Real-time Radar Data Visualization
Giti Javidi1, Ehsan Sheybani1, Danielle Mason1, Akbar Eslami2 and Jamiiru Luttamaguzi2
1
College of Engineering and Technology, Virginia State University, Petersburg, VA
2
Department of Engineering, Elizabeth City State University, Elizabeth City, NC
Abstract - To have a fully functional FMCW X-band radar
for the SMARTLabs ACHIEVE trailer, it is necessary to (a)
produce code to retrieve data from an FPGA board linked
to the radar, (b) calculate Fourier transforms and (c)
display the power spectrum in near-real time using a
computer code based on freely available scientific
development tools. So that the communication between the
FPGA board and the computer is reliable and accurate,
developing a specific format through the use of C was an
initial step. This was followed by the development of a
method to visualize data efficiently. In this case, Python,
along with its matplotlib, SciPy, and NumPy modules, were
used. Both programs were then integrated together within a
graphical user interface.
Keywords: Radar, Processing, FPGA, Fourier transform,
Python.
1
Introduction
The use of radar is important in the detection of both
stationary objects, such as buildings, and moving objects,
such as clouds and aircraft [1, 2]. Radar has varying levels
of frequency with the measurements ranging anywhere from
megahertz to gigahertz [5]. An X-Band radar frequency can
range anywhere between 8 and 12.5 GHz [6]. The radar that
is focused on throughout the course of this project was an
X-Band, frequency modulated continuous wave (FMCW)
radar with frequency of 10 GHz. FMCW radar utilizes
frequency modulation of a continuous signal to acquire
range information. One prior example of such a radar
includes the PILOT radar which was "used by warships for
navigation where the ability to perform accurate navigation
in poor weather is essential for the accomplishment of the
ships' tactical mission" [7]. Another example is the use of
scanning X-band radar, paired with FMCW K-band radar, in
an experiment by Joel Van Baelan, Frederic Tridon, and
Yves Pointen to retrieve accurate rainfall rate estimates [9].
Benefits of this type of radar are that it is not just safe
and inexpensive, but also serves as a means in filling in gaps
of higher powered pulse-doppler radars when used in
conjunction with them [3]. This proves especially important
for SMARTLabs (Surface-based Mobile Atmospheric
Research and Testbed Laboratories), which consists of the
three mobile laboratories [8]. The mobile trailers are
SMART (Surface-sensing Measurements for Atmospheric
Radiative Transfer), COMMIT(Chemical, Optical &
Microphysical Measurements of In-situ Troposphere), and
ACHEIVE (Aerosol-Cloud-Humidity Interaction Exploring
& Validating Enterprise). The SMART trailer utilizes active
and passive sensors to collect data on the atmosphere,
gaining more knowledge about surface energy. The focus of
the COMMIT trailer is to collect and measure information
on the microphysics of aerosols, such as particle size, in
addition to gathering information about optical properties of
aerosols, such as absorption and scattering. For the focus of
this paper, the ACHEIVE trailer will be referenced. The
purpose of the ACHEIVE trailer is to further the
understanding of aerosol-cloud interactions by being able to
probe cloud properties for SMARTLabs as a whole. Within
the trailer, there are three different radars that work
together: the W-band (94 GHz), the K-band(24 GHz), and
the X-band. To successfully use this X-Band radar. It was
important to first effectively retrieve data in a proper format
and then visualize the data in an efficient and reliable
manner.
2
Methods
Prior to the start of this project, there were a few steps
that had been completed already in regards to preparing the
radar-computer communication. One such step included
development and installation of a packet sniffer [4] program
to the Field Programmable Gate-Array (FPGA) board. A
packet sniffer program is "a network monitoring tool that
captures data packets and decodes them using built-in
knowledge of common protocols" ("packet"). In this case,
the packet sniffer program (named Xserver program) was
written in C and accepts data packets with the size of 416
bytes, with 16 bytes of header and 400 bytes of actual data.
Because data coming from the FPGA board is in a 24-bit
format and the data that the Xserver and plotting program
expect is in a 32-bit format, the data needed to be properly
converted by way of another program or additional code
added to Xserver.
3 Summary and Conclusions
Results that have been found at the time of this writing
have shown that while the methods produced are functional,
there are several areas that can be improved or further
integrated. For instance, there were numerous times where
the speed was not fast enough, such as plotting the data. As
a compromise to plot the data in a way that is close to realtime, only a fraction of the data is plotted to the screen. The
reason for that is because every two seconds of data
displayed to the screen is an average of two seconds of data,
instead of it being a second for second plot. Because the
computer that was being used had a small amount of
memory and a slower processor, this method had to be done
or else the plot would run slower. Also, instead of having
both of the programs centralized to the one GUI window, all
of the programs run outside of the GUI in their own separate
windows. This was not a desired effect because it leaves
some disorganization for the user even though the programs
do accomplish the task intended. This was proven to be true
during the field calibration tests conducted at the Wallops
Island Facility in Virginia.
4
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