Onboard Processing of Synthetic Aperture Radar Backprojection Algorithm in FPGA

Autor: David Mota, Helena Cruz, Pedro R. Miranda, Rui Policarpo Duarte, Jose T. de Sousa, Horacio C. Neto, Mario P. Vestias
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 3600-3611 (2022)
Druh dokumentu: article
ISSN: 2151-1535
DOI: 10.1109/JSTARS.2022.3169828
Popis: Synthetic aperture radar is a microwave technique to extracting image information of the target. Electromagnetic waves that are reflected from the target are acquired by the aircraft or satellite receivers and sent to a ground station to be processed by applying computational demanding algorithms. Radar data streams are acquired by an aircraft or satellite and sent to a ground station to be processed in order to extract images from the data since these processing algorithms are computationally demanding. However, novel applications require real-time processing for real-time analysis and decisions and so onboard processing is necessary. Running computationally demanding algorithms on onboard embedded systems with limited energy and computational capacity is a challenge. This article proposes a configurable hardware core for the execution of the backprojection algorithm with high performance and energy efficiency. The original backprojection algorithm is restructured to expose computational parallelism and then optimized by replacing floating-point with fixed-point arithmetic. The backprojection core was integrated into a system-on-chip architecture and implemented in a field-programmable gate array. The proposed solution runs the optimized backprojection algorithm over images of sizes $512\times 512$ and $1024\times 1024$ in 0.14 s (0.41 J) and 1.11 s (3.24 J), respectively. The architecture is $2.6\times$ faster and consumes $13\times$ less energy than an embedded Jetson TX2 GPU. The solution is scalable and, therefore, a tradeoff exists between performance and utilization of resources.
Databáze: Directory of Open Access Journals