Processing of Airborne Video SAR Data Using the Modified Back Projection Algorithm

Cheng, Yu; Ding, Jian; Sun, Zhenrong; Zhong, Chao

doi:10.1109/tgrs.2022.3220643

Cited by 19 publications

(3 citation statements)

References 25 publications

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“…The Taylor approximation is used for Equation (12) to approximate the neighborhood of (x, y, z) = (0, 0, 0) for a function called R t . In this case, R t − R a is defined as…”

Section: Polar-format Algorithmmentioning

confidence: 99%

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FPGA-Based Acceleration of Polar-Format Algorithm for Video Synthetic-Aperture Radar Imaging

Jeong,

Lee,

Lee

et al. 2024

Electronics

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This paper presents a polar-format algorithm (PFA)-based synthetic-aperture radar (SAR) processor that can be mounted on a small drone to support video SAR (ViSAR) imaging. For drone mounting, it requires miniaturization, low power consumption, and high-speed performance. Therefore, to meet these requirements, the processor design was based on a field-programmable gate array (FPGA), and the implementation results are presented. The proposed PFA-based SAR processor consists of both an interpolation unit and a fast Fourier transform (FFT) unit. The interpolation unit uses linear interpolation for high speed while occupying a small space. In addition, the memory transfer is minimized through optimized operations using SAR system parameters. The FFT unit uses a base-4 systolic array architecture, chosen from among various fast parallel structures, to maximize the processing speed. Each unit is designed as a reusable block (IP core) to support reconfigurability and is interconnected using the advanced extensible interface (AXI) bus. The proposed PFA-based SAR processor was designed using Verilog-HDL and implemented on a Xilinx UltraScale+ MPSoC FPGA platform. It generates an image 2048 × 2048 pixels in size within 0.766 s, which is 44.862 times faster than that achieved by the ARM Cortex-A53 microprocessor. The speed-to-area ratio normalized by the number of resources shows that it achieves a higher speed at lower power consumption than previous studies.

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“…The Taylor approximation is used for Equation (12) to approximate the neighborhood of (x, y, z) = (0, 0, 0) for a function called R t . In this case, R t − R a is defined as…”

Section: Polar-format Algorithmmentioning

confidence: 99%

“…More recently, researchers have been working on creating videos from multiple images generated in real time using SAR. Video SAR (ViSAR) observes dynamic targets by surveilling the target area and generating images at a high frame rate [8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

FPGA-Based Acceleration of Polar-Format Algorithm for Video Synthetic-Aperture Radar Imaging

Jeong,

Lee,

Lee

et al. 2024

Electronics

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show abstract

“…Unfortunately, the SAR has certain limitations in detecting moving targets [1][2][3][4][5]. Compared to the conventional SAR, the video SAR (ViSAR) can perform high-framerate imaging and monitoring of the target area, obtaining dynamic observation effects of the area [6][7][8][9][10]. The unmanned aerial vehicle (UAV)-borne ViSAR has great application potential [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

An Embedded-GPU-Based Scheme for Real-Time Imaging Processing of Unmanned Aerial Vehicle Borne Video Synthetic Aperture Radar

Yang,

Zhang,

et al. 2024

Remote Sensing

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The UAV-borne video SAR (ViSAR) imaging system requires miniaturization, low power consumption, high frame rates, and high-resolution real-time imaging. In order to satisfy the requirements of real-time imaging processing for the UAV-borne ViSAR under limited memory and parallel computing resources, this paper proposes a method of embedded GPU-based real-time imaging processing for the UAV-borne ViSAR. Based on a parallel programming model of the compute unified device architecture (CUDA), this paper designed a parallel computing method for range-Doppler (RD) and map drift (MD) algorithms. By utilizing the advantages of the embedded GPU characterized with parallel computing, we improved the processing speed of real-time ViSAR imaging. This paper also adopted a unified memory management method, which greatly reduces data replication and communication latency between the CPU and the GPU. The data processing of 2048 × 2048 points took only 1.215 s on the Jetson AGX Orin platform to form a nine-consecutive-frame image with a resolution of 0.15 m, with each frame taking only 0.135 s, enabling real-time imaging at a high frame rate of 5 Hz. In actual testing, continuous mapping can be achieved without losing the scenes, intuitively obtaining the dynamic observation effects of the area. The processing results of the measured data have verified the reliability and effectiveness of the proposed scheme, satisfying the processing requirements for real-time ViSAR imaging.

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Multiple knowledge embedding for few-shot object detection

Gong

Cai

Wang

2023

SIViP

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Processing of Airborne Video SAR Data Using the Modified Back Projection Algorithm

Cited by 19 publications

References 25 publications

FPGA-Based Acceleration of Polar-Format Algorithm for Video Synthetic-Aperture Radar Imaging

FPGA-Based Acceleration of Polar-Format Algorithm for Video Synthetic-Aperture Radar Imaging

An Embedded-GPU-Based Scheme for Real-Time Imaging Processing of Unmanned Aerial Vehicle Borne Video Synthetic Aperture Radar

Multiple knowledge embedding for few-shot object detection

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