An Improved Back-Projection Algorithm for GNSS-R BSAR Imaging Based on CPU and GPU Platform

Wu, Songping; Xu, Zhichao; Wang, Rui; Yang, Dongkai; Guo, Gongjian

doi:10.3390/rs13112107

Cited by 12 publications

(8 citation statements)

References 38 publications

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“…In the experiment, the total observation duration of the target by the receiving system was 145 s. The experiment validated the effectiveness of using target echo signals and performing azimuthal Fourier transform to achieve large-scale maritime target detection (Ma et al, 2017). Zhou et al (2019) and Wu et al (2021b) from Beihang University carried out a GNSS bistatic SAR imaging, while the receiving station was placed on the chairman's platform of a 3 m high football stadium, and the building in the university was used as the imaging area. Finally, azimuth phase compensation and geometric correction were carried out (Fig.…”

Section: Target Detectionmentioning

confidence: 72%

Remote sensing and its applications using GNSS reflected signals: advances and prospects

Jin,

Camps,

Jia

et al. 2024

Satell Navig

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The Global Navigation Satellite Systems (GNSS), including the US’s GPS, China’s BDS, the European Union’s Galileo, and Russia’s GLONASS, offer real-time, all-weather, any-time, anywhere and high precision observations by transmitting L band signals continuously, which have been widely used for positioning, navigation and timing. With the development of GNSS technology, it has been found that GNSS-reflected signals can be used to detect Earth’s surface characteristics together with other signals of opportunity. In this paper, the current status and latest advances are presented on Global Navigation Satellite System-Reflectometry (GNSS-R) in theory, methods, techniques and observations. New developments and progresses in GNSS-R instruments, theoretical modeling, and signal processing, ground and space-/air-borne experiments, parameters retrieval (e.g. wind speed, sea surface height, soil moisture, ice thickness), sea surface altimetry and applications in the atmosphere, oceans, land, vegetation, and cryosphere are given and reviewed in details. Meanwhile, the challenges in the GNSS-R development of each field are also given. Finally, the future applications and prospects of GNSS-R are discussed, including multi-GNSS reflectometry, new GNSS-R receivers, GNSS-R missions, and emerging applications, such as mesoscale ocean eddies, ocean phytoplankton blooms, microplastics detection, target recognition, river flow, desert studies, natural hazards and landslides monitoring.

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Section: Target Detectionmentioning

confidence: 72%

Remote sensing and its applications using GNSS reflected signals: advances and prospects

Jin,

Camps,

Jia

et al. 2024

Satell Navig

Self Cite

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“…F3 of the non-overlapped mode as the reference for comparison. The GPU accelerated BPA architectures in references [20] and [23] are 1.49 and 1.13 times slower than the proposed Arch. F3 with non-overlapped aperture processing.…”

Section: Discussionmentioning

confidence: 96%

“…Conventional studies on GPU-based BPA acceleration have mainly presented the imaging time and speed-up ratio after acceleration as performance measures [20,23], but these studies did not perform comparative studies with the previous literature of different GPU computing and SAR imaging environments.…”

Section: Discussionmentioning

confidence: 99%

“…When receive and transmit antennas are separated, as in passive or bistatic SAR configuration, the platform motion should be compensated with high precision and it is preferred to divide processing data into multiple blocks. Then, parallel BPA processing can be easily adopted to accelerate for real-time processing and SAR image generation [18][19][20]. This advantage of BPA has motivated many studies that accelerate the BPA in recent decades.…”

Section: Introductionmentioning

confidence: 99%

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Architecture Exploration of a Backprojection Algorithm for Real-Time Video SAR

Lee

Ban

Lee

et al. 2021

Sensors

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This paper explores novel architectures for fast backprojection based video synthetic aperture radar (BP-VISAR) with multiple GPUs. The video SAR frame rate is analyzed for non-overlapped and overlapped aperture modes. For the parallelization of the backprojection process, a processing data unit is defined as the phase history data or range profile data from partial synthetic-apertures divided from the full resolution target data. Considering whether full-aperture processing is performed and range compression or backprojection are parallelized on a GPU basis, we propose six distinct architectures, each having a single-stream pipeline with a single GPU. The performance of these architectures is evaluated in both non-overlapped and overlapped modes. The efficiency of the BP-VISAR architecture with sub-aperture processing in the overlapped mode is accelerated further by filling the processing gap from the idling GPU resources with multi-stream based backprojection on multiple GPUs. The frame rate of the proposed BP-VISAR architecture with sub-aperture processing is scalable with the number of GPU devices for large pixel resolution. It can generate 4096 × 4096 video SAR frames of 0.5 m cross-range resolution in 23.0 Hz on a single GPU and 73.5 Hz on quad GPUs.

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“…The representative timedomain imaging algorithm is the backprojection (BP) algorithm. For each pixel in the imaging grid, the coherent integration along the range migration trajectory is carried out to realize the focusing of scattering points [14]. BP has simple structure and high robustness, which can be applied to different SAR configurations.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Backprojection Algorithm Based on Wavenumber-Domain Spectral Splicing for Monostatic and Bistatic SAR Configurations

Sun

Chen

et al. 2022

Remote Sensing

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This paper introduces a fast backprojection synthetic aperture radar (SAR) imaging algorithm based on wavenumber-domain spectral splicing. The traditional fast backprojection (FBP) algorithm establishes the polar coordinate system with the center of the sub-aperture as the origin. Therefore, the coordinates of the image obtained from each sub-aperture are different. Sub-aperture images must be projected to a uniform coordinate system before they can be coherently superimposed to form the final image, which requires a large amount of calculation. In order to deal with this problem, this paper proposes a novel imaging method, which uses the same polar coordinate system for each sub-aperture. The sub-aperture images are then spliced in the wavenumber-domain, and directly added after upsampling. This method avoids the projection from each sub-aperture to the uniform coordinate system, thus improving the imaging accuracy and efficiency. At the same time, the algorithm is suitable for various configurations, and can achieve good imaging results for bistatic forward-looking SAR and high-speed mobile platform. Finally, simulations are presented to demonstrate the effectiveness of the algorithm.

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An Improved Back-Projection Algorithm for GNSS-R BSAR Imaging Based on CPU and GPU Platform

Cited by 12 publications

References 38 publications

Remote sensing and its applications using GNSS reflected signals: advances and prospects

Remote sensing and its applications using GNSS reflected signals: advances and prospects

Architecture Exploration of a Backprojection Algorithm for Real-Time Video SAR

An Efficient Backprojection Algorithm Based on Wavenumber-Domain Spectral Splicing for Monostatic and Bistatic SAR Configurations

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