Projects:2020s1-1231 Radar Waveform Design
Abstract here
Contents
Introduction
This project will study the performance of several advanced digital binary and polyphase waveforms and compare their performance to unmodulated pulses and linear FM pulses with comparable time-bandwidth products. Comparisons will be made in terms of key performance metrics, including sidelobe levels, Doppler tolerance, resolution, performance in the presence of noise and EM interference. This study will initially be carried out using theoretical simulations, with the findings then verified using a software-defined dual channel transceiver.
Project team
Project students
- Wong Ming Eer
- Shalin Shah
Supervisors
- Brian Ng
- Dr Waddah Al-Ashwal (SRC Australia)
Advisors
Objectives
Creating radar waveform using Matlab to understand the basic principals.
Background
Radar is an acronym of Radio Detection and Ranging and the system emits EM waves. The basic principle of the radar system is to find and position a target and determine the distance between the target and transmitting antenna.
Motivation
The problem of detecting small targets is challenging especially with a heavy clutter background. We aim to exploit waveform agility by tailoring the transmit waveform to have a second look on the target location to suppress the range bins with heavy clutter. An alternative method using mismatch filter was explored and implemented on the received signal to suppress sidelobes if waveform agility is not feasible.
The agile waveform would suppress range bins with high clutter while the mismatch filter would instead be suppressing overall sidelobes. From both implementations, we would aim to decrease the false alarm rate and improve the detection performance.
Adaptive Waveform Design
With a high scanning rate and very short duration pulses, we assume the clutter returns are stationary over timescales of hundreds of milliseconds. With an ocean surface with a small target, we would be able to identify range bins of the strong sea wave corresponding to the target and perform suppression.
The diagrams below show the match filter output of the transmit waveform post suppression.
Conclusion
In this project, the agile waveform allows the suppressed energy to be transferred to the other sidelobes which has weaker clutter response while the mismatch filter averages out the sidelobes at the cost of the main peak. The mismatch filter performs well when its length is greater than the length of the transmit waveform. We could identify and filter out specific clutter patterns using the agile waveform. However, the mismatch filter would be more suitable in conditions of distributed clutters with weak targets.
More work would be put into computing the computational costs and investigating the performance of both implementations in simulation and real life.
References
[1] a, b, c, "Simple page", In Proceedings of the Conference of Simpleness, 2010.
