During the design of proximity radio fuzes (Wang et
al., 2007), a lot of test data must be provided so that the performance
and evaluation could be verified. In fact, the working environments and scenarios
were constructed and simple entries were used for the possible targets. Then,
the radio generator transmits the radio that would be used by the designed radio
fuzes and receiver equipment receives the echo radio signal returned back by
the possible targets (Zhang et al., 2011). Obviously,
this approach would take a lot of time and money which was not economic in the
current advanced computer era. At the same time, the designed fuze radio detector
has to be tested or verified in different scenarios which was not all possible
constructed by actual objects. Furthermore, the actual constructed scenarios
could not be similar to the designed cases and these data from these scenarios
could not be fit the designed fuze radio detector. So, how to construct the
computer simulation platform of radio fuzes was one alternative approach to
avoid these problems.
Up to now, there were few studies or papers that devoted to the radio fuze
simulation platforms. Whats more, only several echo signal simulation
methods (Qiuju and Cuiqiong, 2010; Xu
et al., 2009) of radio fuzes and radar were presented by a few papers.
The presented echo simulation methods were those based statistic characteristic
and their simulated echo signals were not the data of one given targets. These
simulation results dont contain any information of fuze modulation modes
and the Doppler frequencies. Aiming to the target model, many researchers, Jinsheng
and Qinwei (2005), Tao et al. (2004) and
Hongfei et al. (2006) tried to use mathematics
formula to describe the shapes, sizes and movements of the possible targets.
However, this approach could not be successful for most actual targets with
various complex shapes and movement traces. Therefore, one target was divided
into large numbers of scatters and their echo signals were summed up to form
its echo signal (Anying, 2005; He,
2008). The problem was how to do it and it was not given in these studies.
This study would study one system simulation models that can avoid these problems.
In this study, one system echo simulation model based MATLAB Simulink was described
for the proximity radio detectors with existing multiple interfering which would
be very useful to improve the efficiency of radio detector design teams. The
model uses the 3ds Max 2010 scene files as the working environment of radio
detectors and the VRML plug-in ActiveX control as the Display windows in MATLAB
CONSTRUCT SPACE MODELS
As the professional 3D model constructing tool, the 3dS Max 2010 was widely used in the 3D geometry models, i.e., entries in games, objects and so on. In order to simulate the actual working environments of proximity radio detectors, the 3dS Max 2010 was used to set up the scenes with the considerations of weather, sea conditions, cloud, frog, temperature and so on.
Here, one 3D geometry scene was constructed according to the configuration
simulation requirements, as shown by Fig. 1. There were 5
scene entry objects in the scene boxtest, i.e., Box, missile, cone01,
sphere01 and cylinder01 and so on.
|| Boxtest scene model
|| Configuration parameters of the scene model test
The entries, Box and missile were the active objects;
missile and cone01 were configured as radio detectors
while sphere01 and cylinder01 were static objects during
the simulation conditions. As observed in the scene display window, i.e., Fig.
1, scene objects were substituted by simple geometry entries such as cuboids,
spheres, columns, or tapers. With bad modeling ability to control 3ds Max 2010
models, we used these simple geometries as substitutes to verify the system
simulation method and the rigorous 3D scene geometries by professional workers
would replace these simple ones when actual scene models were used for system
In the boxtest model, each scene objects was actually the actual substitutes in the working environments of proximity radio detectors. So, their properties, initial locations, movements were given by Table 1 and these information were used to deduce their location changes with simulation process. When one scene object was substitute of one interfering machine, it was configured as interfering machine. In the similar way, one scene object of one detector would be configured as one detector. Here, yes indicated that one scene object was one detector or interfering object. Furthermore, the scene objects as interfering machines and detectors, were also described with the system working modes and their relative parameters, i.e., sender power, antenna gain shape, initial phase, radiation resistance, carrier frequency and so on.
SIMULATION MODEL AND ITS CONFIGURATION
As the system mode of the simulated proximity radio detectors and interfering
was continuous wave, one echo simulation model was constructed by MATLAB Simulink,
as shown by Fig. 2, where, the sheltering angle was set to
0.00175, the speed of electromagnetic wave as 3x108 m sec-1,
the minimal detecting power -50 dBm, the input sample frequency 20 kHz, the
output sample frequency 170 kHz, the simulation time 0.1 sec. Whats more,
the echo simulation module was configured in the window as display by Fig.
3 and the main parameters were set in the window as shown by Fig.
4. The shapes of antenna gain for detectors and interfering machines was
in the form of circle.
||Simulation model of proximity radio detector with boxtest
|| Configuration window for system parameters
In current space scene model, there were two detectors and one interfering and the echo signal for the two detectors should be evaluated, respectively. For one detector, its echo signal should be computed with other detectors as interfering machines. Meanwhile, the detectors and interfering machines were the actual entries in the scene, their echo signal to one given detector were also considered as interfering signals. Thats to say, they were viewed as general scene objects and their echo signals were also be summed together as the received signal of detectors.
After the simulation model was evaluated, we got the echo signals of Detector1 and Detector2, respectively, as shown by Fig. 5. Here, Detector1 was denoted as the radio detector of the missile while Detector2 denotes the detector cone01. During the whole simulation process, the missile would meet Box firstly and then pass by the entries, i.e., cone01, sphere01 and cylinder01, respectively.
Figure 6 showed the zoomed in signal waveform and the meeting
process could be reflected from the received signal at the receiver of Detector1.
When the missile met the box, the received signal would
be enlarged quickly. Furthermore, the received was much smaller when compared
to the case above, as the missile was not at the opposite of those
scene objects, i.e., cone01, sphere01 and cylinder01,
respectively. However, for the detector cone01, its position was
unchanged and its received echo signal from those objects in its view has little
changes even if when the missile and box passed by.
|| Simulated echo signal by current simualtion model
|| Zoomed in signal for the echo signal at Detector1
This phenomenon was indicated by the received signal strength, i.e., the strength
of its waveform front end was little larger than that of its back end.
According to the simulation results, it could reflect simulate the received signal in the case with multiple detectors and interfering machines. It could be used for the evaluation of complex war-field environments.
In this study, one simulation model with multiple detectors and interfering machines was described for the proximity radio detectors which was the working environments where the proximity radio detectors work. The simulation model involves space scene models, echo signal evaluation and energy loss in the propagations of electromagnetic waves. Finally, the simulation results were presented for the simulation models with special space model constructed by 3ds Max 2010 and verified the accuracy in the case of actual cases.
This study was supported by the Henan Basic and Advanced Technology Research
Program (122300410380), the Key Research Project of Science and Technology by
Henan Ministry of Education (12A510001), the Science and Technology Research
Program of the Education Department of Henan Province of China under Grant No.12A120002.