Parallel processing of sliding spotlight mode SAR imaging based on GPU

Abstract

Sliding spotlight synthetic aperture radar (SAR) is a hot imaging mode in space-borne SAR. It can acquire high-resolution and large azimuth scene size simultaneously. The main challenges for sliding spotlight SAR processing in real time are the huge volume of raw data and complex imaging algorithm. The rapid development of the graphics processing units (GPUs) provides a new computing platform for high-performance SAR processing. This work presents a parallel processing of sliding spotlight SAR imaging algorithm on GPU via compute unified device architecture and tests the speedup of each module of the algorithm on the K20c GPU platform from the aspect of a small granularity and a large granularity of point target images. Compared with traditional CPU-based SAR imaging technology, the proposed GPU-based sliding spotlight SAR imaging obtains a speedup of 186.80 when processing data with a granularity of 16,384 × 8192 and gets a speedup of 49.72 when processing data with a granularity of 65,536 × 32,768, thereby greatly improving the real-time imaging processing.

Keywords

• radar imaging
• graphics processing units
• image processing
• parallel processing
• synthetic aperture radar
• spaceborne radar
• real-time imaging processing
• gpu-based
• traditional cpu-based sar imaging technology
• point target images
• granularity
• compute unified device architecture
• high-performance sar processing
• computing platform
• graphics processing units
• complex imaging algorithm
• spotlight sar processing
• azimuth scene size
• space-borne sar
• hot imaging mode
• spotlight synthetic aperture radar
• spotlight mode sar imaging
• parallel processing