Guevara Díaz, Sergio A. (2020) Estudio e implementación en unidades de procesamiento gráficos GPU S de un formador de imagen SAR usando técnica de backprojection / Study and implementation on graphics processing units GPUs for SAR image formation using the backprojection algorithm. Proyecto Integrador Ingeniería en Telecomunicaciones, Universidad Nacional de Cuyo, Instituto Balseiro.
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| PDF (Tesis) Español 20Mb |
Resumen en español
El algoritmo Backprojection en el domino temporal fue presentado como una simple pero efectiva técnica para enfocar imágenes SAR sin hacer ninguna suposición, siendo capaz de procesar datos de cualquier modo de adquisición SAR y realizar compensación de movimiento de forma natural en el mismo algoritmo. Su principal desventaja es su carga computacional de O(N"3), convirtiéndolo en una opción lenta y no conveniente para implementar en procesamiento serial. Sin embargo, dado el constante avance tecnológico de las unidades de procesamiento gráfico de propósito general (GPGPU) que permite programación en paralelo, ahora es posible considerar la inclusión del Backprojection en el conjunto típico de algoritmos de formación de imágenes SAR. Este proyecto se enfoca en entender los fundamentos de las adquisiciones SAR y en la implementación del algoritmo Backprojection en una GPU NVIDIA T4 para procesamiento en tierra y en tiempo real. En este documento se presenta de forma gráfica e intuitiva las bases teóricas del Backprojection. Dos métodos de interpolación en rango fueron propuestos, el primero es un sobremuestreo de los ecos recibidos y el segundo es un interpolador Sinc. Con ambos métodos se logro reducir los lóbulos secundarios de la respuesta en acimut. Se encontró que si la cantidad de memoria de la GPU no es un factor limitante entonces efectuar un sobremuestreo es mas eficiente, de no ser así, el interpolador Sinc logra su cometido a cambio de un tiempo de procesamiento superior. Se aplico una ventana Kaiser de parámetro β = 2,5 en la compresión en rango, logrando reducir los lóbulos secundarios de la respuesta desde una PSLR de -13 dB hasta -20 dB. Se integro una rutina de compensación de movimiento en el mismo Backprojection y exitosamente se lograron corregir errores de enfoque debido a trayectorias no ideales de la plataforma SAR. Se implemento con la librera OpenCV un post procesamiento de imágenes dedicado a corregir deformaciones geométricas debido a adquisiciones con squint y a espaciamientos en rangos no constantes, además de esto se aplico una ecualización de histograma adaptativo de contraste limitado y un ltro de mediana para reducir speckle noise del producto nal. Finalmente, se presenta la implementación de un procesador en tiempo real Backprojection. Para lograr la velocidad de procesamiento requerida, la versión básica del algoritmo sin la interpolación ni compensation de movimiento fue ejecutada. Para probar esta rutina se realizo una simulación y se obtuvieron resultados satisfactorios, sin embargo aun se necesita una interfaz real con instrumentos SAR. El algoritmo fue escrito en Python y CUDA/C usando la librera CuPy, Para probar el algoritmo se simularon bancos puntuales con el simulador de INVAP, SIDRA y también se usaron datos reales del proyecto SARAT proporcionados por CONAE.
Resumen en inglés
Time domain Backprojection was presented as a basic yet effective algorithm to focus SAR images, being able to process data from any type of SAR imaging mode and perform motion compensation naturally in the same algorithm. The downside of this technique is it's O(N"3) computational complexity, making it a slow non convenient option to perform in serial processing. However, due to the constantly increasing technology of General-Purpose Graphics Processing Units (GPGPU), which allows parallel programming, it is now possible to consider the inclusion of the Backprojection in the every day SAR image formation algorithms. This project focusses on understanding the basics of SAR data acquisitions and in the implementation of the Backprojection algorithm on a GPU NVIDIA T4 for offline and real time data processing. In this document, an intuitive and graphical interpretation of the Backprojection's theory is presented. Two methods of signal interpolation in range were proposed, the first one is the digital upsampling of the echoed signals and the second one is a Sinc interpolator. Both methods achieved a reduction in the secondary lobes of the acimut response. It was found that if GPU memory storage is not a limiting factor then performing an upsampling is more ecient, if thats not the case, then the Sinc interpolation can do the job at the expense of an increased processing time. The kaiser window with parameter β = 2,5 was applied on the range compression, suppressing secondary lobes from the range response from a PSLR of -13 dB to -20 dB. A motion compensation routine integrated on the same Backprojection algorithm is presented, successfully correcting focusing errors given a non ideal motion of the SAR platform. An image post processing processing dedicated to correct geometrical deformations such as squinted geometries and non constant range steps was implemented using the OpenCV library, as well as a Contrast Limited Adaptive Histogram Equalization and a median filter to reduce the speckle noise on the nal product. Finally, an implementation of a real time Backprojection processing was presented. In order to achieve the processing speed needed, the basic version of the Backprojection algorithm without interpolation nor motion compensation was executed. To test this routine a simulation was carried over with successful results, nevertheless a real interface with external SAR instruments is still required. The algorithm is written on Python and CUDA/C using the CuPy library. To test the algorithm, simulations of point targets were done with the INVAP's SIDRA simulator and also, real data from the SARAT project provided from CONAE was used. The real data was taken in between Cordoba and Falda del Carmen, Argentina.
| Tipo de objeto: | Tesis (Proyecto Integrador Ingeniería en Telecomunicaciones) |
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| Palabras Clave: | Radar; [Backprojection algorithm; Algoritmo backprojection; SAR imaging; Imágenes SAR] |
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A back-projection autofocus algorithm based on ight trajectory optimization for synthetic aperture radar imaging. Multidimensional Systems and Signal Processing, 27 (2), 411{431, 2016. 76 |
| Materias: | Ingeniería en telecomunicaciones > Procesamiento digital de señales |
| Divisiones: | Gcia. de área de Investigación y aplicaciones no nucleares > Laboratorio de investigación aplicada en Telecomunicaciones |
| Código ID: | 910 |
| Depositado Por: | Marisa G. Velazco Aldao |
| Depositado En: | 28 Abr 2021 09:39 |
| Última Modificación: | 28 Abr 2021 09:45 |
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