LPI MIMO Noise Radar Waveform Design: A Near Real-Time Algorithm

In recent years, several advantages of noise radars have positioned this technology as a promising alternative to conventional radar technology. Immunity to jamming, low mutual interference, and low probability of intercept are important examples of these advantages. However, noise radar systems are based on random sequences, which introduce several issues, such as fluctuations in the range sidelobes of the autocorrelation function causing high sidelobe levels. Moreover, given the increasing frequency of use, e.g., in autonomous driving applications [1], and the need to have different optimized noise waveforms, real-time sequence generation is crucial. This paper proposes an accelerated algorithm optimized to design noise radar waveforms vectorized with advanced vector extensions (AVX), and parallelized with OpenMP to be implemented on an Intel processor. This algorithm designs waveforms with good autocorrelation properties, low peak-to-average power ratio (PAPR), and low negentropy .