TY - GEN
T1 - A SoPC based Fixed Point System for Spaceborne SAR Real-Time Imaging Processing
AU - Li, Bingyi
AU - Li, Changjin
AU - Xie, Yizhuang
AU - Chen, Liang
AU - Shi, Hao
AU - Deng, Yi
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/11/26
Y1 - 2018/11/26
N2 - 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 facilitated rapid response to disasters. The state-of-the-art System-on-Programmable-Chip (SoPC) technique, associated with embedded processor and other function modules, provides a potential solution to satisfy all constraints. However, with the improvement of processing efficiency and imagery granularity, to implement an entire SAR imaging processing using floating-point arithmetic is unaffordable. Data fixed-pointing is an effective solution, and the core issue is the finite word length optimization under the condition of trading-off hardware resource and processing precision. In this paper, we analyze the finite word length computing error for SAR imaging system using Chirp Scaling (CS) algorithm, and propose a mathematical computing error model. Then, the empirical formula of the system's output noise-to-signal ratio is derived. Guiding by the software simulation result, we implement and verify the proposed method into a Zynq+NetFPGA platform. The run-time results show that the proposed method can achieve a decent image quality assessed by Integrated Side Lobe Ratio (ISLR), Peak Side Lobe Ratio (PSLR) and Relative Mean Square Deviation (RMSD).
AB - 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 facilitated rapid response to disasters. The state-of-the-art System-on-Programmable-Chip (SoPC) technique, associated with embedded processor and other function modules, provides a potential solution to satisfy all constraints. However, with the improvement of processing efficiency and imagery granularity, to implement an entire SAR imaging processing using floating-point arithmetic is unaffordable. Data fixed-pointing is an effective solution, and the core issue is the finite word length optimization under the condition of trading-off hardware resource and processing precision. In this paper, we analyze the finite word length computing error for SAR imaging system using Chirp Scaling (CS) algorithm, and propose a mathematical computing error model. Then, the empirical formula of the system's output noise-to-signal ratio is derived. Guiding by the software simulation result, we implement and verify the proposed method into a Zynq+NetFPGA platform. The run-time results show that the proposed method can achieve a decent image quality assessed by Integrated Side Lobe Ratio (ISLR), Peak Side Lobe Ratio (PSLR) and Relative Mean Square Deviation (RMSD).
KW - FPGA
KW - Finite Word Length
KW - Fixed-point Analysis
KW - Synthetic Aperture Radar (SAR) Imaging
UR - http://www.scopus.com/inward/record.url?scp=85060090809&partnerID=8YFLogxK
U2 - 10.1109/HPEC.2018.8547564
DO - 10.1109/HPEC.2018.8547564
M3 - Conference contribution
AN - SCOPUS:85060090809
T3 - 2018 IEEE High Performance Extreme Computing Conference, HPEC 2018
BT - 2018 IEEE High Performance Extreme Computing Conference, HPEC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE High Performance Extreme Computing Conference, HPEC 2018
Y2 - 25 September 2018 through 27 September 2018
ER -