Assessment of Ship Air Defence Performance
by Modelling and Simulation
Stephen J. Chapman and Kurt K. Benke
BAE SYSTEMS Australia
677 Victoria St
ABBOTSFORD VIC 3067
Keywords: Ship Air Defence Modelling, System Integration, Probability of Survival
ABSTRACT: Ship air defence performance is characterised by a complex interaction between the platform, detection
systems, airborne threats, countermeasures and environment. Air defence modelling is described in the context of
performance assessment of various system configurations with the objective of improving the probability of ship survival.
This paper describes a PC-based Ship Air Defence Model (SADM) developed by BAE SYSTEMS Australia, and used
within BAE SYSTEMS Australia and the Electronic Warfare Division of DSTO. The model includes soft-kill modelling
with active decoys, chaff, and jammers; hard-kill modelling with missiles, guns, and fire-control systems; and a
Command and Control System to assign targets and coordinate soft-kill and hard-kill responses. SADM also models the
interaction between the hard-kill and soft-kill systems deployed on the ship. Typical results are presented and it is shown
how the model can be used to perform hard-kill/soft-kill tradeoffs during the ship design process.
1. Performance Modelling
1.1
Introduction
Ship air defence modelling plays an important role in
the development of modern maritime tactics. A primary
concern in joint air/sea operations is the protection and
optimal deployment of expensive surface assets. The
increasing sophistication of threats, such as anti-ship
cruise missiles, suggests room for continuing model
development in order to identify the appropriate ship
fits, tactics, and countermeasures.
Prediction of ship self-defence performance is a
necessary input for the ongoing process of planning,
budgeting and weapons-fit evaluation for new ship
designs. Changing the configuration of existing weapon
systems and countermeasures also requires assessment
of potential performance under various combat
scenarios. Modelling and simulation represent a costeffective approach to the problem of performance
prediction and tactics assessment under a range of
possible conditions.
1.2
Motivations for Modelling
Assessment of ship air defence performance provides
a base-line for hard-kill/soft-kill options associated with
ship combat systems, quantifies performance and
identifies key system elements responsible, and aids in
the integration and optimisation of these elements [1].
Furthermore, the trade-off between performance and
cost can be investigated in a systematic and quantitative
manner.
The issue of system integration is covered by finding
the best combination of resources (e.g. radar, fire
control, soft-kill, hard-kill etc) that maximises a
measure of effectiveness, such as the probability of
survival. Various measures of effectiveness have been
studied and their relationship to systems analysis and
performance assessment documented [2,3]. In this
paper, we treat the problem from a systems viewpoint
and where necessary provide generic examples only,
due to the classified nature of some inputs.
In addition to finding the best combination of
resources to include on a ship, modelling is used to
derive optimal tactics for employing those resources
against specific threats.
An especially important
instance of this is the optimal coordination of the hardkill and soft-kill assets on a ship.
2. A Ship Air Defence Model
2.1 Model History
The Ship Air Defence Model (SADM) is a software
tool designed to simulate the defence of a single ship
against one or more attacking cruise missiles [4]. It
simulates soft-kill, hard-kill, and the interactions
between them. It is part of a family of tools, another
version of which models the defence of multiple ships
in a task group.
The model was derived from an Anti-Ship Capable
Missile Engagement Model, which was originally
developed by the Electronic Warfare Division (EWD)
of the Defence Science and Technology Organisation
(DSTO) in Australia.
The SADM program has been extensively developed
and enhanced compared to the capabilities of its
ancestral program. The front end of the SADM is
written in MATLAB, and the back end (the
computational core) is written in structured Fortran 95.
The front end provides a graphical user interface (GUI)
to enter scenario data and to display results, whilst the
back end performs the actual simulation of the missileship engagement. The front end provides the ability to
customise more than 250 individual ship, radar, ESM,
weapon, threat, and environmental parameters for each
scenario.
An important feature of the model is its ability to run
well on a standard desktop PC. It is able to produce
results in a timely fashion without requiring an
expensive hardware platform.
2.2 Model Function
The Ship Air Defence Model is a low-level ship,
threat, and countermeasure engagement simulation. The
basic cycle time of the model is the integration interval
of the threat missile seeker. A typical missile seeker
might have a PRF of 5000, with 100 pulses being
integrated before each track loop update, so the typical
update rate of the model is about 50 Hz.
At the beginning of each integration interval, the
positions of the ship and all other players (decoys, chaff
clouds, jammer, and hard-kill weapons) are updated. At
the end of the integration interval, the model calculates
the power contributions seen by each threat seeker from
all ship and countermeasure sources, and builds an
overall signal envelope. The seeker then performs range
and angle tracking on the signal, and the missile model
updates the threat missile position based on the range
and angle errors. This process is repeated until the
threat missile is either destroyed or reaches its closest
point of approach (CPA) to the ship. If the CPA is
within a user-defined ellipse centred on the ship, then
an intercept has occurred, and the missile is considered
to have made a kill. Otherwise, the missile has missed
the ship. The status of all sensors is updated once per
integration interval, with appropriate detections and
track updates supplied to the ship’s Command and
Control system at the proper rates for each type of
sensor.
The Command and Control (C2) System model
contains two principal components. The first portion of
the C2 system processes detections, target reports, etc.
on an interrupt-driven basis. This part of the C2 system
classifies threats, and performs immediate processing
such as the release of automatic countermeasures, if
appropriate. The second portion of the C2 system runs
at a fixed 1 Hz rate. This part of the C2 system works
with the Weapons Control System (WCS) to prioritise
the targets, and to produce an engagement schedule
describing the hard-kill and soft-kill assets used to
attack them. The engagement schedule can include both
hard-kill and soft-kill engagements.
Hard-kill weapons are launched at the times specified
by the C2/WCS, and their flyout models update at the
same 50 Hz rate as the threats. Weapon behaviour will
vary depending on the type of weapon. For missile
weapons such as ESSM, the flyout model consists of a
pitchover manoeuvre, followed by an inertial midcourse phase, and concluded by a terminal homing
phase using proportional navigation. The probability
that a weapon will kill a threat is determined by usersupplied PK tables, which are indexed by the range at
intercept and the manoeuvring capability of the threat.
The model includes a batch processing feature that
allows multiple sets of Monte Carlo simulations to be
defined and executed as a unit. Within a single batch
run, the following parameters may be adjusted: Threats
(number, starting ranges and angles); Decoys (launcher
number, speeds and flight offsets); Chaff (launcher
number, cloud range/angle, radar cross-section, and
jammer coordination); Fire Control Radars (number of
channels); Illuminators (number of channels, start time
and duration); and wind speed and direction.
More than 200 additional ship, threat, weapon, and
decoy parameters can be varied from batch to batch, but
they must remain fixed within a single batch run. All
model inputs are entered using the MATLAB graphical
user interface. When the SADM is started, a series of
input screens allow the user to specify the initial
conditions for either one run or a batch of runs. The
results of one or more runs can be displayed graphically
using the MATLAB front end.
2.3 Model Overview
The SADM model consists of the following cooperative
sub-models (see Figure 1):
• Ship Models:
Trajectory, motion (heave, pitch, roll), radar crosssection (time dependence and aspect angle), electronic
support measures (ESM), search radar detection and
tracking, infrared search and track (IRST), IFF model,
fire control radars, illuminators, command and control
/ weapons control systems (C2/WCS).
• Soft-Kill Models:
Decoy Models – trajectory, payload
Chaff Models – cloud trajectory, radar cross-section
Jammer Models – trajectory, payload response
• Hard-Kill Models:
Missile Models – Flyout models, probability of kill
CIWS Models – detection, kill performance
• Threat Models:
Threat Seeker Model - with range / angle tracking, etc
Threat Trajectory Model – supports both sea skimmers
and high divers
• Environment Models:
Sea state (wind speed and direction), signal
propagation (including effects of multipath, incoherent
scattering, shadowing etc), infrared atmospheric
propagation using LOWTRAN/MODTRAN results.
3.
Selected Component Sub-Models
This section provides more detail about a few of the
component sub-models within SADM. Space limitations prevent a more detailed discussion of the submodels contained within the program.
3.1
C2/WCS Model
The C2/WCS Model mimics the operation of a
Command and Control System / Weapons Control
System. This model interfaces with all of the sensor and
weapons systems on the ship. It implements the Threat
Evaluation and Weapons Assignment (TEWA) process.
Because the TEWA process varies dramatically from
ship class to ship class, the C2/WCS Model has been
structured as a separate dynamic link library (DLL) that
is plugged into the model at run-time. Since the C2/
WCS model is separate and independently compiled, it
is possible to create versions of the model containing
the TEWA for each ship class of interest, and then to
select the one to use for a particular run by selecting the
DLL to load at run-time.
The generic C2/WCS system supplied with the model
can be divided into two portions, an interrupt-driven
portion and a scheduled portion. The interrupt-driven
portion of the system executes in response to a message
from the outside world, such as a track update or an
ESM detection. This portion of the system updates the
appropriate track files, classifies the threat, and orders
immediate actions such as an IFF request or immediate
soft-kill countermeasures. The scheduled portion of the
system runs at a 1 Hz rate. This portion prioritises all
confirmed threats, and schedules hard-kill and soft-kill
assets to engage them.
A state diagram for targets in the C2 system is shown
in Figure 2. When a new threat detection is received, a
track is established for it and its state becomes
IN_TRACK. Each time that a track update occurs, the
track is evaluated to see if it meets the potential threat
criteria. If it does, the state becomes POTENTIAL_
THREAT. Then, the track is evaluated to see if meets
the confirmed threat criteria. If it does, the state
becomes CONFIRMED_THREAT. All confirmed
threats are prioritised, and an engagement schedule is
computed once per second. This schedule can include
both hard-kill and soft-kill assets. Each engagement in
the schedule is committed as the required resources
become available.
Kill assessment is performed after an engagement is
completed. If the kill assessment is positive, the state of
the threat changes to NO_TRACK. If the kill
assessment is negative, the sate of the threat reverts to
CONFIRMED_THREAT, and a new engagement is
planned. The criteria for potential threat evaluation,
confirmed threat evaluation, and hard-kill/soft-kill
coordination are all under user control.
3.2
Search Radar Model
The Search Radar Model supports conventional 2D
radars, conventional 3D radars, or phased array radars.
The user can control parameters such as field of view,
antenna height, sweep rate, resolutions, processing
modes (conventional, MTI, or MTD), and PD as a
function of target RCS and altitude. The starting
azimuth for a search radar is determined randomly
during each Monte Carlo trial. There can be up to two
search radars on a ship.
The model supports either 2D or 3D search radars. If
the radar is a 2D system, then only the x and y
components of target position are reported to the data
fusion engine and the C2 System, and fire-control radar
acquisition times will be increased.
The observations that the search radars send to the
data fusion engine are corrupted in range and angle by
noise. The standard deviation of each measurement is a
function of the range and angle resolution of the radar
divided by the square root of the signal-to-noise ratio.
The search radar models may optionally include
multipath and diffraction in their signal strength
calculations.
3.3
IRST Model
The Infrared Search and Track (IRST) Model has
four components: a Transmittance Model, a Fog
Transmittance Model, a Beam Spreading Model, and a
Target Detection Model.
The IR transmittance curves for standard aerosol and
fog atmospheres are derived from LOWTRAN
atmospheric code. The transmittance data set is
currently stored as a 4-D look-up table of regression
coefficients corresponding to the equation for the BeerLambert Law.
When the IRST looks at a given azimuth, the model
checks to see if any targets are present within the field
of view. If so, it calculates the incident IR energy at the
sensor by starting with the radiance of the target in
watts per steradian, and correcting for range and
atmospheric transmittance. Then, the received signal
strength is compared to a user-specified threshold to
determine if detection occurs.
Observations from the IRST are sent to the data
fusion engine, where they may be optionally used to
improve track quality.
3.4
Weapon Flyout Models
The Ship Air Defence Model is designed to support
up to six types of weapons, each with its own flyout
model. The flyout model is designed to mimic the
operation of a specific weapon, such as a point-defence
missile, and each model has behaviour appropriate to
the weapon it is modelling. For example, a flyout model
may have a pitchover manoeuvre, followed by an
inertial mid-course segment, followed by a proportional
navigation homing segment. These flyout models are
approximate, not full 6DOFs, so they can be used to
determine approximate missile position but not the
actual probability of kill Pk . The probability of kill is
determined by user-supplied Pk tables that are a
function of intercept range and the threat
manoeuvrability. Each flyout model is a separate
dynamic link library, so it is relatively easy to create
new flyout models for new types of weapon systems.
3.5
Threat Seeker Model
The Threat Seeker Model is a model of the missile
seeker’s radar system. It is a rather complicated model
with several discrete components. The major
components of the Threat Seeker Model are the Search
Mode Component, Range Track Component, Angle
Track Component, AGC Component, Loss-of-Lock
Component, and the Chaff Discrimination Component.
Threat seeker and trajectory parameters are set on the
GUI screen shown in Figure 3.
3.6
Threat Trajectory Model
The Threat Trajectory Model models the dynamics of
a representative threat missile that is capable of speeds
from Mach 0.8 to Mach 3.0. The dynamic constants of
the model are automatically adjusted for proper
behaviour depending on the user-specified missile
speed.
The model uses a proportional navigation law in
azimuth. It uses a height-keeping law in elevation
during cruise, and a constant-angle navigation law
during dives.
The inputs to the Threat Trajectory Model are the
smoothed azimuth and (optionally) elevation sightline
rates from the Threat Seeker Model, and height
measurement from the missile’s on-board altimeter.
4. Measures of Effectiveness
The principal measure of effectiveness for any ship
air defence system is the probability of ship survival PS
against a threat or a raid consisting of many threats.
The batch features of the SADM program permit a user
to vary the number, type, and characteristics of threats
in a raid, and see the effect on ship survivability.
Figure 4 shows a typical PS versus number of threats
plot for a subsonic raid against a ship with a 2D search
radar, two channels of fire, and generic semiactive
terminal homing missiles. Note that this plot was
created for the case of weaving subsonic threats and a
shoot-look-shoot fire policy.
Since the SADM model allows a user to easily
change radars, numbers of fire control channels, and
types of weapons, many batch runs can be created and
appropriate PS values can be calculated for each
configuration. The resulting data can be used in system
cost-versus-performance trade-offs.
Figure 5 shows a typical output that can be produced
from the model. It illustrates the effects of changing
search radar types, the number of fire control channels,
and the presence or absence of decoys on the ship PS
against generic weaving subsonic and supersonic
threats. These results are for a ship having only
medium-range semi-active terminal homing missiles
and active decoys. In this case, the ship did not have a
close-in weapons system or short-range point-defence
missiles.
Another use of the model is to optimise self-defence
tactics for maximum PS against a given threat once a
ship configuration has been established. The SADM
model allows a user to modify weapon mixes and fire
policy, providing the PS , the number of rounds
expended, and the cost of the expendables for each
engagement. These output permit a user to optimise
tactics for maximum PS , for maximum time on station,
or even (beware the bean counters!) for minimum cost.
Finally, the model permits a user to explore the
interaction between hard-kill and soft-kill systems, and
to determine how to employ the two complementary
systems together in an optimal manner.
5. Summary and Conclusion
Computer modelling represents a cost-effective
approach to the problem of performance prediction and
tactics assessment under a range of conditions for predefined threat scenarios. A salient feature of the SADM
program is that the modelling process captures the
interaction among the naval platform, surveillance
systems, airborne threats, countermeasures, and the
environment in a low-cost PC-based simulation.
The SADM program provides a tool for supporting
studies in system integration for new or existing ships,
tactics evaluation, countermeasures coordination, and as
a training aid for operators of naval combat systems. It
provides an analytic tool for comparative trials of naval
platforms. Optimisation of ship air defence against
anticipated or future threats is an application where
computer modelling is the only recourse [1,2]. Threat
simulation also leads to the assessment of the most
appropriate tactics for ship defence and survival based
on soft-kill, hard-kill or a combination of both.
6. References
1.
2.
3.
4.
Polk, J., McCants, T. and Grabarek, R., Ship SelfDefense Performance Assessment Methodology,
Naval Engineers J., 209-219, May (1994).
Carling, R.L., A Knowledge-Base System for the
Threat Evaluation and Weapon Assignment
Process, Naval Engineers J., 31-41, Jan. (1993).
Rains, D.A., Methods for Ship Military
Effectiveness Analysis, Naval Engineers J., 127135, March (1994).
Chapman, S.J., A Brief Introduction to the Ship Air
Defence Model, British Aerospace Australia,
Abbotsford, VIC, Australia (1998).
7. Author Biographies
Stephen Chapman is Manager of Technical Systems
and a senior radar engineer at BAE SYSTEMS
Australia (Missiles and Decoys). He has extensive
experience in modelling and simulation of air defence
systems. Mr. Chapman’s experience has included 10
years of radar research at Massachusetts Institute of
Technology Lincoln Laboratory, Lexington, MA, USA,
plus 3 years of seismic signal processing research at
Shell Development Laboratory in Houston, TX, USA.
Kurt Benke is a senior systems analyst with BAE
SYSTEMS Australia. His project experience includes
air defence modelling, infrared search and tracking
(IRST), IR atmospheric propagation, ship trajectory
kinematics and mapping in littoral warfare
applications.
Ship Models
IRST Model
Search Radar
Model
Threat Models
Data Fusion
Model
Threat
Trajectory
Model
IFF Model
Fire Control
Radar Model
Threat Seeker
Model
Illuminator
Model
C2/WCS
Chaff Models
Ship ESM
Model
Decoy Models
Jammer
Models
Weapon Flyout
Models
Wind Model
Ship Trajectory
Model
CIWS Model
Ship Motion
Model
Ship RCS
Model
Figure 1. Major relationships among component models. Arrows show the directions of data flow among the
models.
Potential
Threat
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Th
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a
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Po valu
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Con
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Eva ed Th
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lua
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Confirmed
Threat
sm
en
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As
se
ss
m
en
itm
mm e
Co Tim
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t
t
Su
cc
e
Pl ssf
an ul
Rep
lan
Ne
ga
tiv
e
Ki
ll
at 1
As
se
s
Ta
Det rget
ect
ed
Ki
ll
Plan Engagement
Engagement
Planned
Engaging
Figure 2.
Target state diagram for the generic C2/WCS System.
to
le
ab n
Un Pla
No Track
Po
si
tiv
e
s in
terv
als
In Track
NonEngagable
Figure 3. The Threat Data Screen. This is a typical input data screen for the SADM model.
Figure 4. A typical Scenario Summary Screen illustrating PS versus raid size. This output screen allows a user
to plot any two variables in a batch of runs versus each other.
Scenario A
(subsonic threat)
Radar F + 3 FCS + Decoys
Radar E + 3 FCS + Decoys
Radar D + 3 FCS + Decoys
Radar C + 3 FCS + Decoys
Radar B + 3 FCS + Decoys
Radar A + 3 FCS + Decoys
Radar F + 3FCS
Radar F + 2 FCS
Radar E + 3 FCS
Radar E + 2 FCS
Radar D + 3 FCS
Radar D + 2 FCS
Radar C + 3 FCS
Radar C + 2 FCS
Radar B + 3 FCS
Radar B + 2 FCS
100
P s (%)
80
60
40
20
0
1
3
5
Radar A + 3 FCS
7
9
Radar A + 2 FCS
11
13
15
Number of Threats
Figure 5a.
Probability of survival PS versus number of threats for Scenario A (weaving subsonic cruise missiles).
The value PS is plotted versus the number of threats for different combinations of specified radars, fire
control systems and decoys.
Scenario B
(supersonic threat)
Radar F + 3 FCS + Decoy
Radar E + 3 FCS + Decoy
Radar D + 3 FCS + Decoy
Radar C + 3 FCS + Decoy
Radar B + 3 FCS + Decoy
Radar A + 3 FCS + Decoy
Radar F + 3 FCS
Radar F + 2 FCS
Radar E + 3 FCS
P s (%)
Radar E + 2 FCS
Radar D + 3 FCS
Radar D + 2 FCS
100
Radar C + 3 FCS
80
Radar C + 2 FCS
60
Radar B + 3 FCS
40
Radar B + 2 FCS
20
Radar A + 3 FCS
0
1
Figure 5b.
Radar A + 2 FCS
3
5
7
Number of
Threats
Probability of survival PS versus number of threats for Scenario B (weaving supersonic cruise
missiles). The value PS is plotted versus the number of threats for different combinations of specified
radars, fire control systems and decoys.