Highly Resolved Synthetic Aperture Radar with Beam Steering

The present work deals with a highly resolved radar with a synthetic aperture (synthetic aperture radar - SAR), which uses a beam steering to improve performance. The first part of this work deals with the influence of various effects occurring in the hardware of the High-Resolution Wide-Swath SAR (HRWS SAR) system. A special focus was set to single bit quantization in multi-channel receiver. The second part of this work describes SAR processors for Sliding Spotlight mode

Highly Resolved Synthetic Aperture Radar with Beam Steering

Diese Arbeit beschäftigt sich mit einem hochauflösenden Radar mit synthetischer Apertur. Der erste Teil dieser Arbeit beschreibt mögliche Auswirkungen verschiedener Effekte in dem Empfänger des High-Resolution Wide-Swath SAR (HRWS SAR) Systems. Darüber hinaus wird ein Konzept zu Reduktion von Quantisierungsbits in Systemen mit mehreren Empfangskanälen untersucht. Der zweite Teil der Arbeit betrifft die Datenverarbeitung eines hochauflösenden SAR-Systems in Sliding Spotlight Mode

High-Temporal-Resolution High-Spatial-Resolution Spaceborne SAR Based on Continuously Varying PRF

Synthetic Aperture Radar (SAR) is a well-established and powerful imaging technique for acquiring high-spatial-resolution images of the Earth's surface. With the development of beam steering techniques, sliding spotlight and staring spotlight modes have been employed to support high-spatial-resolution applications. In addition to this strengthened high-spatial-resolution and wide-swath capability, high-temporal-resolution (short repeat-observation interval) represents a key capability for numerous applications. However, conventional SAR systems are limited in that the same patch can only be illuminated for several seconds within a single pass. This paper considers a novel high-squint-angle system intended to acquire high-spatial-resolution spaceborne SAR images with repeat-observation intervals varying from tens of seconds to several minutes within a single pass. However, an exponentially increased range cell migration would arise and lead to a conflict between the receive window and 'blind ranges'. An efficient data acquisition technique for high-temporal-resolution, high-spatial-resolution and high-squint-angle spaceborne SAR, in which the pulse repetition frequency (PRF) is continuously varied according to the changing slant range, is presented in this paper. This technique allows echo data to remain in the receive window instead of conflicting with the transmitted pulse or nadir echo. Considering the precision of hardware, a compromise and practical strategy is also proposed. Furthermore, a detailed performance analysis of range ambiguities is provided with respect to parameters of TerraSAR-X. For strong point-like targets, the range ambiguity of this technique would be better than that of uniform PRF technique. For this innovative technique, a resampling strategy and modified imaging algorithm have been developed to handle the non-uniformly sampled echo data. Simulations are performed to validate the efficiency of the proposed technique and the associated imaging 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°

Extension of Wavenumber Domain Focusing for spotlight COSMO-SkyMed SAR Data

In this work we describe a method to handle curved orbits in wavenumber domain focusing algorithm for high-resolution SAR data acquired by Low Earth Orbit satellites using spotlight mode. The stand..

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

Theory and Design of a Highly Compressed Dropped-Channel Polarimetric Synthetic Aperture Radar

Compressed sensing (CS) is a recent mathematical technique that leverages the sparsity in certain sets of data to solve an underdetermined system and recover a full set of data from a sub-Nyquist set of measurements of the data. Given the size and sparsity of the data, radar has been a natural choice to apply compressed sensing to, typically in the fast-time and slow-time domains. Polarimetric synthetic aperture radar (PolSAR) generates a particularly large amount of data for a given scene; however, the data tends to be sparse. Recently a technique was developed to recover a dropped PolSAR channel by leveraging antenna crosstalk information and using compressed sensing. In this dissertation, we build upon the initial concept of the dropped-channel PolSAR CS in three ways. First, we determine a metric which relates the measurement matrix to the l2 recovery error. The new metric is necessary given the deterministic nature of the measurement matrix. We then determine a range of antenna crosstalk required to recover a dropped PolSAR channel. Second, we propose a new antenna design that incorporates the relatively high levels of crosstalk required by a dropped-channel PolSAR system. Finally, we integrate fast- and slow-time compression schemes into the dropped-channel model in order to leverage sparsity in additional PolSAR domains and overall increase the compression ratio. The completion of these research tasks has allowed a more accurate description of a PolSAR system that compresses in fast-time, slow-time, and polarization; termed herein as highly compressed PolSAR. The description of a highly compressed PolSAR system is a big step towards the development of prototype hardware in the future

Phase History Decomposition for Efficient Scatterer Classification in SAR Imagery

A new theory and algorithm for scatterer classification in SAR imagery is presented. The automated classification process is operationally efficient compared to existing image segmentation methods requiring human supervision. The algorithm reconstructs coarse resolution subimages from subdomains of the SAR phase history. It analyzes local peaks in the subimages to determine locations and geometric shapes of scatterers in the scene. Scatterer locations are indicated by the presence of a stable peak in all subimages for a given subaperture, while scatterer shapes are indicated by changes in pixel intensity. A new multi-peak model is developed from physical models of electromagnetic scattering to predict how pixel intensities behave for different scatterer shapes. The algorithm uses a least squares classifier to match observed pixel behavior to the model. Classification accuracy improves with increasing fractional bandwidth and is subject to the high-frequency and wide-aperture approximations of the multi-peak model. For superior computational efficiency, an integrated fast SAR imaging technique is developed to combine the coarse resolution subimages into a final SAR image having fine resolution. Finally, classification results are overlaid on the SAR image so that analysts can deduce the significance of the scatterer shape information within the image context

Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms

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