Synthetic Aperture Radar (SAR) has been widely used for Earth remote sensing for more than 30 years. It provides high-resolution, day-and-night and weather-independent images for a multitude of applications ranging from geoscience and climate change research, environmental and Earth system monitoring, 2-D and 3-D mapping, change detection, 4-D mapping (space and time), security-related applications up to planetary exploration. With the advances in radar technology and geo/bio-physical parameter inversion modeling in the 90s, using data from several airborne and spaceborne systems, a paradigm shift occurred from the development driven by the technology push to the user demand pull. Today, more than 15 spaceborne SAR systems are being operated for innumerous applications. This paper provides first a tutorial about the SAR principles and theory, followed by an overview of established techniques like polarimetry, interferometry and differential interferometry as well as of emerging techniques (e.g., polarimetric SAR interferometry, tomography and holographic tomography). Several application examples including the associated parameter inversion modeling are provided for each case. The paper also describes innovative technologies and concepts like digital beamforming, Multiple-Input Multiple-Output (MIMO) and bi- and multi-static configurations which are suitable means to fulfill the increasing user requirements. The paper concludes with a vision for SAR remote sensing.

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A tutorial on synthetic aperture radar

Synthetic aperture radar (SAR) is a coherent active microwave imaging method. In remote sensing it is used for mapping the scattering properties of the Earth's surface in the respective wavelength domain. Many physical and geometric parameters of the imaged scene contribute to the grey value of a SAR image pixel. Scene inversion suffers from this high ambiguity and requires SAR data taken at different wavelength, polarization, time, incidence angle, etc. Interferometric SAR (InSAR) exploits the phase differences of at least two complex-valued SAR images acquired from different orbit positions and/or at different times. The information derived from these interferometric data sets can be used to measure several geophysical quantities, such as topography, deformations (volcanoes, earthquakes, ice fields), glacier flows, ocean currents, vegetation properties, etc. This paper reviews the technology and the signal theoretical aspects of InSAR. Emphasis is given to mathematical imaging models and the statistical properties of the involved quantities. Coherence is shown to be a useful concept for system description and for interferogram quality assessment. As a key step in InSAR signal processing two-dimensional phase unwrapping is discussed in detail. Several interferometric configurations are described and illustrated by real-world examples. A compilation of past, current and future InSAR systems concludes the paper.

https://iopscience.iop.org/article/10.1088/0266-5611/14/4/001/pdf

Synthetic aperture radar interferometry

A space-variant interpolation is required to compensate for the migration of signal energy through range resolution cells when processing synthetic aperture radar (SAR) data, using either the classical range/Doppler (R/D) algorithm or related frequency domain techniques. In general, interpolation requires significant computation time, and leads to loss of image quality, especially in the complex image. The new chirp scaling algorithm avoids interpolation, yet performs range cell migration correction accurately. The algorithm requires only complex multiplies and Fourier transforms to implement, is inherently phase preserving, and is suitable for wide-swath, large-beamwidth, and large-squint applications. This paper describes the chirp scaling algorithm, summarizes simulation results, presents imagery processed with the algorithm, and reviews quantitative measures of its performance. Based on quantitative comparison, the chirp scaling algorithm provides image quality equal to or better than the precision range/Doppler processor. Over the range of parameters tested, image quality results approach the theoretical limit, as defined by the system bandwidth. >

Precision SAR processing using chirp scaling

The focusing of synthetic-aperture-radar (SAR) data using migration techniques quite similar to those used in geophysics is treated. The algorithm presented works in the omega -k/sub x/ domain. Because time delays can be easily accommodated with phase shifts that increase linearly with omega , range migration poses no problem. The algorithm is described in plane geometry first, where range migration and phase history can be exactly matched. The effects of the sphericity of the Earth, of the Earth's rotation, and of the satellite trajectory curvature are taken into account, showing that the theoretically achievable spatial resolution is well within the requirements of present day and near future SAR missions. Terrestrial swaths as wide as 100 km can be focused simultaneously with no serious degradation. The algorithm has been tested with synthetic data, with Seasat-A data, and with airplane data (NASA-AIR). The experimental results fully support the theoretical analysis. >

SAR data focusing using seismic migration techniques

Focusing of SAR data requires a space-variant two-dimensional correlation. Different algorithms are compared with each other in terms of their focusing quality and their ability to handle the space-variance of the correlation kernel: the range-Doppler approach with and without secondary range compression, modified range-Doppler algorithms, and four versions of the wavenumber domain processor. The phase aberrations of the different algorithms are given in analytic form. Numerical examples are presented for Seasat and ERS-1. A novel systems theoretical derivation of the wavenumber domain algorithm is presented. >

A comparison of range-Doppler and wavenumber domain SAR focusing algorithms

Problems in the determination of Doppler parameters for spaceborne synthetic-aperture radar (SAR) data processing are examined. The degradations in image quality due to errors in these parameters are summarized. We show that these parameters can be estimated using accurate spacecraft ancillary data. In cases where such data are not available, we propose two techniques to estimate these parameters using the coherent radar return. These techniques were tested with the Seasat SAR data and the test results demonstrate that the accuracies achieved exceed the system performance requirements. Possible applications of these techniques in other areas of SAR data utilization are briefly discussed.

Doppler Parameter Estimation for Spaceborne Synthetic-Aperture Radars

This paper presents an algorithm for azimuth correlation of synthetic aperture radar (SAR) data with extraordinarily large-range migration which cannot be accommodated by the existing frequency domain interpolation approach used in current Seasat SAR processing. We first provide a mathematical model for the SAR range-correlated point-target response both in the spatial and frequency domains. A simple and efficient processing algorithm derived from the exact two-dimensional correlation algorithm is given. This algorithm enables azimuth correlation by two cascaded one-dimensional correlation steps. The first step is to transform the range-correlated SAR data into the frequency domain in azimuth, followed by a newly developed range convolution filter to correct the range-dispersed spectrum of the range-correlated point-target response (RCPTR). The second step is the frequency-domain range migration correction approach for the azimuth compression. Simulation results provided here indicate that this processing algorithm yields a satisfactory compressed impulse response for SAR data with large-range migration whereas previous methods were subject to a broadening of the impulse response along range.

A SAR correlation algorithm which accommodates large-range migration

SeaWinds is a spaceborne wind scatterometer to be flown on the second Japanese Advanced Earth Observing Satellite (ADEOS-II) in 1999. An important international element of NASA's Earth Observing System (EOS), SeaWinds is an advanced follow-on to the NASA scatterometer (NSCAT) on the first ADEOS platform. Unlike previous operational spaceborne scatterometer systems. SeaWinds employs a scanning "pencil-beam" antenna rather than a "fan-beam" antenna, making the instrument more compact and yielding greater ocean coverage. The goals of this paper are twofold. First, the overall SeaWinds functional design and backscatter measurement approach are described, and the relative advantages of the pencil-beam technique are outlined. Second, the unique aspects of measurement accuracy optimization and signal processing for the SeaWinds instrument are discussed. Applying the results of a separate companion paper, ibid., 1997, a technique to significantly improve measurement accuracy by modulating the transmit pulse is described. Trade-offs to optimize the transmit modulation bandwidth are presented.

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Tradeoffs in the design of a spaceborne scanning pencil beam scatterometer: application to SeaWinds

The SeaWinds instrument is the first "pencilbeam" scatterometer to routinely measure ocean surface winds from space. Developed to fly on-board the Japanese ADEOS-II mission, the first flight of SeaWinds was moved up several years when the ADEOS-I satellite carrying the NASA Scatterometer (NSCAT) failed. Utilizing only a one year development time, a dedicated small spacecraft was purchased and the SeaWinds spare hardware was adapted for flight. The SeaWinds on QuikSCAT mission was successfully launched on June 19, 1999. The QuikSCAT mission, the SeaWinds instrument, and the SeaWinds ground data processing are briefly described.

SeaWinds on QuikSCAT: sensor description and mission overview

This paper presents a digital signal processing system that produces the SEASAT synthetic-aperture radar (SAR) imagery. The system consists of a SEL 32/77 host minicomputer and three AP-120B array processors. The partitioning of the SAR processing functions and the design of softwae modules is described. The rationale for selecting the parallel array processor architecture and the methodology for developing the parallel processing scheme on this system is described. This system attains a SEASAT SAR data reduction speed of 2.5 h per 25-m resolution 4-look and 100 km X 100 km image frame. A prelininary performance evaluation of this parallel processing system and potential future applications for remote sensing data reduction are described.

Chialin Wu

Papers

Doppler Parameter Estimation for Spaceborne Synthetic-Aperture Radars

A SAR correlation algorithm which accommodates large-range migration

Tradeoffs in the design of a spaceborne scanning pencil beam scatterometer: application to SeaWinds

SeaWinds on QuikSCAT: sensor description and mission overview

Seasat Synthetic-Aperture Radar Data Reduction Using Parallel Programmable Array Processors