Lab model design and implementation of a radar system
Hands-on experience and instructions prove fruitful in the fields of Radars to understand and develop complex radar systems. For this purpose, lab model sized commercial of the shelf parts based fully functional radar systems prove worthwhile for imparting meaningful practical sk
2025-06-28 16:33:57 - Adil Khan
Lab model design and implementation of a radar system
Project Area of Specialization RoboticsProject SummaryHands-on experience and instructions prove
fruitful in the fields of Radars to understand and
develop complex radar systems. For this purpose, lab
model sized commercial of the shelf parts based fully
functional radar systems prove worthwhile for
imparting meaningful practical skills in students. In
this work a Radar lab model is proposed using uRAD
hardware. This lab model would be utilized by students
to understand the working principles of an actual radar
system. The same system might be utilized for their
research activities as well.
The Lab-Volt TM RADAR system is the lab model available for radar lab at CAE. This lab model gives an understanding on component level working of the complete radar system. A lab model is to be developed that would be more user friendly and its setup would be more elaborative to the students while performing the experiments. The cost of this apparatus would be much
lesser than the foreign equipment as well. The radar is an important avionics component and very few institutes have a lab model of radar system available for the students to develop their basic concepts mainly because of foreign equipment cost. For this purpose, a lab model for the system is to be designed and implemented that would provide a modular level display to the audience and would be much lesser in cost.
Project Implementation MethodThe proposed lab setup is inspired from LabVoltTM lab trainer
system. Hence, for the manuals for this lab those of
LabVoltTM are taken as reference. A GUI design is aimed that is interfaced according to this lab’s requirements. Finally, the
lab model of a functional Radar system has been developed to
be utilized for hands on training of the students.
It would give a low cost uRAD based lab model of
Radar; Implementation of labs manuals of FMCW, MTI,
Pulsed Radar and their related lab experiments is proposed.
Design of a GUI is mentioned as well and it is well interfaced
with the subjective set up. This lab model can further be used
by several students for studying and implementing various
algorithms and experiments related to a Radar.
All the required objectives of range estimation, doppler
estimation, and localization can be carried out using the
described techniques. The described concepts have certain
advantages as compared to the selected single COTS radar.
These advantages include enhancement of field of view (FOV)
of our designed radar, improving the cross-range resolution
(SAR imaging), estimating 3D targets location and tracking of
the targets in 3D space. In order to enhance the performance to
price ratio allow cost single channel transmit/receive COTS
radar was selected which has its in built limitations with
respect to range and doppler resolutions and others as
described earlier. With all these considerations, an innovative
product has been designed to fulfill radar challenge objectives.
Moreover, the results from all the described techniques will be
consolidated to give the overall best possible detection results.
Finally, in order to emulate the challenge, some type of curtain
will be used for analyzing our detected results and techniques
to tailor them according to radar challenge scenario.
Advanced Techniques
An effort will be made to implement certain advanced
techniques while utilizing the same low-cost equipment. These
advanced techniques might not be directly helpful in terms of
radar challenge but, we will demonstrate their results to show
the capability of our low-cost innovative system. These
techniques include Ground Moving Target Indication (GMTI)
on SAR imaging using Along Track Interferometry (ATI)
technique, target classification using Machine Learning, dual
polarization SAR and Multi-Input Multi Output (MIMO)
radar. Although the techniques such as GMTI using ATI and
MIMO are very difficult to implement using two single
channel radars due to phase and time incoherence. We will
examine the impact of these inaccuracies on final outcome.
Similarly, target classification will require generation of
training dataset for the same target scenario for satisfactory
accuracy which seems difficult for such a radar challenge. All
the results from our lab experiments will be shared for
showing system capability.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 6800 | |||
| uRAD (universal radar) | Equipment | 2 | 3400 | 6800 |