2,384 research outputs found
An introduction to the interim digital SAR processor and the characteristics of the associated Seasat SAR imagery
Basic engineering data regarding the Interim Digital SAR Processor (IDP) and the digitally correlated Seasat synthetic aperature radar (SAR) imagery are presented. The correlation function and IDP hardware/software configuration are described, and a preliminary performance assessment presented. The geometric and radiometric characteristics, with special emphasis on those peculiar to the IDP produced imagery, are described
Chaos-Based Coffee Can Radar System
Linear frequency modulated (LFM) radar systems are simple and easy to implement, making them ideal for inexpensive undergraduate research projects. Unfortunately, LFM radar schemes have multiple limitations that make them unviable in many real-world applications. Given the limitations of LFM radar systems, we propose a chaos-based frequency modulated (CBFM) system. In this paper, we present the theory, design, and experimental verification of a CBFM radar system that has both ranging and synthetic aperture radar imaging capabilities. The performance of our CBFM system is compared to that of the LFM system designed by MIT. We document many challenges and unforeseen obstacles that were encountered while developing one of the first CBFM radar systems. Although our initial results look promising, particularly for ranging, there remains a significant amount of research and development to be done on the SAR imaging signal processing software algorithms before a CBFM radar scheme is fully functional
Synthetic aperture radar/LANDSAT MSS image registration
Algorithms and procedures necessary to merge aircraft synthetic aperture radar (SAR) and LANDSAT multispectral scanner (MSS) imagery were determined. The design of a SAR/LANDSAT data merging system was developed. Aircraft SAR images were registered to the corresponding LANDSAT MSS scenes and were the subject of experimental investigations. Results indicate that the registration of SAR imagery with LANDSAT MSS imagery is feasible from a technical viewpoint, and useful from an information-content viewpoint
Synthetic Aperture Radar (SAR) data processing
The available and optimal methods for generating SAR imagery for NASA applications were identified. The SAR image quality and data processing requirements associated with these applications were studied. Mathematical operations and algorithms required to process sensor data into SAR imagery were defined. The architecture of SAR image formation processors was discussed, and technology necessary to implement the SAR data processors used in both general purpose and dedicated imaging systems was addressed
Development of the TanDEM-X Calibration Concept: Analysis of Systematic Errors
The TanDEM-X mission, result of the partnership
between the German Aerospace Center (DLR) and Astrium
GmbH, opens a new era in spaceborne radar remote sensing. The first bistatic satellite synthetic aperture radar mission is formed by flying the TanDEM-X and TerraSAR-X in a closely controlled helix formation. The primary mission goal is the derivation of a high-precision global digital elevation model (DEM) according to High-Resolution Terrain Information (HRTI) level 3 accuracy.
The finite precision of the baseline knowledge and uncompensated radar instrument drifts introduce errors that may compromise the height accuracy requirements. By means of a DEM calibration, which uses absolute height references, and the information provided by adjacent interferogram overlaps, these height errors can be minimized. This paper summarizes the exhaustive studies of the nature of the residual-error sources that have been carried out during the development of the DEM calibration concept.
Models for these errors are set up and simulations of the resulting DEM height error for different scenarios provide the basis for the development of a successful DEM calibration strategy for the TanDEM-X mission
Signal processing for microwave imaging systems with very sparse array
This dissertation investigates image reconstruction algorithms for near-field, two dimensional (2D) synthetic aperture radar (SAR) using compressed sensing (CS) based methods. In conventional SAR imaging systems, acquiring higher-quality images requires longer measuring time and/or more elements in an antenna array. Millimeter wave imaging systems using evenly-spaced antenna arrays also have spatial resolution constraints due to the large size of the antennas. This dissertation applies the CS principle to a bistatic antenna array that consists of separate transmitter and receiver subarrays very sparsely and non-uniformly distributed on a 2D plane. One pair of transmitter and receiver elements is turned on at a time, and different pairs are turned on in series to achieve synthetic aperture and controlled random measurements. This dissertation contributes to CS-hardware co-design by proposing several signal-processing methods, including monostatic approximation, re-gridding, adaptive interpolation, CS-based reconstruction, and image denoising. The proposed algorithms enable the successful implementation of CS-SAR hardware cameras, improve the resolution and image quality, and reduce hardware cost and experiment time. This dissertation also describes and analyzes the results for each independent method. The algorithms proposed in this dissertation break the limitations of hardware configuration. By using 16 x 16 transmit and receive elements with an average space of 16 mm, the sparse-array camera achieves the image resolution of 2 mm. This is equivalent to six percent of the λ/4 evenly-spaced array. The reconstructed images achieve similar quality as the fully-sampled array with the structure similarity (SSIM) larger than 0.8 and peak signal-to-noise ratio (PSNR) greater than 25 --Abstract, page iv
Software Defined Radio Based Frequency Modulated Continuous Wave Ground Penetrating Radar
Frequency modulated continuous wave (FMCW) radar allows for a wide range of research applications. One primary use of this technology and what is explored in this thesis, is imaging in the form of ground penetrating radar. To generate proper results, spectral wide-band reconstruction has been developed to overcome hardware limitations allowing for high resolution radar. Requiring complex reconstruction algorithms, the proposed method benefits greatly in terms of performance and implementation compared to other radar systems.
This thesis develops a wideband linearly frequency modulated radar leveraging a software-defined radio (SDR). The modular system is capable of a tunable wideband bandwidth up to the maximum SDR ratings. This high-resolution system is further improved through implementation of grating side-lobe suppression filters that correct for the spectral discontinuities imposed by the reconstruction. These grating lobes are managed through multiple techniques to alleviate any ghost imaging or false positives associated with object detection. The solution provided allows for generally non-coherent devices to operate with synchronous phase giving accurate sample-level measurements. Various corrections are in place as mitigation of hardware transfer functions and system level noise. First the system was theorized and simulated, illuminating the performance of the radar. Following development of the radar, measurements were conducted to confirm proper and accurate object detection. Further experiments were performed ensuring Ground Penetrating Radar (GPR) performance as designed. Applications of this work include Synthetic Aperture Radar (SAR) imaging, innovative GPR, and unmanned aerial vehicle (UAV) systems
Frequency Diversity for Improving Synthetic Aperture Radar Imaging
In this work, a novel theoretical framework is presented for using recent advances in frequency diversity arrays (FDAs). Unlike a conventional array, the FDA simultaneously transmits a unique frequency from each element in the array. As a result, special time and space properties of the radiation pattern are exploited to improve cross-range resolution. The idealized FDA radiation pattern is compared with and validated against a full-wave electromagnetic solver, and it is shown that the conventional array is a special case of the FDA. A new signal model, based on the FDA, is used to simulate SAR imagery of ideal point mass targets and the new model is used to derive the impulse response function of the SAR system, which is rarely achievable with other analytic methods. This work also presents an innovative solution for using the convolution back-projection algorithm, the gold standard in SAR image processing, and is a significant advantage of the proposed FDA model. The new FDA model and novel SAR system concept of operation are shown to reduce collection time by 33 percent while achieving a 4.5 dB improvement in cross-range resolution as compared to traditional imaging systems
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