Processing of Sliding Spotlight and TOPS SAR Data Using Baseband Azimuth Scaling

This paper presents an efficient phase preserving processor for the focusing of data acquired in sliding spotlight and TOPS (Terrain Observation by Progressive Scans) imaging modes. They share in common a linear variation of the Doppler centroid along the azimuth dimension, which is due to a steering of the antenna (either mechanically or electronically) throughout the data take. Existing approaches for the azimuth processing can become inefficient due to the additional processing to overcome the folding in the focused domain. In this paper a new azimuth scaling approach is presented to perform the azimuth processing, whose kernel is exactly the same for sliding spotlight and TOPS modes. The possibility to use the proposed approach to process ScanSAR data, as well as a discussion concerning staring spotlight, are also included. Simulations with point-targets and real data acquired by TerraSAR-X in sliding spotlight and TOPS modes are used to validate the developed algorithm

Простой алгоритм компенсации миграций светящихся точек по дальности для режима бокового обзора РСА (англ.)

Introduction.  Range Cell Migration (RCM) is a source of image blurring in synthetic aperture radars (SAR). There are two groups of signal processing algorithms used to compensate for migration effects. The first group includes algorithms that recalculate the SAR signal from the "along–track range – slant range" coordinate system into the "along-track range  –  cross-track range"  coordinates using the method of interpolation. The disadvantage of these algorithms is their considerable computational cost. Algorithms of the second group do not rely on interpolation thus being more attractive in terms of practical application.Aim. To synthesize a simple algorithm for compensating for RCM without using interpolation.Materials and methods. The synthesis was performed using a simplified version of the Chirp Scaling algorithm.Results.  A simple algorithm, which presents a modification of the Keystone Transform algorithm, was synthesized. The synthesized algorithm based on Fast Fourier Transforms and the Hadamard matrix products does not require interpolation.Conclusion. A verification of the algorithm quality via mathematical simulation confirmed its high efficiency. Implementation of the algorithm permits the number of computational operations to be reduced. The final radar image  produced using the proposed algorithm is built in the true Cartesian coordinates. The algorithm can be applied for SAR imaging of moving targets. The conducted analysis showed that the algorithm yields  the  image of a moving target provided that the coherent processing interval is sufficiently large. The image lies along a line, which angle of inclination is proportional to the projection of the target relative velocity on the line-of-sight. Estimation of the image parameters permits the target movement parameters to be determined.Введение. Миграции светящихся точек по дальности являются источником расфокусировки радиолокационных изображений в радиолокаторах с синтезированной апертурой (РСА). Существует две группы алгоритмов обработки сигналов для компенсации миграций. Первая группа включает алгоритмы, в которых на основании методов функциональной интерполяции осуществляется пересчет принятых сигналов из системы координат "продольная дальность – наклонная дальность"  в систему "продольная дальность – поперечная дальность". Недостатком алгоритмов данной группы является их высокая вычислительная сложность. Алгоритмы второй группы не используют интерполяционные методы и являются поэтому более привлекательными для практического использования.Цель.  Синтезировать простой алгоритм компенсации миграций без применения функциональной интерполяции.Материалы и методы. Синтез алгоритма осуществлен на основании упрощенной версии алгоритма ЛЧМ-фильтрации (Chirp Scaling Algorithm).Результаты. Синтезирован простой алгоритм, являющийся модификацией алгоритма "замкового камня".Алгоритм основан на использовании быстрых преобразований Фурье и поэлементных матричных умножений. В алгоритме не применяются методы интерполяции.Заключение. Проверка качества алгоритма на основе математического моделирования подтвердила его высокую эффективность. Использование алгоритма позволяет уменьшить количество вычислительных операций.Финальное радиолокационное изображение, получаемое с помощью алгоритма, строится в  истинной декартовой системе координат. Алгоритм может быть применен для построения РСА изображений движущихся целей. Данный в статье анализ показал, что алгоритм позволяет построить хорошо сфокусированное изображение движущейся цели, когда интервал синтезирования достаточно велик. Изображение движущейся цели выстраивается вдоль отрезка прямой, угол наклона которой пропорционален проекции относительной скорости цели на линию визирования. Оценка параметров изображения позволяет определить параметры движения цели

Factorized Geometrical Autofocus for Synthetic Aperture Radar Processing

Synthetic Aperture Radar (SAR) imagery is a very useful resource for the civilian remote sensing community and for the military. This however presumes that images are focused. There are several possible sources for defocusing effects. For airborne SAR, motion measurement errors is the main cause. A defocused image may be compensated by way of autofocus, estimating and correcting erroneous phase components. Standard autofocus strategies are implemented as a separate stage after the image formation (stand-alone autofocus), neglecting the geometrical aspect. In addition, phase errors are usually assumed to be space invariant and confined to one dimension. The call for relaxed requirements on inertial measurement systems contradicts these criteria, as it may introduce space variant phase errors in two dimensions, i.e. residual space variant Range Cell Migration (RCM). This has motivated the development of a new autofocus approach. The technique, termed the Factorized Geometrical Autofocus (FGA) algorithm, is in principle a Fast Factorized Back-Projection (FFBP) realization with a number of adjustable (geometry) parameters for each factorization step. By altering the aperture in the time domain, it is possible to correct an arbitrary, inaccurate geometry. This in turn indicates that the FGA algorithm has the capacity to compensate for residual space variant RCM. In appended papers the performance of the algorithm is demonstrated for geometrically constrained autofocus problems. Results for simulated and real (Coherent All RAdio BAnd System II (CARABAS II)) Ultra WideBand (UWB) data sets are presented. Resolution and Peak to SideLobe Ratio (PSLR) values for (point/point-like) targets in FGA and reference images are similar within a few percents and tenths of a dB. As an example: the resolution of a trihedral reflector in a reference image and in an FGA image respectively, was measured to approximately 3.36 m/3.44 m in azimuth, and to 2.38 m/2.40 m in slant range; the PSLR was in addition measured to about 6.8 dB/6.6 dB. The advantage of a geometrical autofocus approach is clarified further by comparing the FGA algorithm to a standard strategy, in this case the Phase Gradient Algorithm (PGA)

A review of synthetic-aperture radar image formation algorithms and implementations: a computational perspective

Designing synthetic-aperture radar image formation systems can be challenging due to the numerous options of algorithms and devices that can be used. There are many SAR image formation algorithms, such as backprojection, matched-filter, polar format, Range–Doppler and chirp scaling algorithms. Each algorithm presents its own advantages and disadvantages considering efficiency and image quality; thus, we aim to introduce some of the most common SAR image formation algorithms and compare them based on these two aspects. Depending on the requisites of each individual system and implementation, there are many device options to choose from, for in stance, FPGAs, GPUs, CPUs, many-core CPUs, and microcontrollers. We present a review of the state of the art of SAR imaging systems implementations. We also compare such implementations in terms of power consumption, execution time, and image quality for the different algorithms used.info:eu-repo/semantics/publishedVersio