Airborne Spaceborne Synthetic Aperture Radar Research Articles

Accurate Range Modeling for High-Resolution Spaceborne Synthetic Aperture Radar.

Spaceborne synthetic aperture radar (SAR) is an advanced microwave imaging technology that provides all-weather and all-day target information. However, as spaceborne SAR resolution improves, traditional echo signal models based on airborne SAR design become inadequate due to the curved orbit, Earth rotation, and increased propagation distance. In this study, we propose an accurate range model for high-resolution spaceborne SAR by analyzing motion trajectory and Doppler parameters from the perspective of the space geometry of spaceborne SAR. We evaluate the accuracy of existing range models and propose an advanced equivalent squint range model (AESRM) that accurately fits the actual range history and compensates for high-order term errors by introducing third-order and fourth-order error terms while maintaining the simplicity of the traditional model. The proposed AESRM's concise two-dimensional frequency spectrum form facilitates the design of imaging algorithms. Point target simulations confirm the effectiveness of the proposed AESRM, demonstrating significant improvements in fitting accuracy for range histories characterized by nonlinear trajectories. The developed AESRM provides a robust foundation for designing imaging algorithms and enables higher resolution and more accurate radar imaging.

Dynamic Predictive Quantization for Staggered SAR: Experiments With Real Data

Present and future spaceborne synthetic aperture radar (SAR) missions are designed to acquire an increasingly large amount of onboard data. This is a consequence of the use of large bandwidths, multiple polarizations, and the acquisition of large swath widths at fine spatial resolutions, which result in challenging requirements in terms of onboard memory and downlink capacity. In this scenario, SAR raw data quantization represents an essential aspect, as it affects the volume of data to be stored and transmitted to the ground as well as the quality of the resulting SAR products. Dynamic predictive block-adaptive quantization (DP-BAQ) is a novel technique, recently proposed by the authors, consisting of a low-complexity data compression method, and its application is particularly suitable for staggered SAR systems. DP-BAQ exploits the existing correlation among the azimuth raw data samples by applying linear predictive coding (LPC). This results in a data rate reduction of up to 25% with respect to state-of-the-art SAR quantization methods. In this letter, we test and validate the potential of DP-BAQ on airborne SAR data which emulates the system scenario of Tandem-L, a German Aerospace Center (DLR) mission proposal for a bistatic L-band system. For this purpose, an experimental SAR image has been acquired at the L-band by the airborne DLR flugzeug-SAR (F-SAR) sensor over the Kaufbeuren area, in Southern Germany. In order to simulate the staggered SAR acquisition mode, we implemented a dedicated resampling and filtering of the data. Our analyses confirm the effectiveness of DP-BAQ for efficient data volume reduction, exhibiting a consistent and promising performance when tested on areas characterized by different land cover types and backscatter statistics.

A High-Resolution, Wide-Swath SAR Imaging System Based on Tandem SAR Satellites.

For the spaceborne synthetic aperture radar (SAR), it is difficult to obtain high resolution and wide width at the same time. This paper proposes a novel imaging system based on tandem SAR satellites, where one obtains coarse resolution and wide swath by the scanning mode, and the other obtains the undersampled echo from the same swath. The high resolution is achieved by associating the tandem SARs’ echo and using the minimum-energy-based algorithm. Finally, a high-resolution wide-swath SAR system is designed, and its imaging performance is verified by simulated data and real airborne SAR data.

Motion Compensation/Autofocus in Airborne Synthetic Aperture Radar: A Review

Air- and spaceborne synthetic aperture radar (SAR) can provide a large number of high-resolution images for microwave remote sensing applications, such as geoscience and climate change research, environmental Earth system monitoring, and precision agriculture. Unlike spaceborne SAR, the flight trajectory of airborne SAR may deviate from its ideal straight course due to the influence of atmospheric turbulence, resulting in significant motion errors in radar raw data. If a standard imaging algorithm is directly used to process the data, the image focusing quality will be significantly degraded. Therefore, to improve image focusing quality, one typically needs to integrate standard imaging algorithms with an effective motion compensation (MoCo)/autofocus technique. In this article, we present a comprehensive overview of MoCo/autofocus methods for airborne SAR to articulate related research and promote further development.

An Efficient Polyphase Filter-Based Resampling Method for Unifying the PRFs in SAR Data

Variable higher pulse repetition frequencies (PRFs) are increasingly being used to meet the stricter requirements and complexities of current airborne and spaceborne synthetic aperture radar (SAR) systems associated with higher resolution and wider area products. POLYPHASE , the proposed resampling scheme, downsamples and unifies variable PRFs within a single look complex SAR acquisition and across a repeat pass sequence of acquisitions down to an effective lower PRF. A sparsity condition of the received SAR data ensures that the uniformly resampled data approximate the spectral properties of a decimated densely sampled version of the received SAR data. While experiments conducted with both synthetically generated and real airborne SAR data show that POLYPHASE retains comparable performance with the state-of-the-art best linear unbiased interpolation scheme in image quality, a polyphase filter-based implementation of POLYPHASE offers significant computational savings for arbitrary (not necessarily periodic) input PRF variations, thus allowing fully on-board, in-place, and real-time implementation.

Mapping Palaeohydrography in Deserts: Contribution from Space-Borne Imaging Radar

Space-borne Synthetic Aperture Radar (SAR) has the capability to image subsurface features down to several meters in arid regions. A first demonstration of this capability was performed in the Egyptian desert during the early eighties, thanks to the first Shuttle Imaging Radar mission. Global coverage provided by recent SARs, such as the Japanese ALOS/PALSAR sensor, allowed the mapping of vast ancient hydrographic systems in Northern Africa. We present a summary of palaeohydrography results obtained using PALSAR data over large deserts such as the Sahara and the Gobi. An ancient river system was discovered in eastern Lybia, connecting in the past the Kufrah oasis to the Mediterranean Sea, and the terminal part of the Tamanrasett river was mapped in western Mauritania, ending with a large submarine canyon. In southern Mongolia, PALSAR images combined with topography analysis allowed the mapping of the ancient Ulaan Nuur lake. We finally show the potentials of future low frequency SAR sensors by comparing L-band (1.25 GHz) and P-band (435 MHz) airborne SAR acquisitions over a desert site in southern Tunisia.

High resolution 3-D imaging via multi-pass SAR

Spaceborne/airborne synthetic aperture radar (SAR) systems provide high resolution two-dimensional terrain imagery. The paper proposes a technique for combining multiple SAR images, acquired on flight paths slightly separated in the elevation direction, to generate high resolution three-dimensional imagery. The technique could be viewed as an extension to interferometric SAR (InSAR) in that it generates topographic imagery with an additional dimension of resolution. The 3-D multi-pass SAR imaging system is typically characterised by a relatively short ambiguity length in the elevation direction. To minimise the associated ambiguities we exploit the relative phase information within the set of images to track the terrain landscape. The SAR images are then coherently combined, via a nonuniform DFT, over a narrow (in elevation) volume centred on the 'dominant' terrain ground plane. The paper includes a detailed description of the technique, background theory, including achievable resolution, and the results of an experimental study.

The analysis of backscattering properties from SAR data of mountain regions

Possibilities and problems for the extraction of backscattering coefficients from airborne and spaceborne Synthetic Aperture Radar (SAR) data are discussed. Corrections for system errors and for imaging geometry are described. Examples are given for airborne SAR data acquired in the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">X</tex> - and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</tex> -bands over a test site in the Austrian Alps and for Seasat SAR data of glacierized areas in Iceland. From these data, backscattering coefficients have been derived on a relative scale for wet snow, glacier ice, and several ice-free surfaces. Data of in situ measurements on surface roughness and on dielectric parameters are presented for interpretation purposes and as the basis for backscatter modeling. The SAR-derived results are compared with theoretical backscattering calculations which were based on the Kirchhoff model for surface scattering and on the Born approximation for snow volume scattering.