ISAR imaging algorithm for micro-motion target with sparse aperture based on joint optimization of nuclear norm and information entropy

Key Points

• The aim is to develop a robust ISAR imaging algorithm that addresses challenges from micro-motion targets under sparse aperture conditions.
• Proposed a joint optimization approach using nuclear norm and information entropy based on signal models and motion characteristics.
• Applied robust principal component analysis for effective image processing.
• Utilized a projection transformation after separation to generate high-quality ISAR images.
• Operated under conditions of constrained radar resources and complex target movements.
• Successfully achieved high-precision separation of micro-motion signals and target imageries.
• Demonstrated improved imaging quality compared to traditional methods.
• Verified effectiveness through simulation and real measurement data.