Noise Radar Waveform Design: Preliminary Results for a MOEA Approach

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.