A High-Order Imaging Algorithm for High-Resolution Space-Borne SAR Based on a Modified Equivalent Squint Range Model

Two challenges have been faced in signal processing of ultrahigh-resolution spaceborne synthetic aperture radar (SAR). The first challenge is constructing a precise range model, and the second one is to develop an efficient imaging algorithm since traditional algorithms fail to process ultrahigh-resolution spaceborne SAR data effectively. In this paper, a novel high-order imaging algorithm for high-resolution spaceborne SAR is presented. First, a modified equivalent squint range model (MESRM) is developed by introducing equivalent radar acceleration into the equivalent squint range model, and it is more suitable for high-resolution spaceborne SAR. The signal model based on the MESRM is also presented. Second, a novel high-order imaging algorithm is derived. The insufficient pulse-repetition frequency problem is solved by an improved subaperture method, and accurate focusing is achieved through an extended hybrid correlation algorithm. Simulations are performed to validate the presented algorithm

An imaging algorithm for spaceborne high-squint L-band SAR based on time-domain rotation

For spaceborne high-squint L-band synthetic aperture radar (SAR), the long wavelength and high-squint angle result in strong coupling between the range and azimuth directions. In conventional imaging algorithms, linear range walk correction (LRWC) is commonly used to correct linear range cell migration which dominates the coupling. However, LRWC introduces spatial variation in the azimuth direction, limits the depth-of-azimuth-focus (DOAF) and affects the imaging quality. This article constructs a polynomial range model and develops a modified omega-k algorithm to achieve spaceborne high-squint L-band SAR imaging. The key to this algorithm is to rotate the two-dimensional (2-D) data after LRWC in the time domain by a proposed time-rotation (TR) operation that eliminates the DOAF degradation caused by LRWC. The proposed algorithm, which is composed of LRWC, bulk compression, TR, and modified Stolt interpolation, achieves well-focused results at a 1-m resolution and a swath of 4 km × 4 km at a squint angle of 45°

Generalized Processing for Pulsed Synthetic Aperture Radar

The Range-Doppler Algorithm (RDA) and the Chirp-Scaling Algorithm (CSA) process Synthetic Aperture Radar (SAR) data with approximations to ideal SAR processing. These approximations are invalid for data from systems with wide bandwidths, large bandwidths, and/or low center frequencies. While simple and efficient, these frequency-domain methods are thus limited by the SAR parameters. This paper explores these limits and proposes a generalized chirp-scaling approach for extending the utility of frequency-domain processing. We demonstrate how different order approximations of the SAR signal in the two-dimensional frequency domain affect image focusing for varying SAR parameters. From these results, a guideline is set forth which suggests the required order of approximation terms for proper focusing. A proposed generalized frequency-domain processing approach is derived. This method is an efficient arbitrary-order chirp-scaling algorithm that processes the data using the appropriate number of approximation terms. The new method is demonstrated using simulated data

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)

Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms

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Imaging Formation Algorithm of the Ground and Space-Borne Hybrid BiSAR Based on Parameters Estimation from Direct Signal

This paper proposes a novel image formation algorithm for the bistatic synthetic aperture radar (BiSAR) with the configuration of a noncooperative transmitter and a stationary receiver in which the traditional imaging algorithm failed because the necessary imaging parameters cannot be estimated from the limited information from the noncooperative data provider. In the new algorithm, the essential parameters for imaging, such as squint angle, Doppler centroid, and Doppler chirp-rate, will be estimated by full exploration of the recorded direct signal (direct signal is the echo from satellite to stationary receiver directly) from the transmitter. The Doppler chirp-rate is retrieved by modeling the peak phase of direct signal as a quadratic polynomial. The Doppler centroid frequency and the squint angle can be derived from the image contrast optimization. Then the range focusing, the range cell migration correction (RCMC), and the azimuth focusing are implemented by secondary range compression (SRC) and the range cell migration, respectively. At last, the proposed algorithm is validated by imaging of the BiSAR experiment configured with china YAOGAN 10 SAR as the transmitter and the receiver platform located on a building at a height of 109 m in Jiangsu province. The experiment image with geometric correction shows good accordance with local Google images

A Beam-Segmenting Polar Format Algorithm Based on Double PCS for Video SAR Persistent Imaging

Video synthetic aperture radar (SAR) is attracting more attention in recent years due to its abilities of high resolution, high frame rate and advantages in continuous observation. Generally, the polar format algorithm (PFA) is an efficient algorithm for spotlight mode video SAR. However, in the process of PFA, the wavefront curvature error (WCE) limits the imaging scene size and the 2-D interpolation affects the efficiency. To solve the aforementioned problems, a beam-segmenting PFA based on principle of chirp scaling (PCS), called BS-PCS-PFA, is proposed for video SAR imaging, which has the capability of persistent imaging for different carrier frequencies video SAR. Firstly, an improved PCS applicable to video SAR PFA is proposed to replace the 2-D interpolation and the coarse image in the ground output coordinate system (GOCS) is obtained. As for the distortion or defocus existing in the coarse image, a novel sub-block imaging method based on beam-segmenting fast filtering is proposed to segment the image into multiple sub-beam data, whose distortion and defocus can be ignored when the equivalent size of sub-block is smaller than the distortion negligible region. Through processing the sub-beam data and mosaicking the refocused subimages, the full image in GOCS without distortion and defocus is obtained. Moreover, a three-step MoCo method is applied to the algorithm for the adaptability to the actual irregular trajectories. The proposed method can significantly expand the effective scene size of PFA, and the better operational efficiency makes it more suitable for video SAR imaging. The feasibility of the algorithm is verified by the experimental data

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

Time domain synthetic aperture radar image processing using fast factorised backprojection

Includes bibliographical references (leaves 114-115).Fast Factorised Backprojection(FFBP) is a Synthetic Aperture Radar (SAR) focusing technique which uses Filtered Backprojection(FBP) to produce high quality images in the spatial domain at speeds which rival spectral domain SAR focusing methods. Synthetic Aperture Radar (SAR) focusing is fundamentally a matched filtering process which can be performed both in the spatial or spectral domain. Spatial domain SAR focusing techniques like filtered backprojection can, in theory, completely recover the scene from data with an infinite bandwidth acquired using an isotropic antenna along an arbitrary curved flight path of infinite length. This means that the focusing of a image using filtered backprojection is only limited by a finite bandwidth, non isotropic beam width and a finite flight path length. However filtered backprojection with an operation count which is proportional to 0 (n3 ) is computationally inefficient in speed when compared to the frequency domain SAR image reconstruction algorithms with an operational count which is proportional to 0 (n2 10g (n))