Yang Chen, Li Bingyi, Chen Liang, Wei Chunpeng, Xie Yizhuang, Chen He, Yu Wenyue
Beijing Key Laboratory of Embedded Real-time Information Processing Technology, Beijing Institute of Technology, Beijing 100081, China.
Sensors (Basel). 2017 Jun 24;17(7):1493. doi: 10.3390/s17071493.
With the development of satellite load technology and very large scale integrated (VLSI) circuit technology, onboard real-time synthetic aperture radar (SAR) imaging systems have become a solution for allowing rapid response to disasters. A key goal of the onboard SAR imaging system design is to achieve high real-time processing performance with severe size, weight, and power consumption constraints. In this paper, we analyse the computational burden of the commonly used chirp scaling (CS) SAR imaging algorithm. To reduce the system hardware cost, we propose a partial fixed-point processing scheme. The fast Fourier transform (FFT), which is the most computation-sensitive operation in the CS algorithm, is processed with fixed-point, while other operations are processed with single precision floating-point. With the proposed fixed-point processing error propagation model, the fixed-point processing word length is determined. The fidelity and accuracy relative to conventional ground-based software processors is verified by evaluating both the point target imaging quality and the actual scene imaging quality. As a proof of concept, a field- programmable gate array-application-specific integrated circuit (FPGA-ASIC) hybrid heterogeneous parallel accelerating architecture is designed and realized. The customized fixed-point FFT is implemented using the 130 nm complementary metal oxide semiconductor (CMOS) technology as a co-processor of the Xilinx xc6vlx760t FPGA. A single processing board requires 12 s and consumes 21 W to focus a 50-km swath width, 5-m resolution stripmap SAR raw data with a granularity of 16,384 × 16,384.
随着卫星载荷技术和超大规模集成电路(VLSI)技术的发展,机载实时合成孔径雷达(SAR)成像系统已成为实现对灾害快速响应的一种解决方案。机载SAR成像系统设计的一个关键目标是在严格的尺寸、重量和功耗限制下实现高实时处理性能。在本文中,我们分析了常用的chirp缩放(CS)SAR成像算法的计算负担。为了降低系统硬件成本,我们提出了一种部分定点处理方案。快速傅里叶变换(FFT)是CS算法中计算量最大的操作,采用定点处理,而其他操作采用单精度浮点处理。利用所提出的定点处理误差传播模型,确定了定点处理字长。通过评估点目标成像质量和实际场景成像质量,验证了相对于传统地面软件处理器的保真度和准确性。作为概念验证,设计并实现了一种现场可编程门阵列-专用集成电路(FPGA-ASIC)混合异构并行加速架构。定制的定点FFT采用130nm互补金属氧化物半导体(CMOS)技术实现,作为Xilinx xc6vlx760t FPGA的协处理器。单个处理板聚焦50公里测绘带宽度、5米分辨率条带图SAR原始数据(粒度为16384×16384)需要12秒,功耗为21瓦。