Radar systems have obtained a lot of attention in
recent years since they can operate in a variety of weather
conditions and their applications are innumerable, ranging from
automotive and marine radar to imaging or health monitoring
purposes. Hence, noise radars have become a viable substitute
for traditional radar technology, particularly in the defence
domain. These systems excel for its resistance to jamming,
low mutual interference and low probability of interception.
However, the nature of non-deterministic sequences introduce
several challenges such as fluctuations in the range sidelobes of
the autocorrelation function, causing it to have a high sidelobe
level, which can mask targets of interest. This paper introduces
the use of Multi Objective Evolutionary Algorithms (MOEAs) to
design noise radar waveforms with good correlation properties
while maintaining an adequate efficiency at the power amplifier.