Abstract: Staggered SAR technology improves imaging performance by employing non-uniform pulse repetition interval (PRI) sequences. However, existing sequence designs are insufficient in optimizing the uniformity of blind-zone distribution. To address this, this paper proposes an improved discrete particle swarm optimization (DAPSO) algorithm accelerated by GPU. First, a discrete model conforming to the hardware timing quantization and smoothness constraints of spaceborne systems is established, and the blind-zone evaluation is accelerated using a GPU parallel architecture. Then, with the core objectives of minimizing blind-zone clustering and maximizing distribution uniformity, the algorithm is guided to search for generate PRI sequences with low blind-zone ratios and highly dispersed blind-zone distributions. Simulations demonstrate that, compared with conventional linear and unconstrained random sequences, the proposed sequence achieves more uniform blind-zone distribution and lower data loss rates, thereby significantly enhancing scene integrity and the detection capability of weak targets in strong clutter backgrounds.

Key words: Staggered SAR, PRI sequence design, particle swarm optimization, blind-zone suppression, non-uniform sampling