Optimizing PN-Sequences with Genetic Algorithm for SAR Waveform Diversity

Raito Suzuki, Akira Hirose, Ryo Natsuaki

Abstract: Waveform diversity is an important technique to extend the observation coverage of synthetic aperture radar (SAR) without sacrificing spatial resolution and power consumption. Applying pseudorandom noise sequence (PN-sequence) to frequency modulation chirp (FM chirp) pulses is one of the possible solutions. In this paper, we propose to optimize the PN-sequence with a genetic algorithm (GA) to improve the range ambiguity suppression in SAR images of multiple swaths compared to the existing M-sequence. The imaging simulations show that the proposed method succeed in separating range ambiguous signals from multiple swaths and suppressing range ambiguity by 24.9 to 25.3 dB compared to the case using FM chirp pulse alone.