Citation: Cao, Y.; Guo, S.; Jiang, S.;
Zhou, X.; Wang, X.; Luo, Y.; Yu, Z.;
Zhang, Z.; Deng, Y. Parallel
Optimisation and Implementation of
a Real-Time Back Projection (BP)
Algorithm for SAR Based on FPGA.
Sensors 2022, 22, 2292. https://
doi.org/10.3390/s22062292
Academic Editor: Andrzej Stateczny
Received: 18 February 2022
Accepted: 13 March 2022
Published: 16 March 2022
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Article
Parallel Optimisation and Implementation of a Real-Time Back
Projection (BP) Algorithm for SAR Based on FPGA
Yue Cao
1,2,
* , Shuchen Guo
1
, Shuai Jiang
1
, Xuan Zhou
1
, Xiaobei Wang
1
, Yunhua Luo
1,2
, Zhongjun Yu
1,2
,
Zhimin Zhang
1,2
and Yunkai Deng
1,2
1
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China;
laneruoyi@163.com (S.G.); jiangshuai@aircas.ac.cn (S.J.); zhouxuan@aircas.ac.cn (X.Z.);
wangxb@aircas.ac.cn (X.W.); luoyh@aircas.ac.cn (Y.L.); yuzj@aircas.ac.cn (Z.Y.); zmzhang@mail.ie.ac.cn (Z.Z.);
ykdeng@mail.ie.ac.cn (Y.D.)
2
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences,
Beijing 101408, China
* Correspondence: yuecao0927@hotmail.com; Tel.: +86-185-0139-9627
Abstract:
This study conducts an in-depth evaluation of imaging algorithms and software and hard-
ware architectures to meet the capability requirements of real-time image acquisition systems, such
as spaceborne and airborne synthetic aperture radar (SAR) systems. By analysing the principles and
models of SAR imaging, this research creatively puts forward the fully parallel processing architecture
for the back projection (BP) algorithm based on Field-Programmable Gate Array (FPGA). The pro-
cessing time consumption has significant advantages compared with existing methods. This article
describes the BP imaging algorithm, which stands out with its high processing accuracy and two-
dimensional decoupling of distance and azimuth, and analyses the algorithmic flow, operation, and
storage requirements. The algorithm is divided into five core operations: range pulse compression,
upsampling, oblique distance calculation, data reading, and phase accumulation. The architecture
and optimisation of the algorithm are presented, and the optimisation methods are described in detail
from the perspective of algorithm flow, fixed-point operation, parallel processing, and distributed
storage. Next, the maximum resource utilisation rate of the hardware platform in this study is found
to be more than 80%, the system power consumption is 21.073 W, and the processing time efficiency
is better than designs with other FPGA, DSP, GPU, and CPU. Finally, the correctness of the processing
results is verified using actual data. The experimental results showed that 1.1 s were required to
generate an image with a size of 900
×
900 pixels at a 200 MHz clock rate. This technology can solve
the multi-mode, multi-resolution, and multi-geometry signal processing problems in an integrated
manner, thus laying a foundation for the development of a new, high-performance, SAR system for
real-time imaging processing.
Keywords:
synthetic aperture radar (SAR); back-projection algorithm (BP);
real-time image processing;
field-programmable gate array (FPGA)
1. Introduction
In the past decade, advances in digital and microwave technologies have led to the
leap-forward development of synthetic aperture radar (SAR) with significant improve-
ments in the device capability, system design, and processing algorithm. However, the
SAR image generation and information processing link cannot match the SAR capability
improvement to achieve the most efficient remote sensing information acquisition capa-
bility. The traditional remote sensing, SAR information acquisition process comprises the
following: planning the platform flight routes and radar operation modes, collecting and
recording radar echo data from the ground area using SAR radar, returning, copying, or
uninstalling echo data, importing the data to ground high-performance computing devices,
processing data with an algorithm, achieving the result, and forwarding the results to
Sensors 2022, 22, 2292. https://doi.org/10.3390/s22062292 https://www.mdpi.com/journal/sensors
