Side lobe suppression for polyphase codes in radar

Radar systems rely on effective sidelobe suppression to concentrate energy on the primary lobe, ensuring accurate target detection and minimizing false identifications. Reducing sidelobe levels improves the radar system's capacity to detect weak or far-off objects by helping it differentiate between real targets and background noise. This paper focuses on improving radar signal processing by suppressing side lobes in polyphase codes, which are commonly used in radar systems for pulse compression and waveform design. To address this, in this paper a novel hybrid optimisation approach has been proposed combining Particle Swarm Optimization (PSO) and the Grey Wolf Optimization (GWO) to design polyphase codes with significantly reduced sidelobes. This approach combines the global search efficiency of PSO with the local refinement capabilities of GWO, achieving superior sidelobe suppression while preserving resolution and detection accuracy. The suggested method has been evaluated in regard to suppression effectiveness and computational efficiency by simulating the various optimisation techniques in MATLAB, demonstrating its superiority over traditional windowing techniques and single optimisation algorithms like the genetic algorithm. This novel approach enhances radar performance by reducing interference, improving target discrimination, and increasing resilience against jamming, making it a robust solution for modern radar applications.