavier armor material that provides
substantially more protection. However, in an urban
environment, even a small increase in weight will
result in the soldier moving significantly slower. In
turn, the enemy soldiers can more accurately shoot
the slower moving soldier, allowing them to shoot the
soldier in an unarmored location, resulting in an
overall decrease in survivability. This analysis would
be difficult to perform without actually developing
the body armor and testing it in an operational
environment. Even if the armor is developed, no
commander would agree to having their soldiers
carrying unproven equipment in combat.
2.3 Physical and Cognitive Loading
The largest negative emergent property from the
addition of new equipment is related to physical and
cognitive loading. Ideally, soldiers would be given
every possible capability to aid in destroying their
enemy. However, soldiers are already carrying over
100 lb of equipment consisting of weapons, armor,
ammunition, food, water, and electronics (Mittal,
2019). Since soldiers are already carrying close to
their maximum load, any additional equipment will
displace equipment currently carried. If this
displacement comes from batteries, water, or food,
the maximum duration of the mission must decrease.
In addition to carrying a large amount of
equipment, the soldiers must be able to operate it. The
new electronics on a soldier includes radios,
navigation tools, computers, minesweepers, and
robots. Soldiers are expected to operate all of this
equipment while “keeping their head on a swivel” and
“scanning their sector.” Modern combat in urban
environments, where soldiers must detect and identify
enemies in a crowd, imposes a significant cognitive
load on soldiers. As such, any new equipment must
not significantly increase the cognitive loading on the
soldier (Shanker & Richtel, 2011).
3 COMBAT MODELING
3.1 Overview of Combat Models
Combat simulation provides the capacity to test new
equipment in an operational setting, albeit, both the
equipment and operational setting are simulated
(Washburn & Kress, 2009). The military divides
combat simulation into three categories—live,
virtual, and constructive. Live simulations use real
soldiers with real equipment in a simulated
environment, such as a training site. Virtual
simulations involve real soldiers using virtual
equipment in a virtual environment, similar to a video
game. Constructive simulations employ virtual
soldiers using virtual equipment in a virtual
environment (Hodson, 2017).
Each type of simulation can play a role in
developing, evaluating, and testing requirements at
various stages in the system lifecycle. Live and virtual
Combat Simulation to Support the Conceptual Design of Equipment for the Soldier System
241
simulations require that the system already be
prototyped. As such, these simulations aid in system
validation and assessing the overall system usability.
Meanwhile, constructive simulations allow for
modelling a virtual soldier using virtual equipment in
a simulated environment. Since the soldiers are
virtual, their capabilities can be readily augmented to
reflect the addition of new equipment even if the
equipment has not been designed or built. Therefore,
constructive simulations are inherently useful for
systems still in their conceptual phase, such as those
used in this analysis.
Indeed, constructive simulation is used for
equipment design in a number of industries to include
medical devices, automotive, and consumer products
(INCOSE, 2015). Additionally, constructive
simulation is used for larger defense applications.
However, its usage has been fairly limited for analysis
of the soldier system (Hill & Miller, 2017).
3.2 Limits of Modelling New
Technologies
Though a range of constructive combat modeling
programs are available, most of them are not intended
for analysis; rather they are developed for training
(Tolk, 2012). In particular, these software packages
are used as part of larger live training events to
simulate events occurring elsewhere in the battlefield.
For example, a brigade will be performing a mission
at the National Training Center as part of a larger
overall division-level mission. The other brigades on
the battlefield are simulated with the results of the
simulation influencing the mission of the real unit.
Since these simulation packages are not designed
for analysis, they do not readily allow for the addition
of new equipment (Tolk, 2012). For example, many
of these simulation packages would not readily have
the capacity to model novel technologies such as an
exoskeleton or adaptive camouflage patterns.
Additionally, the methodologies that underly the
simulations are based on fundamental military
doctrine where soldiers and units shoot, move, and
communicate. The addition of new technology can
substantially change these methodologies. For
example, shooting algorithms rely on detecting a
target, identifying that the target is an enemy,
orienting towards the target, shooting the target,
determining where the bullet strikes the target, and
then determining the damage done from the hit. The
addition of a threat recognition system would change
this process because the soldier would no longer need
to identify the target as an enemy; rather, the new
system would automate that process for the soldier.
4 METHODOLOGY
Figure 2 displays a methodology for using combat
simulation to analyse different performance metrics
related to future military technology. This process is
applicable to all military technology; however, it is
tailored to those technologies that are still in the
conceptual phase that will result in substantial
changes in how soldiers operate.
Similar to any type of systems analysis, the first
phase is to define the problem. This phase starts by
defining a set of relevant missions for a given soldier.
These mission sets can be found in military doctrine.
These missions are then modelled in a simulation
package to provide a baseline set of performance
metrics for this analysis. These simulations can
achieve some level of validation through comparison
to performance data from training sites.
The performance metrics from the systems-level
analysis provide insight into problems that need to be
solved. Typically, these metrics are survivability and
lethality, with the goal that a new technology
increases the ability of a soldier to kill their enemy
and/or decrease their likelihood of being killed by the
enemy (Washburn & Kress, 2009). Another common
metric is mission success rates, which is the
percentage of time that the soldiers can complete their
mission.
The second step of the process is to identify a
technology that will solve the problem identified in
the first step by improving the relevant performance
metric. The researcher then needs to understand how
the new technology will be implemented into the
combat scenario. They also need to determine how it
will change the individual soldier’s physical and
cognitive loading, since any new equipment will
result in changes in these parameters. Finally, it is
necessary to identify how the technology will change
a soldier’s skills. For example, the new technology
could reduce target acquisition time, make them shoot
more accurately, move faster, or have an increased
knowledge state about the battlefield.
The third step in the process is to perform the
operational analysis. The operational analysis
requires modifying the combat simulation to reflect
the new technology. For example, the soldier may
change their actions based on the information
provided by a new piece of equipment. In another
case, the soldier may simply execute their mission
faster because they are carrying a lighter load.
SIMULTECH 2020 - 10th International Conference on Simulation and Modeling Methodologies, Technologies and Applications
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Figure 2: Methodology for performing a soldier system
analysis using combat simulation.
5 CASE STUDY: TACTICAL
CYBER CAPABILITIES
The methodology presented in Section 4 was
specifically designed to support a study on tactical
cyber capabilities for the United States Army. These
capabilities are expected to play a key role in future
small unit operations.
5.1 Define Problem
5.1.1 Base Scenario
Though the full span of Army mission sets is vast, this
analysis is limited to those performed by small
infantry units at the squad or platoon level. FM 3-
21.8: The Rifle Infantry Platoon and Squad gives four
common mission types performed by such a unit
(Headquarters, Department of the Army, 2016).
These mission types include:
Raid: fast kinetic movement into an area to
engage a known enemy.
Ambush: setting a stationary trap for an enemy,
then engaging when they are vulnerable.
Combat patrol: movement through an area to find
and engage enemy targets.
Destroy bunker: engaging a fortified enemy
position.
These four missions become more complex if they
are performed in an urban environment. First, enemy
targets are harder to detect and identify because they
are blended in with civilian non-combatants.
Additionally, urban combat involves multiple levels
(i.e., underground sewage systems, ground level,
multiple story buildings). Moreover, the buildings in
urban environments provide opportunities for cover
and concealment for both forces; meanwhile, the
buildings limit movement down canalized pathways.
5.1.2 Infantry Warrior Simulation
The Infantry Warrior Simulation (IWARS) is a
constructive, force-on-force, combat simulation that
focuses on small-unit operations. The primary
IWARS simulation objects are intelligent agents that
are semi-autonomous, which allows for realistic
modeling of soldier and unit behaviors. The
methodologies that underly IWARS are stochastic,
such that the simulation must be run numerous times
to get a range of output parameters to include
measures of survivability and lethality (Samaloty,
Schleper, Fawkes, & Muscietta, 2007).
IWARS was selected for this analysis because it
models individual soldiers conducting squad to
platoon size operations. Tactical cyber capabilities
are focused on units at this echelon. Other more
common simulation platforms aggregate individual
soldiers into units, not allowing for an accurate
modeling of soldiers with augmented capabilities
(Page, 2016).
An IWARS model is developed by placing blue
(friendly), red (enemy), and green (civilian) forces
onto a map. Each agent is assigned movement paths,
behaviors, and equipment, which then allows them to
perform a set of tasks that constitute their mission.
The behaviors can get very complex and are often
based on the actions of other agents in the scenario.
The performance of the soldier and their equipment is
captured through a parameterized database that can be
edited to reflect new capabilities. Screenshots of
IWARS is shown in Figure 3. The top image shows
the top-down view of a blue unit moving into a town
to clear the town of red forces. The bottom image
displays the 3D image for the agents shooting at the
intersection in the center of the right image.
The four missions were modeled in an urban
environment using IWARS. In all four cases, a small
unit of blue soldiers is conducting an operation
against ten red soldiers. The raid mission has a
platoon of blue forces sweeping into the town from
the north to find and kill the red forces that are
entrenched in the buildings. The ambush mission has
a blue force establishing an L-shaped ambush at a
crossroad in the center of the town. The combat patrol
has a blue force being ambushed by red forces and
then counter-attacking the red forces. The bunker
mission has the blue forces moving into the town, get
pinned down by a bunker, and then executing the
battle drill to destroy the bunker.
Define
Problem
Determine mission set
Build base model
Evaluate current performance metrics
Solution
Design
Identify method to improve performance metrics
Determine change in physical and cognitive load
Determine change in soldier skills
Operational
Analysis
Modify scenario to reflect new technology
Estimate the probability of technology working
Evaluate change in performance metrics
Combat Simulation to Support the Conceptual Design of Equipment for the Soldier System
243
Figure 3: Screenshots of IWARS. Top-down view of raid
scenario showing blue forces moving south into a town
(top). Three-dimensional view of friendly and enemy
soldiers at the intersection in center of town (bottom).
5.1.3 Current Performance Metrics
The metrics of concern for this analysis are
survivability and lethality. These two metrics are
typically used qualitatively to describe the effect of
adding new equipment into the soldier system;
however, with combat modelling, these metrics can
be defined quantitatively. The survivability metric is
defined to be the percentage of blue forces (i.e.,
friendly soldiers) that survive a mission, and the
lethality metric is set as the percentage of red forces
(i.e., enemy soldiers) killed during a mission.
Table 1 displays the survivability and lethality
metrics for the four mission sets. Each scenario was
run 100 times to provide a desired relative precision
of 5 percent. Table 1 indicates the following:
Raid: The blue forces outnumber the red forces
by a factor of 3 allowing them to overwhelm the
red forces. However, the blue forces incur a high
death toll because the red force is in a defensive,
fortified position.
Ambush: The red forces have the element of
surprise, resulting in low survivability and
lethality metrics for the blue forces.
Combat patrol: The combat patrol has equal
numbers of red and blue forces on the move, with
neither side having a solid defensive posture; as
such, both groups impose similar casualties.
Destroy bunker: The destroy bunker mission has
a fairly high blue casualty rate, though the red
casualty rate is higher.
For all four scenarios, the survivability metric can
be significantly increased with the overall goal of
achieving a score of 100, which indicates that no
soldiers were killed during the mission. The results
indicate that across the scenarios, approximately half
of the blue forces die in each scenario. One method of
increasing the blue survivability is to increase their
lethality. If the blue forces can kill the red forces
faster, the red forces will impose less damage on the
blue forces. The outputs from the models indicate that
there is an opportunity to increase blue force lethality.
Table 1: Survivability and lethality metric scores for each
of the four baseline combat scenarios.
Survivability Lethality
Mission Type Average St. Dev Average St. Dev
Raid 56.6 8.0 88.3 8.0
Ambush 34.4 13.9 52.2 14.9
Combat Patrol 45.0 13.2 56.7 20.9
Destroy Bunker 44.2 11.6 76.8 14.0
5.2 Solution Design
5.2.1 Tactical Cyber Capabilities
The rapid growth of the consumer electronics market
provides numerous opportunities for technologies
that can increase a soldier’s lethality, and hence
survivability. Advances in fields such as artificial
intelligence, augmented reality, cloud-computing,
and micro-electronics can translate into game-
changing military technology (Wilson, 2016).
Meanwhile, enemy soldiers are carrying more
electronics that are vulnerable to a cyber-attack
(Almohammad & Speckhard, 2017). This
combination of events creates the potential for a new
set of cyber weaponry that will provide soldiers a
tactical edge, potentially increasing their survivability
and lethality (Porche, et al., 2018).
Though cyber weaponry is typically considered a
strategic level asset, many offensive cyber
capabilities have trickled down to the tactical, small-
unit level (Brantly & Collins, 2018). Similar to
strategic cyber weaponry, tactical cyber weaponry
allows dismounted soldiers to detect and exploit an
enemy’s communication channels. Since the full
range of possible tactical-cyber-attacks is very broad,
this study limits itself to looking at four types of
tactical cyber-attacks. These four tactical cyber-
SIMULTECH 2020 - 10th International Conference on Simulation and Modeling Methodologies, Technologies and Applications
244
attacks were selected because they encompass a broad
range of different capabilities. Additionally, they
represent capabilities that are already fielded or under
development.
The first tactical cyber-attack is a localized attack
on the electric grid. Individual buildings are
connected to the larger electric grid with numerous
communication pathways (Congressional Research
Service, 2018). These communication channels can
be exploited to deny electric services to a building.
This would disrupt the enemy by throwing them into
a set of disarray. Additionally, if the attack is at night,
the enemy would lose the ability to use lights.
Another tactical cyber-attack involves the use of
radio frequency (RF) triangulation. If friendly forces
know the radio frequencies associated with an enemy
combatant, they can triangulate and track its position
(Liu, Zhang, Su, Li, & Xu, 2013). This type of
exploitation allows the soldier to observe the enemy
beyond line of sight while also getting positive
identification through their radio signals.
A third tactical cyber-attack is communication
denial, also known as jamming. Since communication
is done simply through sending radio signals through
the air, the signal can be lost if the noise thresholds
are increased. This can be achieved by simply
pushing a large amount of radio frequency noise into
the environment. This type of tactical cyber-attack
does not allow the enemy to synchronize efforts.
The fourth tactical cyber-attack is communication
intercepting. If the enemy forces are communicating
over an unencrypted network or if the encryption key
is known, friendly forces can intercept the enemys
communication, hence gaining new intelligence. This
information allows friendly forces to observe enemy
forces from a further range.
5.2.2 Physical and Cognitive Load
The different tactical cyber capabilities will impose a
different amount of physical and cognitive loading on
soldiers. To analyze the different physical loadings, it
is useful to break the capabilities into two categories:
active and passive (Shirey, 2000). Active implies that
signals are being transmitted to disrupt the enemy’s
communication channels. Passive implies that the
system is simply ingesting the enemy’s
communication channels and processing the results.
The localized grid attack and communication
denial capabilities require active devices. These
devices would impose a higher physical load on the
soldier since the system must transmit signals, which
is power intensive. A simple radio requires 10 W of
power, associated to 1 lb of batteries for 10 hours of
operation. Jamming devices can require 100 W of
power, requiring 1 lb of batteries for each hour of
operation (Leemans & Mittal, 2018).
Passive devices would be required for RF
localization and communication intercept. These
devices require significantly less power since they are
simply collecting radio signals. However, upon
collecting the signals, the results must be analyzed
which does require power. A normal computer for
analyzing these results would require approximately
10 W of power, although triangulating a position
would require significantly less power than
decrypting and analyzing communication data
(Leemans & Mittal, 2018). Though there are less heat
concerns for passive devices, they often require bulky
antennae that can operate at multiple wavelengths.
The cognitive load on a soldier from the devices
would be based on how much human input is required
for the capability. At the low end, communication
denial would require minimal human input outside of
turning on the device. RF localization imposes a
slight cognitive loading on the soldier since they are
provided with additional information, although the
use of Augmented Reality can reduce this cognitive
load. A localized grid attack would require
significantly more human input since the soldier
would be required to work around the different
safeguards. Meanwhile, communication intercept
would incur a large cognitive load on the soldier since
they must make sense of whatever information they
receive and process what is important.
5.3 Operational Analysis
5.3.1 Incorporation of Tactical Cyber
Each model was modified to reflect the addition of
each of the four tactical cyber capabilities. Since
IWARS does not inherently have these capabilities
built in, each capability had to be incorporated
through changing certain model attributes and soldier
behaviors. The localized grid attack capability was
incorporated by increasing the confusion and
acquisition times for red agents inside the relevant
structures. The RF localization capability was
modeled by continuously giving the blue agents the
knowledge of red force locations. IWARS provides
the capability for communication denial through
decreasing the probability of a successful
communication transmission. The communication
intercept capability was modeled by changing the
blue forces mission to reflect intelligence about
enemy plans.
Combat Simulation to Support the Conceptual Design of Equipment for the Soldier System
245
The physical load associated with the devices can
be integrated into the simulations by increasing the
overall load and reducing the speed associated with
soldier movement. Additionally, the cognitive load
can be integrated by slowing reaction times, reducing
their field of view, and including head-down time.
5.3.2 Scenario Results
Each of the four scenarios were rerun with the
incorporation of each of the four different tactical
cyber capabilities. Table 2 displays the survivability
score for each run, and Table 3 displays the change in
lethality score. The items in bold indicate a
substantial improvement from the baseline.
The results indicate that there was only a marginal
increase in the lethality metric in most of the mission
sets. For the most part, the simulations represent
doctrinal missions consisting of battle drills that are
intended to make the blue forces fairly effective at
killing the red forces. As such, the new capabilities
logically only provide marginal benefit in regard to
the number of red soldiers killed. However, further
analysis found that the blue forces were able to kill
the red forces earlier in the scenario.
As such, each of the new capabilities provided a
significant increase in survivability in at least one of
the mission sets. The RF localization capability
increases blue survivability for the raid and combat
patrol, by allowing the blue forces to avoid traps and
“fatal funnels” set by the red forces. Other
capabilities, such as communication denial provided
an increase in survivability by putting the red forces
into disarray and hindering their ability to coordinate
an attack. The communication intercept and localized
grid attacks also provide an increase in survivability;
however, these increases are limited.
Table 2: Survivability metric for each of the 4 combat
scenarios for the four different tactical cyber capabilities
(italicized number is the +/- 95% confidence interval).
Mission
Type
Base
Grid
Attack
RF
Local.
Comm
Denial
Comm
Int.
Raid
56.6 55.5 82.6 67.9 72.9
±1.6 ±2.1 ±1.0 ±0.6 ±0.8
Ambush
34.4 30.7 56.1 38.7 48.7
±2.7 ±2.7 ±3.1 ±2.8 ±3.0
Combat
Patrol
45.0 42.0 73.4 67.2 71.2
±2.6 ±2.6 ±2.6 ±2.5 ±2.6
Destroy
Bunker
44.2 46.0 45.4 55.4 49.2
±2.3 ±1.9 ±2.2 ±1.7 ±2.2
Table 3: Lethality metric for each of the 4 combat scenarios
for the four different tactical cyber capabilities (italicized
number is the +/- 95% confidence interval).
Mission
Type
Base
Grid
Attack
RF
Local.
Comm
Denial
Comm
Int.
Raid
88.3 82.8 97.3 88.8 88.7
±1.6
±1.7 ±1.6 ±1.6 ±1.6
Ambush
52.2 57.8 53.1 56.2 57.8
±2.9
±2.7 ±3.1 ±2.8 ±3.0
Combat
Patrol
56.7 56.9 58.0 57.0 56.1
±4.1
±4.4 ±4.3 ±3.8 ±4.3
Destroy
Bunker
76.8 78.7 77.8 81.3 77.4
±2.7
±2.0 ±2.5 ±2.2 ±2.3
5.3.3 Validation of Results
Since the technology for the different cyber
capabilities are not available, the models cannot be
validated through real-world comparison. The base
scenarios, however, were compared to performance
reports for small-unit exercises in a similar training
site; the model results aligned well with these reports.
The different models were also validated by
consulting with infantry and signal officers who
served as subject matter experts that could evaluate
the scenarios and determine if the model results align
with their expectations. The infantry officers agreed
that based on their best judgement, they would expect
comparable changes in red and blue force casualties
to what the simulation found.
5.4 Case Study Conclusions
The four scenarios of interest—the raid, ambush,
combat patrol, and destroy a bunker—currently incur
a high casualty rate for the infantry squad. However,
the combat models indicate that the inclusion of new
tactical cyber capabilities will allow the unit to take
less casualties over the mission.
The grid attack capability provided a statistically
insignificant increase in survivability across the
mission sets. Though the enemies were less
organized, the increase in cognitive loading on the
soldiers offset this benefit. The RF localization
capability offered the largest increase in survivability
in three of the four mission sets. The benefit for RF
localization is that the system required the least
change in physical and cognitive loading. The
communication denial system and communication
intercept systems both provided benefits in certain
mission sets. However, the communication denial
system imposed a large physical burden on the soldier
due to the weight of the system, and the
SIMULTECH 2020 - 10th International Conference on Simulation and Modeling Methodologies, Technologies and Applications
246
communication intercept system imposed a large
cognitive load on the soldier.
The results of this study indicate that if the Army
can only adopt one tactical cyber capability for
fielding to its infantrymen, they should proceed with
an RF localization capability. Additionally, the
simulations indicate the importance of not increasing
a soldier’s physical and cognitive load, which can
potentially offset any benefit from a new capability.
6 CONCLUSIONS
As the complexity of the world increases, militaries
are required to perform more complex operations. In
doing so, the soldier system, defined as the soldier,
equipment, and their mission sets, increases in
complexity. Therefore, the addition of new
equipment onto a soldier requires a systems level
analysis that involves having soldiers using the
equipment in an operational environment. Since this
is not feasible for equipment, especially in the
conceptual design phase, simulation will play a
crucial role in this analysis.
Several combat simulations are available, though
many have historically been used for training
purposes; regardless, they can be modified to account
for new soldier capabilities. This paper outlines a
methodology for performing such an analysis.
The paper then presented a case study that
performs a trade space analysis on different tactical-
cyber capabilities given to dismounted soldiers. This
analysis used the combat simulation package IWARS
to compare changes in soldier performance with the
additional of different new tactical cyber capabilities.
This methodology was developed primarily to
perform the analysis on tactical cyber trade-space
presented in the case study. Future works will look at
expanding this methodology to other tactical
equipment including biomechanical enhancements,
future weapons, and autonomous systems.
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