Self-Protection Chaff Modelling using the TRIREME Simulation

Self-Protection Chaff Modelling
using the TRIREME Simulation
Environment
Tomasz Jasinski, Mark Cooke
Aerospace Systems Group
Electronic Warfare and Radar Division
DSTO
1
Outline
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Introduction
TRIREME Overview
Chaff RCS
Aerodynamics
Total RCS
Frequency Response
Model Structure
Model Outputs
Summary & Future Work
Acknowledgements
References
Questions
2
Introduction
• Aim
– Development of a general purpose parameter-driven selfprotection chaff model useable with limited knowledge
about chaff type, launcher or aircraft configuration.
• Purpose
–
–
–
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Trial support
Engagement simulations
Countermeasures effectiveness studies
HIL simulations
The model is fed by fundamental physical parameters and doesn’t require an intimate
knowledge of chaff, launcher or aircraft. It is not a high fidelity model, such as one based
on a computational fluid dynamics package (that could provide a detailed analysis of
aircraft wake), or electromagnetic analysis software (that could emulate the response of
every dipole in the chaff cloud). This approach would be computationally intensive and
would be dependant on subtleties in aircraft configuration that in many cases are
unknown.
The main purpose of the model is to assist in trial preparation and for running
engagement simulations. Since such simulations may involve a large variety of aircraft
and scenarios, the requirement is for an easily configurable model that gives reasonable
solutions for any situation, rather than extremely accurate solutions for a particular
situation.
3
TRIREME Overview
• Background
– TRIREME (the Tactical Radar and InfraRed Engagement Modelling
Environment) was developed by the Aerospace Systems group in 2002.
– Original chaff model based on a stationary, single cloud, commercial naval chaff
model. The main limitations were:
• No cloud shielding effects for salvo releases, common in the self-protection
application
• No consideration given to platform motion (i.e. aerodynamics)
This is the top level of the TRIREME RF framework, and the environment into which the
chaff model was integrated (indicated). It is typically made up of blocks such as
transmitters, receivers, countermeasures, aircraft and missiles. It has a logical flow
following the physical RF path (e.g. transmitter feeds into the environment, which
outputs into the target platform, etc). Each model can either be a detailed system model
or a simple parameter-based model.
4
TRIREME Overview
• Relevant features
– Fully functional simulation environment; power levels,
line-of-sight angles, aircraft motion and other engagement
parameters already calculated.
– A large repository of components (radars, aircraft, missiles,
countermeasures, etc) already exists, including configurable
models for use when a detailed model is not available.
– Self-configuring; Simulink wires are automatically rerouted when a block is added or replaced through the use of
S-functions.
– The majority of models (including this chaff model) are
vectorised.
A vectorised model is one that accepts vectors as well as scalars as inputs. This
effectively allows the model to be used against a variable number of inputs, which can
change dynamically. This is a particularly useful quality for a chaff model, where
hundreds of chaff clouds may be launched throughout a simulation. In such a case, each
chaff cloud uses the same code.
5
Chaff RCS
• The response of a single, randomly oriented dipole is
well documented[1]:
σ θ = 0.17λ2 cos 2 θ + 0.11λ2 sin 2 θ
• Power reflected off a cube of volume x3 of n randomly
oriented dipoles with capture area 0.17λ2 and incident
power density ρi has been represented by:
ρi
x
ρt = ρi e
2
− 0.17 n ( λ ) ⎤
⎡
x
Pr = ρ i x 2 ⎢1 − e
⎥
⎦
⎣
− 0.17 n ( λ )
x
2
Ps = 0.65 ρ i x 2 ⎡1 − e
⎢⎣
− 0.17 n ( λ ) 2
x
⎤
⎥⎦
Rather than considering each dipole within a chaff cloud separately, the smallest model
elements are constant density cubes of dipoles. The RCS of these elements is a function
dipole density and wavelength. The main assumption made using this simplification is
that dipoles are independent of each other (their radiation patterns aren’t distorted by
cross-coupling of other dipoles). This was shown to be a reasonable assumption to make
down to separations of about 0.4 wavelengths.
Both the reflected and side-scattered quantities are shown as power levels, corresponding
to power that is re-radiated from the dipoles. However, the transmitted quantity is shown
as a power density, indicating the attenuation of the direct path. In reality, there would
also be a back-scattered component which has not been shown here due to its relatively
small magnitude when dealing with these particular geometries.
Theta is the angle of reflection (zero for the mono-static case considered here).
6
Chaff RCS
EM simulation (1440 dipoles)
Physical model (1440 dipoles)
20
0
Reflection (9GHz)
Transmission (9GHz)
10
Normalised Gain (dB)
Attenuation (dB)
-10
-20
-30
0
-10
Theoretical
Measured
-40
-50
0
1
2
Wavelengths Separation
3
-20
0
0.5
1.0
1.5
Mean Dipole Separation (λ's)
Testing of the concept was carried out at Loughborough University (UK) as part of a
Master’s Thesis project. Both anechoic chamber tests and electromagnetic simulations
were carried out on cubes of dipoles of various densities. In general, results consolidated
the theory. However, at dipole separations below about 0.4 wavelengths, there were
major discrepancies. The chaff cubes became transmissive (directional) along the axis of
incidence. Since this effect was only observed at extremely high chaff densities (about
400,000 dipoles per cubic metre) corresponding to perhaps the first few milliseconds of a
jettison, the effect was not investigated further or incorporated into the final chaff model.
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Aerodynamics
• Based on vortex approach
– Well documented, well understood, elegant and precise
– Assumes all chaff dipoles are caught up in wingtip vortices
• Modelling of roll-up phase remains questionable so a
common atmospheric diffusion model was used.
Wingtip vortex formation using
the Lamb vortex model [2][3]
VT =
Atmospheric diffusion model [1]
p ( x, t ) =
⎛ − r 2 ⎞⎤
Γ ⎡
⎢1 − exp⎜⎜ 2 ⎟⎟⎥
2πr ⎢⎣
⎝ rc ⎠⎥⎦
1
2πB x t
⎛ ( x − Ax t ) 2 ⎞
⎟
exp⎜⎜ −
2 B x ⎟⎠
⎝
4
Relative Density
3
2
1
0
-2
0.5
-1
0.4
0
Position (m)
0.3
1
0.2
2
0.1
Time (s)
The extremely small Reynolds numbers of chaff dipoles imply that they follow the
aircraft’s wake. Therefore, if wake motion can be defined, then dipole motion is implied.
The initial stage of bloom (while the air is still in sheets) is modelled using a classical
diffusion model. This allows for approximate cloud growth and dipole density to be
obtained. Once dipoles are captured in the wingtip vortices, velocities can be calculated
using the Lamb vortex model.
Definitions: VT is tangential velocity, Γ is circulation, r is vortex radius, rc is vortex core
radius, Ax is the drift coefficient, Bx is the diffusion coefficient, x is position and t is time.
8
Aerodynamics
• Advantages:
– Aerodynamics become parameterised (i.e. a function of aircraft weight,
g-load, speed, wing span and altitude).
– Many useful quantities can be easily derived for aircraft wake (e.g.
velocity profile, decay times and fall rates).
Simulated vortex velocity profile for
an F/A-18 fighter at various g-loads.
Decay of a theoretical span-wise
vortex velocity gradient.
500
1000
Core Velocity (m/s)
Vortex Velocity (m/s)
250
0
-1000
-250
t = 10s
t = 2s
t = 0.5s
t = 0.1s
8-g Loading
4-g Loading
2-g Loading
1-g Loading
-500
-1.0
-0.5
0
Radius (m)
0.5
1.0
-0.050
-0.025
0
0.025
0.050
Core Radius (m)
As these plots show, in theory, vortex core velocities are extremely high. However, the
core is typically less than 1cm in diameter, and the radius of interest in this application is
of the order of one metre. At such distances from the core, meaningful results can be
obtained.
It should be stressed here that wake vortices are a consequence of lift that is generated
from the aircraft wings and body. They are not the result of exhaust gases from the engine
(jetwash), which has not been considered here.
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Total RCS
• The entire chaff cloud is constructed from chaff cubes of
various densities.
• Reflectivity and transmissivity are calculated for “rays” of
radiation.
• Rays are added for each “slice” of the chaff cloud (simulation
time-step).
Cloud cross-section
Sample cloud structure
Constant density
cells
Decreasing
chaff density
3σ chaff
surface
Launch point
Hypothetical
“ray” of
incident
radiation
Aircraft direction
3σ chaff
surface
Once dipole distribution is known as a function of time, the entire cloud can be
constructed from chaff cube elements. It may be possible to apply this approach to other
types of chaff deployments (such as naval chaff), however, cloud shape and dipole
distribution would need to be defined.
It should be noted that the two diagrams on this slide are for illustrative purposes only
and do not represent any simulation results.
10
Frequency Response
• Dipole frequency response based on lookup table containing
the standard dipole response curves.
• Cuts (dipole lengths) and quantities are user defined (a drop
down list of common chaff types are also available).
• Total cloud response is the sum of all dipole responses.
RCS of a dipole [4]
Simulated response of a custom
chaff package (with arbitrary cuts)
7500
2
RCS (m )
5000
2500
0
0
2
4
6
8
10
Frequency (GHz)
The chaff cloud frequency response is calculated using standard dipole response curves.
Each cut within the package is considered. As an example, the frequency response of
some arbitrary lengths of chaff have been simulated and shown as a sample frequency
response plot.
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Model Structure
12
Model Outputs
140
50
120
40
Tangential Velocity (m/s)
RCS (m2)
100
80
60
30
20
40
0
10
Unshielded Cloud
Shielded Cloud
20
0
0.5
1
1.5
Time (s)
2
2.5
0
3
0
2
4
6
8
10
Cloud Radius (m)
0
0
-5
-20
-10
-15
-20
Gain (dB)
RCS Loss (dB)
-40
-60
0m
0.3m
0.5m
1.0m
2.0m
4.0m
6.0m
-80
-100
-120
0
0.1
0.2
0.3
0.4
0.5
0.6
Time (s)
0.7
0.8
0.9
-25
-30
-35
-40
-45
1
-50
0
0.1
0.2
0.3
0.4
0.5
0.6
Time (s)
0.7
0.8
0.9
1
Note: all results correspond to an arbitrary chaff length, chaff quantity, flight condition
and aspect. They should not be treated as realistic results.
Clockwise from top-left: a simulation involving two, identical clouds shows the effect of
shielding by the leading cloud; tangential velocities as a function of cloud radius within a
blooming chaff cloud; attenuation of “rays” taken at various radii through a blooming
cloud; cloud attenuation as a function of time.
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Summary & Future work
• Key points:
– A parameterised, vectorised self-protection chaff model was developed
and integrated into the TRIREME simulation environment.
– Chaff cloud RCS was calculated from constant density cells of
randomly oriented dipoles. This allowed calculation of cloud
obscuration effects, required when dealing with salvo jettisons.
– Chaff cloud aerodynamics were based on atmospheric diffusion and
Lamb vortex models. This allowed calculation of approximate cloud
dimensions and chaff velocities within the cloud.
• Future plans:
–
–
–
–
–
Further refinement and testing of approach.
Validation of results against trial data and other models.
Extension to bi-static case.
Generation of simplified model for real-time applications.
Generation of simplified, standalone “RCS Tool” for use by clients.
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Acknowledgements
• M. Hodkin, DSTL Farnborough, UK.
• C. Carpenter, RAF College Cranwell, UK.
• Department of Aeronautical and Automotive Engineering, Loughborough
University, UK.
• Department of Electronic and Electrical Engineering, Loughborough
University, UK.
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References
[1] S. A. Vakin, L. N. Shustov and R. H. Dunwell
Fundamentals of Electronic Warfare
Artech House, 2001
[2] E.L. Houghton and P.W. Carpenter
Aerodynamics for Engineering Students
Edward Arnold, 1993
Fourth Edition
[3] J.N. Hallock and W.R. Eberle
Aircraft Wake Vortices: A State-of-the-Art Review of the United States R&D Program
U.S. Department of Transportation, February 1977
[4] J. H. Van Vleck F. Bloch and M. Hamermesh
Theory of Radar Reflection from Wires or Thin Metallic Strips
Journal of Applied Physics -- March 1947 -- Volume 18, Issue 3, pp. 274-294
Radio Research Laboratory, Harvard University, Cambridge, Massachusetts
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Questions?
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