Examples of current radar technology and applications, chapter 5, part B

Basic principles and tradeoff considerations for SLAR are summarized. There are two fundamental types of SLAR sensors available to the remote sensing user: real aperture and synthetic aperture. The primary difference between the two types is that a synthetic aperture system is capable of significant improvements in target resolution but requires equally significant added complexity and cost. The advantages of real aperture SLAR include long range coverage, all-weather operation, in-flight processing and image viewing, and lower cost. The fundamental limitation of the real aperture approach is target resolution. Synthetic aperture processing is the most practical approach for remote sensing problems that require resolution higher than 30 to 40 m

Advanced Multi-Channel SAR Imaging - Measured Data Demonstration

Synthetic Aperture Radar (SAR) is a well-established technique for remote sensing of the Earth. However, conventional SAR systems relying on only a single transmit and receive aperture are not capable of imaging a wide swath with high spatial resolution. Multi-channel SAR concepts, such as systems based on multiple receive apertures in azimuth, promise to overcome these restrictions, thus enabling high-resolution wide-swath imaging. Analysis revealed that these systems imperatively require sophisticated digital processing of the received signals in order to guarantee full performance independently of the spatial sample distribution imposed by the applied pulse repetition frequency (PRF). A suitable algorithm to cope with these challenges of multi-channel data is given by the “multi-channel reconstruction algorithm”, which demonstrated in comprehensive analysis and system design examples its potential for high perform-ance SAR imaging. In this context, various optimization strategies were investigated and aspects of operating multi-channel systems in burst modes such as ScanSAR or TOPS were discussed. Furthermore, a first proof-of-principle showed the algorithm’s applicability to measured multi-channel X-band data gathered by the German Aerospace Cen-ter’s (DLR) airborne F-SAR system. As a next step in the framework of multi-channel azimuth processing, this paper builds on the results recalled above and continues two paths. Firstly, focus is turned to further optimization of the proc-essing algorithm by investigating the classical Space-Time Adaptive Processing (STAP) applied to SAR. Secondly, attention is turned to the analysis of the measured multi-channel data by elaborating the impact and compensation of channel mismatch and by verifying the derived theory

Time Domain SAR Processing with GPUs for Airborne Platforms

A time-domain backprojection processor for airborne synthetic aperture radar (SAR) has been developed at the University of Massachusetts’ Microwave Remote Sensing Lab (MIRSL). The aim of this work is to produce a SAR processor capable of addressing the motion compensation issues faced by frequency-domain processing algorithms, in order to create well focused SAR imagery suitable for interferometry. The time-domain backprojection algorithm inherently compensates for non-linear platform motion, dependent on the availability of accurate measurements of the motion. The implementation must manage the relatively high computational burden of the backprojection algorithm, which is done using modern graphics processing units (GPUs), programmed with NVIDIA’s CUDA language. An implementation of the Non-Equispaced Fast Fourier Transform (NERFFT) is used to enable efficient and accurate range interpolation as a critical step of the processing. The phase of time- domain processed imagery is dif erent than that of frequency-domain imagery, leading to a potentially different approach to interferometry. This general purpose SAR processor is designed to work with a novel, dual-frequency S- and Ka-band radar system developed at MIRSL as well as the UAVSAR instrument developed by NASA’s Jet Propulsion Laboratory. These instruments represent a wide range of SAR system parameters, ensuring the ability of the processor to work with most any airborne SAR. Results are presented from these two systems, showing good performance of the processor itself

InSAR Simulations for SWOT and Dual Frequency Processing for Topographic Measurements

In Earth remote sensing precise characterization of the backscatter coefficient is important to extract valuable information about the observed target. A system that eliminates platform motion during near-nadir airborne observations is presented in this thesis, showing an improvement on the accuracy of measurements for a Ka- band scatterometer previously developed at Microwave Remote Sensing Laboratory (MIRSL). These very same results are used to simulate the reflectivity of such targets as seen from a spaceborne radar and estimate height errors based on mission-specific geometry. Finally, data collected from a dual-frequency airborne interferometer com- prised by the Ka-band system and an S-band radar is processed and analyzed to estimate forest heights