2011 International Conference on Modeling, Simulation and Control
IPCSIT vol.10 (2011) © (2011) IACSIT Press, Singapore
Real Time Path Planning in STAGE
Xun Luo, Jiaqi Liu, Gang Meng
National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematical，Beijing,
China
Corresponding Author: Xun Luo. Tel: +86 13671359045; Fax: +86 010 68382257.
E-mail address: mrluoxun@163.com
Abstract：A new method of aircraft low altitude penetration is proposed with temporal constraints that
allow periods of high observability interspersed with periods of low observability as well as the way to
develop in STAGE environment. The aircraft’s RCS character is simplified into the “bow-tie” distribution,
then the aircraft can dynamically adjust its heading angle to minimize the risk from the radars. The
developing methods of user model and the script language is given, and analyze the simulation result of one
aircraft’s low altitude penetration.
Key words: Real time path planning, STAGE, penetration, RCS
1. Introduction
Path planning is one of the major subjects in aircraft’s low altitude pentration efficiency, attracting many researchers
and institutes’s interest, and commiting themselves to the study. While the threats concerning with the penetration are
very complicated, such as the terrain threat, radar detection threat, fighter inteception threat, SAM threat, and antiaircraft
artillery threat etc. So it’s very important to select a professional simulation platform to run user’s simulation, while the
STAGE producted by the eNGENUITY Technologies Inc.(ETI) from Canada is a mature simulation platform, which
could provide plenty of simulation means and extendable model easy to develop, which decrease the pressure user
suffered in platform construction.
2. Introduction in STAGE Scenario 5.0
The following picture is an overview of the STAGE Scenario architecture (relation between the different
executables and databases). The applications shown on the right side are other products and executables that can interact
with STAGE. All other components are part of the product.
Fig 1
STAGE architecture
STAGE’s architecture is mainly built up by next parts[1]:
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Scenario Manager (SM) :User interface used to build and assemble the components of a scenario (Scenario and
Database Editor) and monitor and control its evolution (Runtime Environment). The Runtime Environment containing
the SAD (Situation Awareness Display) is shown in the SM at runtime.
Simulation Engine (SIM) :SIM gets entities’ and scenario’s information from the communications between SM, and
display the scenario’s situation and the statistic during simulation running, reacts with the simulation.
Integrated Development Environment (IDE) : The STAGE Scenario Integrated Development Environment (IDE)
provides a Graphical User Interface (GUI) that you use to add the data structures required to support the simulation
models that you incorporate into STAGE.
3. User model and development of script language
The real time path planning method mainly include the detection model of radar, the aircraft’s RCS distribution
model and the real-time path planning model.
3.1. Detection probability model
In STAGE there is its own detection probability against the target, which needs user fill some specific parameters of
radar, such as power, frequency, and user must set the probability of detection curve at some given RCS, which means a
lot of work if the RCS distribution is complex.
The curve could demonstrate the radar’s detection probability against a given RCS. If the RCS changed, user have
to define another radar’s detection probability curve against the changed RCS. Therefore the detection probability model
against general RCS needs to be redesigned to meet the requirement.
While the detection probability model against general RCS could refer to literature [2].
3.2. RCS distribution model of aircraft
The RCS of the entity is set to one single value in STAGE, so it’s an average value, which could not match the
aircraft’s real RCS distribution of course. The following picture is a typical RCS distribution of an aircraft, and from
which we could conclude that the RCS in aera nearby heading and tailing direction is small, while the RCS near side
direction is bigger. Frederick[3] present two simplified RCS model to match the real aircraft’s RCS distribution. In this
airticle the “bow tie” distribution is adopted, which could match the typical aircraft’s RCS in certain degree.
Fig 2 typical aircraft RCS distribution
The RCS value could be achieved from the next expressions:
⎛ f (ψ ) − f ( 0 )
⎞
−1.14 ⎟⎟
⎜⎜
f ( 0)
⎝
⎠
σ = 10
f (ψ ) =
( sinψ
(1)
+ 0.1)
(2)
The azimuth angle(ψ ) in expression above could be achieved according to next picture.
α
Y
( x, y)
ψ
? Radar
?
R
( x0 , y0 )
ϕ
X
? ? ?
Fig 3 aircraft’s orientation relationship with the radar
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3.3. Aircraft’s real time path planning model
The real time path planning model is the kernel part, but it is not ready in STAGE, so it’s necessary to develop the
model meet the requirement of STAGE.
According to literature [4], the tracking while scan(TWS) technology is the most often used technology in radar data
processing, which mainly built up by some behavior such as: track initialization, track correlation, track filtering and
tracking, track suspension.
Assume the time of radar establish a track is TStart , if aircraft could maneuver against radar so that the radar miss
the target temporal for a certain time, assume the time is TLL , the aircraft could get rid of the threat of radar temporaryly,
which would triggle the track suspension or track initialization failure, then the aircraft could fly over the defense area of
radar because of the disengage fortunately[4-6]. Then it would be possible for aircraft to penetrate the defense area with
temporal constraints that allow periods of high observability interspersed wth periods of low observability, which could
be helpful to lower the detection probability of radar against aircraft.
The real time path planning model’s principles is described as below:
(1) checking the current node is destination or not, if yes, then exit.
(2) checking the information about the threat is updated or not, then calculate the detection probability(Pd) at current
node. If Pd>0.5, the Engage timer record the interval that radar had detected the aircraft with assumption that radar detect
the target if Pd>0.5, and clear the Engage timer; If Pd<0.5, the Lock Loss timer record the interval that radar had lost the
aircraft.
(3) if the interval in Engage timer is bigger than TStart , the aircraft execute the avoidance maneuver.
(4) if the interval in Lock Loss timer is bigger than TStart , clear the Engage timer.
And the avoidance model’s principles is described below:
(1) calculate the azimuth angle ψ , aircraft fly away along the line between the aircraft and radar.
(2) when the Pd<0.5, Lock Loss timer began to count, if the value in Lock Loss timer is bigger than TLL , it’s
determined that radar loss the aircraft, then the aircraft returned back to its original trajectory.
(3) exit.
3.4. Extend scirpt language
User could extend the original scirpt language by adding yourselves customized constants, functions and classes,
which could make the development easier in large system developing.
For example, user could add the user model in paragraphs above to STAGE kernel according to the syntax of STAGE,
after compiling, user could call the customized functions during your development on script language.
3.5. Extend simulation engine
After embeded the user model to the STAGE kernel, the user simulation engine need to recompile with the same way
as extending script language, and then, user could call the customized function in STAGE simulation.
3.6. Develop script
After integrated the customized function into the STAGE, user could develop script attached to different entities,
through which user could set the entity’s beheavior when triggered some specific condition.
4. Example
To build up a scenario need to add the entities which would be used in STAGE, such as radar, aircraft. After adding
these entities, user need to initialize these entities with velocity, acceleration, and other parameters so on. Then attaching
their own script which could excute the beheavior when triggered the user defined condition.
The final scenario is shown as following. Assume that the start point locate below the figure, and the end point locate
above the figure, the velocity of the aircraft is 300m/s, the radar patrol along the route at the velocity of 100m/s in left
side.
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Fig 4 scenario setup
The next figure is one simulation result. The blue trajectory in right side is the aircraft’s route, while the red
trajectory left side is the radar’s route.
Fig 5 one simulation result
According to the simulation result, the aircraft executes the threat avoiding beheavior effectively against radar during
its low altitude penetration.
Certainly the occurrence of the threat avoiding maneuvering depends on the orientation relationship with the radar.
According to the aircraft trajectory, it could be read that aircraft execute the threat avoiding maneuvering when radar
track the aircraft for a interval longer than TStart . The aircraft changed its heading angle to the direction of flying away
the radar according to the orientation relationship with the radar, obviously the direction is the minimun RCS area. The
aircraft fly away for a interval longer than TLL , which would make the occurrence of track suspension. After getting
away from the surveillance of radar, the aircraft refollowed the original trajectory. Because the aircraft still could be
detected, the aircraft would execute the threat avoiding maneuvering again, then the serrated trajectory was generated.
The data of all entities produced during simulation could be watched through the hook dialog at left side and the
shell window at right side in the following picture, from which user could achieve the information in anytime during the
simulation, and provide the comprehensive information for true penetration, make the detailed penetration strategy.
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Fig 6 simulation process control
In shell window, user could edit code in script to show the real time entity state parameters user would be highly
concerned, such as slant range, RCS against radar and the probability of detection.
In hook dialog, user could watch entity’s real time parameters such as velocity, hight and script’s status. User could
also redesign the display contents through STAGE developing templates to show more information.
The dialog in middle is the console, through which user could control the speed of simulation and the starting time
of the simulation.
In addition, there is a Logger tool for recording, through which user could record the simulation process for data
analysing and strategy researching.
5. Conclusion
According to the Lock Loss model, using the “bow tie” RCS distribution model, the aircraft could exposure for a
while under the radar threat safely, and during this while aircraft could execute the threat avoiding maneuvering to get a
new route. And the STAGE is a powerful software for real time simulation, through which user could develop his own
model with full energy, STAGE would easily lower the user’s burden in underlying development.
6. REFERENCES
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