【摘要】 SAR实时成像处理系统的定点化优化能够减小系统存储规模、提高系统运算速度,是降低系统功耗、减小系统规模、提高实时性的有效方法.本文以CS成像算法为例,分析并统计了算法的运算量,针对其核心运算——FFT进行了定点化优化,选择基-22FFT算法,设计了合理的定标策略.采用SystemC语言对整个SAR成像系统进行了系统级快速仿真和验证,真实模拟了FPGA系统的实现结果.对16 384×16 384大小的点阵数据和面目标数据采用24bits的字长进行了成像仿真,仿真结果满足系统指标要求.更多还原

【Abstract】 Fixed-point processing optimization can reduce the storage,improve the computing speed,is an effective way to reduce power consumption and storage,improve the real-time performance of synthetic aperture radar(SAR)real-time imaging system.Taking the well-known chirp scaling(CS)algorithm as example,the count of computations was analyzed in this paper.Radix-22 algorithm of fast Fourier transform(FFT)as the main part of computations was adopted for fixed-point processing optimization,realized through a reasonable scale strategy with SystemC.Thus rapid system-level simulation of CS algorithm was implemented to provide a standard basis for FPGA implementation.Finally,test images from the raw lattice and area target data(16 384×16 384)were analyzed using fixed-point CS algorithm with 24 bits input word lengths.The simulation results meet the requirements of system indicators.更多还原